SupplyChain Strategy attended Ivalua NOW 2026 to gather insights on the future of procurement
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Supply chain and procurement are in a state of flux. While leaders across all industries are focusing on many of the same exciting topics – AI, ESG, automation, etc. – the world around us is experiencing uncertainty. But that type of chaos often births innovation. Ivalua NOW is shaped around embracing that innovation.
Ivalua’s global event, which took place in Paris on the 11th and 12th of March, brought together over 1,500 procurement and supply chain professionals at the Carrousel du Louvre. The stunning venue attracted leaders and experts, all of whom were determined to face geopolitical chaos and the race to adopt new technologies. Importantly, that includes ensuring the human side of business remains in focus.
It’s always been the case that supply chain leaders need to adapt in order to thrive, but the key now is also being armed with the right knowledge and tools, which are only becoming more complex. Generative AI is transforming the way we work, but the focus at Ivalua NOW 2026 was on how to apply AI effectively. GenAI is no longer a buzz word: it has real-world practical applications across the supply chain. And that’s what this event – and the whole concept of shaping new horizons – is about.
The technology is real
After the first day of customer and partner meetings, talks, and workshops, the main event kicked off on the following day with an AI video of Alex Saric, Ivalua’s CMO, flying from New York to Paris in his car. Why? “Obviously we had a little fun with technology for our opening video today, but there is a point,” Saric said in his opening speech.
“Our world is rapidly changing how we live, how we work. Technology is having a huge shift. Now the video may seem futuristic – even a little bit outlandish – but actually, all the technology in it is real and available today.”
However, Saric said, while huge change is happening around us, “what is important is maintaining the right balance in our personal and professional lives. We need to embrace the new because it’s exciting; it lets us do much more. And let’s be honest – not embracing it doesn’t mean you’re standing still. It means you’re falling behind as everyone else does embrace it.”
What humans do best
That’s not to say that everything is changing. “We need to preserve the old ways of working as well, especially when it comes to people and relationships,” Saric added. “That’s really critical. Agentic AI is already starting to fundamentally transform how we work, allowing us to make faster, more informed decisions, and freeing us from a lot of the dull and mundane tasks that still consume a huge amount of our day. By doing so, it’s going to allow us to focus on what humans do best: relationships, people, strategy. Now that’s the real promise of the human-agent operating model, which is coming.”
Saric doubled down on the fact that businesses have a choice: they can resist, and watch the future be shaped for them without their input. Or they can be proactive, and start using modern tools the way they want that fits best for their organisation. He added that the aim of Ivalua NOW 2026 was to inspire attendees by showing new innovations, showcasing customers who are succeeding on their journeys, and enabling networking opportunities.
Reshaping the supply chain world
“Your job has never been harder,” said Franck Lheureux, Ivalua’s CEO, said during his keynote address. “But there is hope. You wouldn’t be here otherwise.”
Lheureux posed the questions every supply chain professional in the room is asking themselves: what talent do I need to thrive in today’s agentic world? How do I deal with cyber threats? When and how do I adopt AI for the best? How do I continue to prioritise climate change? How do I fight inflation, costs, and other impediments?
“Your impact has never been greater. You’re a force for good” – Franck Lheureux, CEO
“This is your world,” Lheureux added. “You’re reshaping your job, inventing a better future. Preparing this, a quote by Mahatma Ghandi came to my mind: ‘be the change you wish to see in the world’. You have the power to be the change, as long as you start, as long as you set yourself in motion, and set yourself in a positive direction.
“Your impact has never been greater. You’re a force for good. Every dollar you spend, you have a decisive opportunity to make it a relevant spend. Doing good for people, doing good for suppliers, doing good for your employees, society, and the planet. That’s your superpower. You have the opportunity, you have the technology, you have the appetite. More importantly, you have a mandate to make it happen.”
Acting and reacting
Lheureux inspiring words set the tone for the rest of the day. David Khuat-Duy, Founder and Chief AI Officer at Ivalua, followed with an overview of the agentic AI revolution, and what it means to both Ivalua and supply chain at large. Then, there was an educational talk through Ivalua’s innovations and trends from Pascal Bensoussan, Chief Product Officer.
Deep discussions of cutting-edge ideas and innovations continued through the day. Supply chain leaders from all walks of life presented on digital transformation, how women are driving change within procurement, why the CPO-CIO alliance is so vital, supplier dynamics, sustainability, and of course, many discussions about AI – the benefits, the risks, and beyond.
The type of guidance this event offers is invaluable. Despite the rapid pace of change, and the endless discussions about how best to move forward, forging a clear path is still a challenge. At 2025’s Ivalua NOW event, Lheureux stated that it’s hard to think about and project the future if you’re constantly forced to react on a day-to-day basis. Later in the day at this year’s event, I asked Lheureux what has changed – if anything.
“I sense that our customers have a paradoxical situation to fight the day-to-day constraints they face,” he explained. “What are the levels of a given company to cope with external shock, and still build a strategy for a long-term future? It’s supply chain resilience, and diversifying your supplier portfolio to reduce the dependency on one region.”
Ultimately, the key to moving forward proactively instead of reactively is being unlocked with technology. Lheureux added: “You need the technology to deploy best practice and policies, to shape the world, to shape the future with different results. And AI will still have something to do about it.”
SupplyChain Strategy was an official partner of Manifest 2026, and here are our insights into the event that had Vegas…
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SupplyChain Strategy was an official partner of Manifest 2026, and here are our insights into the event that had Vegas rockin’.
The first thing you notice walking into the Expo Hall at Manifest 2026 is the movement. Robotics arms stack pallets a few metres from a booth showcasing AI-powered planning platforms. Autonomous trucks sit alongside warehouse automation systems. Drones buzz overhead as software startups demonstrate dashboards that track shipments in real time.
But it is not just the technology drawing crowds. Everywhere you turn, supply chain professionals are deep in conversation. Old colleagues reconnect, startup founders pitch ideas and procurement leaders debate strategy over coffee.
Pam Simon, Conference Chair, Manifest, delivers the opening keynote speech and there’s a palpable buzz around this vast hall as she whets our appetite for what’s to come…
We first got an inkling of what was to come when we spoke to Tanzil Uddin, SVP of Content and Partnerships at Manifest, back in October: “2026 will be pushing things up a notch!” And he wasn’t wrong.
Beyond the supply chain
For three days in Las Vegas, Manifest becomes something more than a conference. It becomes a real-time snapshot of the global supply chain ecosystem.
Held once again at The Venetian, Las Vegas, the 2026 edition of Manifest 2026 welcomed more than 7,000 attendees representing manufacturers, retailers, logistics providers, startups, investors and senior executives from across the industry.
And as the event continues to grow, its purpose has remained surprisingly consistent: bringing the entire supply chain ecosystem together under one roof.
From startup summit to global supply chain hub
The event’s origins date back to a much smaller gathering, the Future of Logistics Tech Summit. That boutique event focused largely on venture investors and early-stage technology companies. The modern incarnation of Manifest emerged in 2022, when the event was relaunched with a broader vision: a forum representing the entire supply chain landscape.
Today, the conference operates under Hyve Group and has rapidly grown into one of the sector’s most influential gatherings. As Uddin explains, the goal has always been to represent the entire ecosystem. “Manifest is really a full ecosystem event dedicated to the end-to-end supply chain. We bring together startups and investors, but also supply chain leadership like chief supply chain officers and chief procurement officers from retail, manufacturing, automotive, life sciences and more.”
That diversity is visible throughout the show floor, where emerging technology companies sit alongside established logistics operators and major enterprise software vendors…
Oana Jinga, Co-Founder and Chief Commercial and Product Officer at Dexory, on how her company is helping customers obtain better visibility to power better decision-making amidst seismic innovation and transformation.
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Warehouse visibility has long been viewed as an operational issue.
Lost stock, missed orders and wasted labour are all costly and time-consuming problems. But these issues aren’t just operational, they have become increasingly board-level and strategic concerns for supply chain leaders to deal with.
Dexory’s rise
Fortunately, Dexory found a solution. The company is revolutionising the warehousing and logistics industry through AI-driven automation and advanced robotics, delivering real-time data intelligence that elevates operational efficiency. Dexory’s digital twin technology is the only platform for autonomous robots that continuously delivers data and insights on warehouse operations in real-time. The company’s robots and data visualisation platform work together to measure, track and locate goods across their supply chain journey within the warehouse. Dexory’s autonomous robots can scan up to 10,000 pallet locations per hour, digitising warehouses with unmatched speed and precision.
For Oana Jinga, Co-Founder and Chief Commercial and Product Officer at Dexory, she believes it was actually the COVID-19 pandemic that changed how organisations thought about stock visibility and inventory management. “Suddenly orders weren’t being fulfilled on time,” explains Jinga. “Products were even sometimes left in warehouses for ages and ended up being out of date or out of stock. It meant visibility really became a buzzword at board level.”
Indeed, Dexory found some light out of the darkness of the pandemic as the leadership team worked on filling that gap in the market. At the heart of Dexory’s journey are the company’s three founders; Andrei Danescu, Adrian Negoita and Jinga herself. The trio originally launched BotsAndUs out of a passion for robotics and innovation, which became Dexory in late 2022 and subsequently went through significant Series A, Series B and Series C funding rounds.
Adapting to change
Today, volatility, labour shortages and rising customer expectations are often regarded as contributing to major pressure on supply chains. Jinga believes that within supply chain and warehousing, there had previously been a misconception that throwing people at a problem acted almost like a magic wand. However, in a post-pandemic world, that doesn’t ring true any longer.
“There’s been a massive shift,” she tells us. “We don’t have the same number of people working in this industry, especially after COVID-19, which has meant companies are embracing automation and digitalisation more than ever before. There’s also another element around how we can do more with the same resources or even less, whether that is through automation or not, and understand how we can be more efficient. It’s very, very important for this industry.”
As such, Jinga is well aware of the risks that supply chain leaders face when they lack continuous, real-time visibility within their warehouses. She believes that when there is an issue, the biggest challenge is often not the problem itself but instead the knock-on effect that it brings. “For example, if someone goes to pick something from a location and it’s not there, that investigation time spirals because then they can’t fulfill the order and get it out the door because there might be trucks waiting too,” explains Jinga. “It’s not just the visibility, it’s actually being able to act on what you are seeing which will enable a more efficient site overall.”
Agile mindset
Indeed, demonstrating real-time warehouse intelligence can offer a host of benefits. This includes the likes of resilience and confidence in decision-making, particularly during disruption or peak demand periods. For Jinga and Dexory, what she encountered prior to speaking with customers was that a lot of decision-making had taken place over a long period of historical data but that data was only checked a handful of times a year and was often outdated by the time it was used. “They were checking that data maybe once or twice a year – it was really quite infrequent,” says Jinga. “Ultimately, it means that the information that you’re working on is always out of date. The difference now is having that visibility and working on it instantly because then decision-making is based on reality rather than on some sort of a trend that could be completely different now.”
In the modern world where everyone wants things immediately, having real-time visibility over data is essential in order to power effective day-to-day warehouse decisions. Jinga recognises the importance of being able to respond to disruption quickly and dealing with potential problems efficiently. “If something has happened to the stock in one of the aisles or there is a quantity issue then you can instantly deploy someone to deal with it and then all the knock-on effects of that problem are going to disappear,” she discusses. “Or you might be alerted to a much bigger investigation that you need to deal with because if something is missing, you have to work out what happened. That immediacy allows our customers to react instantly and not allow issues to pile up.”
Positive future
Looking forward, the future of Dexory is bright. In February 2026 at Manifest Vegas, Dexory announced the launch of its next-generation autonomous robots and a new software feature Storage Health. The robot is faster, more efficient and capable of capturing significantly more data across increasingly complex warehouse operations. It captures high-frequency warehouse data and continuously feeds a live view of operations into Dexory’s digital twin platform DexoryView. It is equipped with an extended scanning range of up to 60 feet and processes more data quicker.
Given the speed of transformation, Jinga believes that the key to embracing an AI-driven future is ensuring that data is kept as clean as possible. “Anything that you can drop on top of that data afterwards is going to give you good results if the input is as clean as it should be,” Jinga reveals. “I always tell our customers to start working with us because we can help get their data cleaned up very quickly and efficiently. You must ensure the data is correct otherwise the solution won’t be as effective as it can be but it won’t be the solution’s fault.”
We met with Drew Taranto, Vice President of Product Management for eCommerce and Returns at DHL, to see how supply…
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We met with Drew Taranto, Vice President of Product Management for eCommerce and Returns at DHL, to see how supply chains are still adapting to these times of constant disruption…
Drew Taranto, Vice President of Product Management for eCommerce and Returns, is focused on growth strategy across omnichannel fulfilment and reverse logistics. His role spans working with brands across multiple industries to help them expand their eCommerce capabilities while adapting to changing consumer expectations. Taranto explains that his remit is firmly product and future-focused.
“What are we doing to provide additional services for our customers? What are we doing to change the industry in light of what’s coming from end-consumers? And really helping drive that within our company through the product development lens is really what my responsibilities are.”
Distribution at the core
As a global contract logistics provider, DHL Supply Chain designs and operates distribution centres, manages warehousing and fulfilment, and supports complex supply chain operations for manufacturers, retailers and brands worldwide. Within that landscape, distribution remains the operational backbone. Taranto is clear that the biggest structural shift for DHL lies in how its customers now think about their networks. “Warehousing is one of our core offerings,” he says. “But what I would say is that there are lots of shifts in how our customer base is thinking about and building their distribution networks. What’s important to them is constantly changing…”
Exiger’s new tool will help fight against modern slavery in the supply chain
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Exiger has announced the launch of its no cost, open access website that allows global citizens, companies, governments, and NGOs to review whether a company or its supply chain is linked to state-sponsored forced labour. forcedlabor.ai empowers all companies, regardless of the size of their compliance budget, to make better decisions about who they do business with and ensure that their supply chain isn’t unknowingly profiting from modern slavery.
“Modern slavery is a blight on humanity,” said Exiger CEO Brandon Daniels. “An estimated 50 million people are trapped in modern slavery, many of whom are hidden in opaque supply chains. As part of our mission to make the world a safe and transparent place to succeed, Exiger has decided to make the world’s largest dataset on companies connected to state-sponsored forced labour available to everyone. Hundreds of thousands of companies and millions of global supply chains are impacted.”
forcedlabor.ai lets companies, citizens, government agencies, law enforcement, NGOs, and civil society enter the name of supplier or company to immediately see potential forced labour connections in their supply chains. Powered by Exiger’s proprietary AI capabilities, results are evidenced-based and actionable. forcedlabor.ai will cover a growing scope and currently encompasses People’s Republic of China (PRC) state-sponsored forced labour, Uyghur Forced Labor Prevention Act (UFLPA) risks and US Customs and Border Protection (CBP) Withhold Release Orders (WRO) exposure across virtually every industry, including retail, automotive, industrials, consumer goods and electronics, and agricultural products.
“The CCP is responsible for one of the gravest human atrocities in recent history: the genocide of Uyghurs,” said Representative John Moolenaar, Chairman of the House Select Committee on the Strategic Competition Between the US and the Chinese Communist Party, on the launch of forcedlabor.ai. “Corporate actors must be open-eyed and take action to avoid complicity in this abuse and billions of dollars in global supply chains that rely on the CCP’s persecution of the Uyghurs.”
“When our global non-profit, which helps organisations build their resilience to modern slavery and labour exploitation, was looking for a technology to provide supply chain visibility, we reviewed over 400 platforms, and Exiger was heads and shoulders above all of the others,” said Slave-Free Alliance CEO Tim Nelson. “They’ve built the world’s largest forced labour risk database with some 20 billion records, and now they’re making incredibly valuable data available to everyone, creating a level of baseline transparency never before possible.”
The tool was developed with input from human rights and supply chain specialists including Kit Conklin, Exiger SVP of Risk & Compliance, Atlantic Council Nonresident Senior Fellow and former US House Select Committee on China Senior Advisor, as well as Dr. Laura Murphy, one of the world’s foremost experts on forced labour, Professor of Human Rights and Contemporary Slavery at the Helena Kennedy Centre for International Justice at Sheffield Hallam University, Senior Associate in the Human Rights Initiative at CSIS, and former Department of Homeland Security (DHS) Senior Policy Advisor who led the UFLPA Entity List team.
“This is a revolutionary, first-of-its-kind platform that makes regulator-grade forced labor risk intelligence accessible to everyone,” said Conklin. “The scale and universal availability of this data, powered by AI, represents a new era in forced labor transparency.”
Exiger is launching forcedlabor.ai at WEF’s 2026 Annual Meeting at Davos. Exiger CEO and WEF Governor Brandon Daniels will discuss how AI and supply chain intelligence, including forced labour data, are reshaping the industrial, economic and defence landscape alongside private sector CEOs and government officials at the USA House. The first session, Boardroom to Battlefield: Winning the AI Tempo War for Economic and National Security, is at 12:15PM CET on Wednesday, January 21, and the second, From Enforcement to Advantage: The Integrated Trade Strategy Powering America’s Industrial Revival is at 2:15PM CET on Thursday, January 22. Sessions will be livestreamed. For details on all of Exiger appearances and activations at Davos, visit https://www.exiger.com/davos2026.
Simon Bowes, CVP Manufacturing Industry Strategy EMEA at Blue Yonder, discusses AI’s role in resilience
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For some time, global supply chains have been under considerable pressure. Media coverage continues to reflect the uncertainties faced across industries as diverse as construction, chemicals, semiconductors and food, among many others. News reports point to both positive developments and persistent challenges, with stories about disruption, weak demand and slow recovery appearing alongside more encouraging signals.
On the ground, these issues are causing significant problems. Research reveals that 84% of executives have experienced supply chain disruptions, ranging from route changes and extreme weather to geopolitical unrest. These disruptions complicate planning, impacting everything from production capacity to transportation costs.
On the other hand, supply chains have also proved themselves to be incredibly resilient, with organisations everywhere adapting to unprecedented levels of disruption to keep the wheels of commerce in motion. Looking ahead, however, how can organisations strike a balance between maintaining operational continuity and adapting quickly to new risks and changing market conditions?
AI-powered digital transformation
Key to long-term success is an ongoing commitment to digital transformation, particularly the deeper integration of smart supply-chain platforms and AI-driven tools that strengthen visibility and support faster, more confident decision-making.
In this context, “smart” supply chain platforms are modern, cloud-based systems designed to connect data, processes and stakeholders across the end-to-end supply chain. They replace fragmented legacy tools and spreadsheets with a unified operating environment, integrating data from internal functions (planning, procurement, manufacturing, logistics, etc) and external partners (customers, suppliers, carriers, retailers). In doing so, they provide a single, consistent source of truth across the supply chain network.
AI can play a central role in generating insights that organisations use to radically improve planning and decision-making. By processing large data sets to detect patterns, anomalies or emerging risks more quickly than manual analysis, machine-learning models can anticipate fluctuations in demand and inventory positions, using that information to inform forward planning.
AI can also recommend actions, such as re-routing shipments or adjusting production plans, to minimise disruption while automation reduces reliance on manual decision-making and speeds up response times. Together, these capabilities help organisations adapt more quickly when conditions change, as they inevitably will.
Effective integration
Despite strong potential, integrating AI into incredibly complex supply chains is not without its challenges. For instance, many networks remain extremely fragmented, with data often trapped in multiple systems that don’t communicate well. This reduces the quality and completeness of information available to AI models, meaning organisations struggle to operationalise tools consistently across relevant functions. According to Blue Yonder’s research, 82% of leaders agree that outdated technology will hinder their supply chain’s potential, and 51% state that implementing new tech is a top strategic priority.
In the rush to deliver performance improvements, some organisations have implemented AI on a piecemeal basis, deploying point solutions that address only one area (such as warehouse optimisation or forecasting) without supporting broader end-to-end decisioning. The problem with this approach is that it can easily create new barriers by reinforcing data and process silos, making it harder to share insight across functions and limiting the ability to coordinate responses when conditions change.
So, what do AI-powered supply chain processes look like in practice? Imagine a manufacturer sourcing key components from multiple suppliers across different regions. Without prior warning, a disruption, such as a severe weather event that closes a port or a supplier’s production delay, occurs. Using traditional processes, teams would need to manually piece together information from procurement, logistics and production systems to understand the scale of the problem, a task that can take hours or even days.
Armed with the appropriate data platform and AI tools, because data from procurement, production, logistics and inventory is unified, the organisation receives an early alert. AI models quickly analyse the likely impact of the problem, such as which orders will be affected, expected delays, and how production capacity will be influenced, among other factors.
The platform then evaluates scenarios around options such as alternative suppliers, rerouting via different ports, adjusting production schedules or reallocating inventory across distribution centres. It then recommends the most effective option based on lead time, cost and service commitments.
Planners can review and approve the recommended response, supported by a clear rationale. After this point, execution steps are automatically triggered across procurement, transportation partners and warehouse operations. As conditions evolve, AI continues to monitor performance and adjust recommendations, ensuring customer commitments are met and cost impacts are minimised.
In many ways, the argument in favour of using AI to improve supply chain performance and resilience has already been won. Research has shown that 80% of industry leaders say AI is already changing how they operate. Delivering on the technology’s true potential requires a shift from experimentation to scaled deployment. That means unifying data, connecting processes and equipping teams to act on AI-driven insight with confidence.
The CRO of Kallikor discusses how supply chain professionals can become more proactive and less reactive
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Poor alignment of strategy to execution plans across supply chain operations coupled to a continuous mix of internal and external disruptions are leading to a culture of constant firefighting. Last-minute fixes and costly reactive changes to address even small bottlenecks are eroding margins and confidence at the top. And, for CEOs and CFOs, this short-term mindset in the operation leaves them incapable of making confident growth bets for the future.
Instead, decision-makers need a way to shift from firefighting to foresight, with access to a safe virtual environment that enables testing of long-term strategies, quantifying the impact of even the smallest changes and aligning decisions across finance, commercial, logistics and supply chain operations.
Starting anywhere
No more reactive, day-to-day problem solving to deal with demand changes or external factors. Instead,leaders can use composable simulation to target the real pressure points that constrain growth – whether that’s in-store operations, warehouse flows, transport strategy or outdated inventory policies. By tackling the bottlenecks that matter most, businesses gain the agility to act decisively.
With a joined-up model spanning areas of operation, changes in one domain which impact adjacent processes can be modelled together – avoiding greedy optimisation which favours one function, landing additional costs elsewhere in the business. Those might include warehouse design, store operations or network flow, with the power to move seamlessly between but balance the needs of different areas as needed. That flexibility gives executives the foresight to direct resources where they’ll unlock future growth, not just satisfy immediate local operational challenges.
From composability to adaptability
Composability is crucial for adaptability. With composable simulation, businesses can quickly adapt to changing requirements or conditions across the operation. New use cases or models can be added if needed, supporting targeted improvements on-the-fly, but critically balancing each of the elements of the end-to-end flow.
Firefighting mindsets have been exacerbated by rigid rules and policies, or guardrails, in supply chains, especially when they no longer fit today’s market dynamics. Composable simulation enables businesses to simulate different scenarios that challenge those guardrails.
The short and long-term impact of changing or removing certain policies or rules can be fully tested in a risk-free environment, enabling true foresight. It’s even possible to identify new effective ways of operating across the supply chain which may have been previously overlooked due to the established, siloed structures in place.
Accessibility that drives alignment
But even with the flexibility, impact and foresight offered by composable simulation, it only creates value if the insights are accessible to decision-makers at every level, so that impact is lessened if the platform is too complex for staff to leverage and C-suite leaders can’t gain the relevant insight.
Many old-school tools demanded near perfect data and data scientist level tech talent to deliver value. That’s no longer the case. Innovations in AI and no-code models mean composable simulation no longer requires spotless data or deep technical expertise. A happy by-product is that composable simulation avoids the downsides of data aggregation necessary to feed the traditional tools.
Even if substantial gaps are present in the available data, AI can synthesise the missing elements based on the available information. Through intelligent preparation of extensive simulation experiments it is possible to describe and fully explore complex scenarios which extend beyond the bounds of what could be achieved with ‘real’ data alone.
The result is a safe environment for testing operational decisions and modelling real-world impact, accessible to all, from technical specialists to the C-Suite.
Targeted change, strategic impact
In short, composability allows businesses to leave firefighting in the past, challenge the rigid guardrails that have held them back and achieve much-needed foresight. By building modular simulation digital twins, leaders can test new strategies, expose outdated rules and see the ripple effects of every decision before committing capital. Instead of reactively addressing bottlenecks, the supply chain becomes the cockpit for growth foresight, where the C-suite can align investors, operations and strategy – and act boldly with confidence.
These milestones reflect not just commercial progress, but market validation of Exiger’s platform
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The US Army has licensed Exiger’s AI software in order to accelerate its defence acquisition, reduce lead times, and enhance operational readiness. It’s part of a multi-million collar contract that’s been awarded to Exiger to provide end-to-end supply chain risk illumiation.
“This is a revolutionary capability that will transform the way the U.S. Army approaches sustainment,” said Exiger CEO Brandon Daniels. “Our software will help identify at-risk NIINs that may be subject to undue constraints from a variety of factors. It will unlock the organic and additive capabilities that the government has invested in. And it will monitor for severe risk hiding in the supply chain, identifying where natural and manmade disasters, supplier operational and reputational risk, and foreign adversary sourcing could create disruptions in the weapons systems our warfighters depend on. Together, these capabilities deliver a more predictive industrial base, capable of responding to evolving mission needs at speed.”
Exiger has also joined forces with Palantir as part of this project, combining Palantir’s operating system with its own mission-built supply chain AI.
“This partnership combines Palantir’s and Exiger’s world-class technologies to integrate production decisions with battlefield demands, ensuring the US Army can deliver faster and more reliably to those on the front lines,” said Mike Gallagher, Head of Defense, Palantir.
“AI and automation across the supply chain enable deeper visibility, faster risk surfacing, active and proactive mitigation, and accelerated supply movement, giving commanders and portfolio acquisition executives a level of foresight and speed never before possible,” Daniels added.
Exiger has been awarded a huge contract to help modernise the detection of transshipment for the US government
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Exiger, the market-leading supply chain AI company, announced today that it has been awarded an exclusive, multi-million dollar contract by US Customs and Border Protection (CBP) to modernise the detection of illicit transshipment across global supply chains. Designed to evade tariffs, trade restrictions and sanctions, illicit transshipment is the practice of manipulating supply chains to disguise a product’s true country of origin. Exiger’s Trade AI will be adopted and deployed across CBP, serving as an additional tool for the US government’s transshipment detection capability.
Transshipment identification and enforcement are critical priorities for the Department of Homeland Security (DHS) and CBP. Convergent Solutions, Inc., DBA Exiger Government Solutions, will equip CBP enforcement offices and personnel across the US with access to Exiger’s AI platform and data to identify illicit transshipment at-scale and in real-time.
“Billions of dollars worth of global trade move through illegal transshipment channels that seek to bypass US restrictions,” said Exiger CEO Brandon Daniels. “A core CBP mission is to enforce US trade and forced labor laws, thereby helping ensure that American manufacturers and workers are competing on a level playing field. Exiger is proud to support this mission, bringing to bear the world’s largest proprietary supply chain database and the market’s most sophisticated AI.”
Exiger’s AI will be an additional resource available to CBP personnel to:
Detect illegal transshipment across global supply chains
Monitor and enforce tariff and trade regulations
Leverage Exiger’s proprietary AI models and trade intelligence data to enrich data in CBP systems and enhance decision making
Deploy AI-enabled validations of tariff classification, value and country of origin
Create automated bills of material for products and sub-components
Map the flow of raw materials and sub-components through global supply chains
Risk-score shipments in-real time
Collect tariff revenues earlier
Trace global supply chains to enhance import visibility and risk segmentation
Exiger’s proven AI solutions have been deployed across 60+ US Government agencies, including the Department of War, Department of State, Department of Energy, DHS, the intelligence community, and armed forces.
Exiger’s technology continues to earn top recognition. In April, Exiger was named an awardee on the Government Services Administration’s Supply Chain Risk Illumination Professional Tools and Services (SCRIPTS) Blanket Purchase Agreement, and was the highest-ranked unrestricted vendor awardee of the 10-year, $919 million contract. This year, Exiger was named a Leader in the 2025 Gartner® Magic Quadrant™ for Supplier Risk Management Solutions, a Best-of-Breed Solution and three-time Value Leader in Spend Matters’ SolutionMap, and a Leader in Omdia’s Market Radar: Firmware and Software Supply Chain Security. Exiger also won a 2025 STEVIE® Award for AI Company of the Year.
Jonathan Jackman, Regional VP at Kinaxis, dives into how AI is reshaping supply chain planning.
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Artificial intelligence (AI) is often seen as a threat to jobs, with a recent TUC poll showing half of UK adults worry that AI will take their job. When it comes to the supply chain sector, AI is shaping up to be a powerful tool that empowers planners to take on more creative, fulfilling roles.
The prospect of AI-enabled supply chain planning is an exciting one for both professionals and businesses. Scaling operations without the need to massively increase headcount is a major selling point for any enterprise, while for professionals, the prospect of removing the repetitive, mundane and manual processes that restrict and slow effective planning is surely a promising one.
Far from job elimination, AI is a major upgrade for supply chain workers in a number of different ways. We’re entering a new era of increasingly autonomous AI systems, which will elevate supply chain planning to new heights. So, how exactly will the day-to-day role of the planner evolve as we go further into the AI era?
Humans still in control
First, it’s important to dispel a myth: the supply chains of the future will not be “driverless”. Many believe that AI, and particularly agentic AI, has the potential to run supply chains on autopilot. This is far from reality: while AI can surface insights, automate tasks and even take action in a crisis, it will always need to be augmented by a human to fully interpret the nuances of the real-world.
This human oversight is a crucial failsafe. There will be many times where AI flags potential shortages and proposes the best way to respond, but it will only ever be as good as the insights it is fed and the guidance given by human. For example, what if it is missing a crucial bit of real-time information about an upcoming election which could lead to disruptive trade challenges? While the algorithms. may be great at crunching the numbers and making recommendations, only a human planner can assess the full context surrounding a decision before deciding action.
The future of supply chain planning isn’t AI instead of humans, it will be AI and humans. In the AI era, supply chain professionals will be the orchestrators, steering AI systems and validating recommendations with important human insights and context.
Each planner is likely to have fleets of AI agents beneath them, acting as demand forecasters, inventory optimisers and scenario simulators – feeding information back to the supply chain professionals to empower them to make the best decisions based on the maximum amount of data analysis, all done in real time.
Planners unleashed
With AI handling the mundane and routine supply chain tasks, planners will be unleashed to focus on the creative, strategic elements of the job that machines simply cannot do: building relationships, working with partners, building and selling strategy, and, of course, managing AI agents.
Consider negotiations with partners, for example, AI won’t be able to compete with a human. It will, though, supply planners with the data they need to enter those discussions armed with deeper insights than ever before, empowering them to work more effectively.
Planners will also play a critical role in shaping the very AI tools they use – training models, curating data, and ensuring outputs reflect reality. Over time, this human feedback loop will make the technology even more valuable.
One key evolutionary step we are starting to see is the emergence of Autonomous Concurrent Orchestration. Currently, many vendors focus on agents automating existing siloed processes, but in the future, we will see more agents that synchronise planning decisions across functions – procurement, logistics, manufacturing – in real time. Agent-to-agent communication will break down silos and speed up problem solving and decision making, easing the burden on supply chain professionals.
Augmenting, not replacing
Perhaps artificial intelligence is the wrong phrase when it comes to supply chains Instead, the industry should be discussing augmented intelligence, where machines unlock insights and real-time decision making that simply wasn’t possible when tasks relied on manual processes.
For planners, the AI era promises exciting change: embracing new tools and evolving alongside this technology is not only good for business, but good for the careers of supply chain professionals.
SupplyChain Strategy attended July’s Exiger Executive Forum to hear from the best and the brightest in the industry.
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Supply chain resilience is one of the most pressing concerns of modern business, whether executives are aware of it or not. That was the central theme of the Exiger Executive Forum held on July 23rd 2025. Titled Supply Chain Sovereignty in a Fractured World: Winning the AI and Geopolitical Race for Resilience, the event brought together business analysts, CEOs, supply chain and procurement executives, academics, and politicians for an open discussion around supply chain sovereignty and the urgent need to secure supply chains across myriad industries and territories.
As geopolitical events, trade wars, and threats to globalised networks threaten to destabilise global and local supply chains, the case for supply chain sovereignty, which is an organisation’s ability to control its supply chain and minimise dependence on external suppliers, becomes increasingly stark. However, a myriad of stakeholders must come together to enable organisations and nations to gain independent control of supply chains, and collaboration between industry, government, and academia is essential.
Three guest speakers joined Maria Villablanca, CEO and Co-Founder of Future Insights Network, each representing voices from within politics, business, and academia: Tobias Ellwood, former UK Minister and Chair of the Defence Select Committee; Koray Köse, CEO and Chief Analyst of Köse Advisory, Senior Fellow at GlobSEC Geotech Centre, and Board Member of Slave-Free Alliance; and Karsten Machholz, Professor for Supply Chain Management and Strategic Procurement at University of Applied Sciences, Wuerzburg-Schweinfurt.
The discussion exemplified the discordancy of priorities and perspectives among senior voices from all angles regarding security, economics, policies all impacting value chains, albeit with a shared willingness to engage in secure, competitive, ethical and innovative supply chains, fuelling businesses and economies through heightened volatility in a fractured world that is recalibrating through the era of reglobalisation.
Supply chain sovereignty: Bridging political understanding, and urgency
“It is a dangerous world that we’re entering,” Ellwood warned. “If I ask you ‘Do you think the world will be safer or more dangerous in five years from now?’, I think we’d all agree in which direction it’s going. We have to then ask ourselves how we prepare for that.” To that end, Ellwood believes an increased focus on supply chain sovereignty is both an economic and military imperative.
For Ellwood, the central issue is limited understanding, both public and private, around the urgency presented by the current risk and threat environments. Through the combination of limited knowledge around supply chain complexity and an election cycle-focused impetus to enact vote-winning policies, he believes the political class lacks both the nous and urgency to prioritise supply chain sovereignty.
“After 20 years in politics, I can safely say that many politicians are simply unaware of what’s coming over the hill,” said Ellwood. “The tide took me out to the last general election, and so I went from helping to craft and nudge policy and encourage Britain to move forward to then scrutinising what we were doing, not just at home but internationally. Now that I’m outside of politics, I continue doing those same things.”
The necessity for political engagement is not lost on Köse, who through his own experiences of researching, advising and leading supply chain organisations, has been advocating for supply chain resilience as a top line driver for economies and companies, has equally encountered the depth of that disconnect.
“At an early point I realised that geopolitics is the key denominator for all value chains and all of us in this context,” he said, adding that work is overdue but starting to be underway to bridge this gap. “The London Defence Conference, as one critical congregation, is key for you all folks to be aware of. Not only because of what they do in terms of bringing the politicians into one room to debate some of the most fierce topics of the day, but it’s all about convergence. Bringing in supply chain leaders, policy makers and technology folks with a direct approach to debate.”
Villablanca noted that Ellwood’s presence was indicative of a gradually shifting tide, however. “It’s not lost on me that here we are in this panel, talking about supply chain, and we have a former politician with us,” she said. “That is very different to some of my earliest supply chain conferences where we didn’t see that, so it’s a sign of the times. Set the scene for us around why you’re here and why it’s important to discuss the geopolitical situation vis-a-vis supply chain today.”
“I spent most of my time in politics trying to strategise, trying to go four or five chess moves ahead, and I found I was on my own,” Ellwood replied. “Politicians operate for the day, for the here and now, the election cycle; the news cycle is what keeps them busy. They’re not thinking about these things and yet the world we’re now seeing in everything… everything is being weaponised because that is the change in the character of conflict.
“But today, from my perspective, I see the world splintering into two spheres of hugely competing influences. If you look at the number of countries that have signed up to China’s One Belt One Road initiative, you’ll see that many of them are either opting or hedging their bets as to where things go.
“To make matters worse, our exemplifiers of what democracy looks like aren’t in a good place. We see what’s going on in America, British politics and so on, and Europe and America are not on the same page. We aren’t promoting global law in the sense that we had a sense of determination that we had when organisations were set up in 1945. Other nations are getting together and realising that there’s an opportunity to exploit the wobbliness of our world order and do things their own way.
“That’s where the mechanisation of just about anything comes in to cause us economic harm, to sow political discord from afar. It’s very easy to do and becoming easier simply because of the openness of our society. It means, from a rudimentary perspective, anything you do can be weaponised against you.”
“It’s very easy, from afar, to then limit your supply chains and thereby limit your capabilities. There are countries that specialise in sowing economic discord from afar. They understand and learn and know supply chains better than we do, and they can work out which missing pieces will cause our assembly lines to grind to a halt.”
That lack of preparedness, he says, is an impediment to putting the nation on a footing that could support a war effort on the scale of the World Wars.
He continued: “There’s also the prospect of preparing for war, which means that we are suddenly spending more money on defence. Our ability to switch on the supply chain levers to support military capability is not there. This is why companies that have no connection with the defence world need to think about the services they provide that might have a military bearing. In five years time, you may be called upon to do exactly that.
“That is the mindset we now need to get into. Security and economy are one and the same now, and that’s what we need to learn.”
AI, foresight, and risk strategy
The conversation then shifted to the business side, where securing critical supply chains powering key technologies such as AI, defence and security, biotech, energy and quantum computing has become a more pressing concern in the wake of a range of global disruptions through the early 2020s.
Along with broad supply chain breakdown during the COVID-19 pandemic, the geopolitical environment has become more fraught. Escalating trade wars, the imposition of sweeping import tariffs in the US and heightening tensions between America and China have thrown globalised networks into question. Alongside those challenges, Environmental, Social and Governance (ESG) directives have placed an increased onus on supply chain leaders to sanitise their supply networks against modern slavery, conflict minerals, and indirectly sourcing materials from rogue nations. The case for establishing redundancies in supply, as well as heightening visibility on an end-to-end supply basis, was thus clear amongst the panel.
“Koray, you work with a lot of different companies,” began Villablanca. “Do you think there’s a mindset issue where politics and commerciality need to come together to realise the common goal and create resilient supply chains?”
“Directly, there probably is a mindset issue,” Köse replied. “I think there is a lack of clarity about the importance of geopolitics’ impact upon supply chains, and there is certainly the capability issue of understanding the context of geopolitics.” He then elaborated on the challenge by highlighting shortfalls in companies’ predictive capabilities.
“Companies operate with risk dashboards,” he continued. “Sometimes it’s just red, yellow, green, and that’s all you have. They have a few key risk indicators like financial compliance issues, quality issues, performance issues, but you never see strategic foresight. It’s retroactive, based on historical numbers. If you look at a production line it might say, ‘We didn’t have an incident for 80 days’. What if somebody were to say, ‘We won’t have an incident in the next 100 or 80 days’? You don’t see that in production; it always looks backwards because it is built on the past.
“A big problem in a lot of the military complex, and in politics, is thinking that the next war will be like the last one. They cannot necessarily understand that asymmetric, hybrid and proxy warfare is really where things are going, and the same goes for technology. Supply chains are often built on yesterday’s technology.”
To then end, he believes supply chain leaders should be more forthright in leveraging their profound influence upon business operations: “In supply chain, we see the conversation about having a ‘seat at the table’ for decades now and I always say, ‘Just bring your own freaking table’, and invite everybody to it. Everything, every cent in an organisation, goes through you. Own that leverage and don’t run after them, invite them to come to you. Your table is where value is generated, secured and innovation and competitiveness are established. You hold the fate of the future.”
As to politics’ place within meeting this challenge, Villablanca asked Ellwood whether the political sphere could be doing more to shape the corporate agenda.
“Yes, and that last point you said is the most critical; recognising that there is a massive risk, that this is a very different world that we’re now facing, and I expect the point that’s really being made is the absence of politicians,” he said. “The politicians themselves need to be told what we need because their expertise in understanding this arena is poor.
“China now owns the periodic table. If you are into silicon wafers, where’s your serum going to come from? If you’re into magnets, where’s your Europium going to come from? You need to know this sort of detail, and it’s not just you yourself. It’s your suppliers and the suppliers of your suppliers, too.”
While supply chain transparency has undoubtedly increased in recent years, he stressed that considerable work remains to realise total visibility.
“At a recent procurement event I was astonished at how many household names were unaware of what their second and third-tier partners were doing during the procurement cycle,” Ellwood continued. “They didn’t understand the vulnerabilities, down to the SMEs, of what’s going on. If the assembly line stops then that’s quite serious, but what’s going to happen because of that stress?
“There are people who don’t understand it over here, not recognising that our competitors are deliberately looking at our supply chains and working out where that vulnerability lies. It is so that Ford stops making trucks, so that pharmaceuticals stop making medicines. Ministers are ignorant about this and we need to become better at it. This is the frontline of the next war that we’ll fight, and that war is coming.”
“I would add that some can’t fathom the complexity of certain supply chains and the vulnerability and risk associated with multiple tiers within them,” Villablanca posited. “There’s probably a translation issue with regards to business and politics around supply chain.”
To this, Ellwood stressed that international government groups hold the keys to unlocking a broader understanding within members’ respective political spheres.
“The G7, the Five Eyes Alliance, this is where these conversations need to go,” said Ellwood. “To recognise this must be a priority within the western world, we now need to have an alternative source to make sure that we can build our aircraft, we can build our factories, we can build our products. It isn’t so much the rare earth minerals themselves, but it’s the processing. Setting up a processing factory for rare earth minerals takes almost a decade.”
Here, a guest interjected with a point that hearkened back to Ellwood’s own admission that politicians have an innate directive to focus on local, vote-winning issues: “Politicians recognise there are no votes in this. The average MP will say their inbox is full of ‘fix the NHS’, ‘get the roads fixed’.”
Resolving political challenges such as those, Ellwood replied, is predicated upon strengthening economies to open fiscal headroom for public investment.
“If our economy is affected by problems with our supply chains, there’ll be no money in the treasury,” he explained. “Not for health, transport, potholes, policing, defence. It’s imperative that if you want to fill the coffers, then we need to protect ourselves. You can only do that with supply chain resilience. As a politician, you’ve got to take the people with you if you want to make the case.”
Villablanca then repositioned the conversation with regards to pressing issues around sustainability.
“There’s a lot of risk associated with our supply chains that goes beyond geopolitics,” she said. “We also have climate issues, economic issues. How do we maintain sovereignty in our supply chains while still trying to pursue goals around sustainability?”
“Supply chain transparency is something that I advocated for when I was a young consultant in the early 2000s when my hair was not so grey,” said Machholz, highlighting the gradual shift in supply chain priorities around identifying the finer details across those networks. “It isn’t a new topic and in the EU we now have the Critical Raw Materials Act.
Machholz drew the conversation towards sustainability in the context of integrity and continuity. “I’m German, and what we have is engineering power. We are good at car and machine manufacturing, but we have no natural resources. We have a little bit of coal, but all other things need to be imported. There have to be some sources to get those things.
“There’s Trump and tariffs going up and down, and we have some other geopolitical tensions affecting supply. You might say, ‘Where do I source this particular thing from? We don’t really have a second source of supply, because both of these sources are located in the same geographical spot.’ Maybe both of them are coming out of China.”
For Machholz, lessons to be gleaned around forecasting with technology’s latest predictive capabilities were presented en masse by the pandemic. “If we look at COVID, almost all supply chains were disrupted and you were running out of materials,” he continued. “You needed to be much more risk alert, and this is the problem we have already touched on: not looking in the back mirror, but using your data and turning insights into foresights to see what could happen, and then being agile and adapting.
“Sustainability could be one thing, having several sources, having alternatives, but of course, especially if we’re talking about critical raw materials, critical parts or maybe patent-protected or monopolistic suppliers, we are in an ambitious situation, put it that way, to find some alternatives.”
Machholz stressed: “This is something that each supply chain manager, CPO, and CFO, needs to understand to set boards’ scenarios. I’m pretty sure with the help of artificial intelligence we can elaborate much more on our data and predict different scenarios so we can be more prepared rather than just reactive.”
Shifting from cost-cutting to resilience
Of course, supply chain executives are under siege from an enormous breadth of challenges, whether it’s geopolitics, technological evolution as both a benefit and a threat, and shifts in consumer behaviours precipitated by those same factors. Rising to meet those challenges on all fronts, especially in a business landscape that often adheres to cost optimisation and efficiency over investing in resilience, can give rise to decision paralysis or financially-stymied strategies.
Turning to Köse, Villablanca asked: “There’s a mountain of black swan events lurking around us, ready to attack at any minute. What are the things that a supply chain leader should be focusing on today to try to build resilience?”
“To be honest, I don’t think they’re looking at building resilience,” said Köse. “What they’re doing right now is cost optimisation, looking at inflation and making sure that the profit margins are going to be protected through the bottom line, not considering top line revenue maximisation.
“I think agility and economics always need to come back to top line, which basically means in the context of normal business 101 you are producing something, that there is a want and a need and a willingness to pay, and not necessarily hyper-focusing on the cost line or saying, ‘I’m not going to produce a bunch of bullshit that nobody’s going to pay for, just because I got to claim savings to my CFO’.”
“I’m going to challenge you there,” Villablanca interjected. “I think, theoretically, that’s great, but everybody in this room is running a business. We have our own boards, people above us, board directors and so on saying, at the end of the day, you are remunerated and we are all remunerated for our quotas. How do you deal with the day-to-day management of your business as well as building that kind of resilience, agility and visibility?”
To this, Köse stressed that the difference can be made by reframing how businesses examine and counteract risk. “We’re thinking about turning the tide by really embedding foresight in risk indicators. Those risk indicators need to incorporate geotechnical, geostrategic issues with foresight,” he continued before highlighting what he implied to be a tendency for organisations to bury their heads in the sand when faced with developing geopolitical challenges.
“I published an article before Russia invaded Ukraine, about Russia getting ready to invade Ukraine, that went through loads of red tape and debate internally that calling Russia an aggressor was cancelled out from the research note,” said Köse. “They said, ‘You can’t say that’ while it was pretty obvious that Russia were clearly the aggressors.
“The supply chain-focused function needs to spread out and have these geopolitical indicators, geotech-related risk indicators, and not just the last financial report from your supplier A to Z or tier one or tier two.
“We must then tie it back to the value and revenue you’re generating. Get away from this hyper focus and obsession with savings. In that context, make your analytics smarter with a bold analysis of things that you feel uncomfortable about. Think about ‘what now?’ and think about politics. I know we eradicated politics out of business as much as we eradicated many other beliefs from the conversation, but it has to come back.”
With this in mind, he proposed that cost optimisation is to an organisation’s detriment where resilience is concerned, not to its security. “Your indicators for success are not just on the cost line item or bottom line. Your priority must be on the top line. If I sell more, I can grow. With cost optimisation you can shrink yourself to death. That’s what some countries have done with political reviews where you shrink this, you shrink that, let’s shrink here, let’s shrink there. Potholes, collapsing bridges and rail systems, come because of the shrinkage of your investment budget for public infrastructure, for example. What I have found in the last decade of the sustainability high is that it actually impeded resilience, while the narrative said it was supposed to increase resilience.”
To this, Machholz highlighted the data behind Köse’s comments that resilience offers heightened growth potential than cost-cutting measures.
“There were some studies from McKinsey which showed that companies who are investing in risk management are 4.7 times more profitable than those who don’t,” Machholz shared, stressing that businesses engaged in this mindset are missing growth opportunities.
“People just fall back and say, ‘Okay, now the risk is over, COVID is over, whatever event is over,” he continued. “‘We can just go back to business as usual’. Resilience is just extra cost, extra inventory, maybe a second supply chain that needs attention, money, and people to take care of it, and they just simply don’t do it. This is, I think, one of the big threats that we are all facing.”
Exiger Executive Forum: A closer look
The Exiger Executive Forum (EEF) in London is a global think tank that brings together elite independent voices from strategy, policy, technology and business to equip leaders with the frameworks and foresight needed to navigate the multipolar era. The EEF is exclusively curated for industry experts, analysts, policy makers, and senior procurement and supply chain decision-makers through Exiger, a market-leading supply chain AI company. The next Exiger Executive Forum ‘War-time Economics: How Europe’s €800BN Defence Spend Will Reshape Supply Chains’ will take place in London on Thursday, September 18th, 2025.
Ellwood concurred that this lack of foresight and willingness to invest in protective supply chain measures leaves businesses undefended against interruptions both foreseen and not. “We need to prepare ourselves for unexpected events to happen as the norm,” he said. “What would happen to any business if it didn’t have power for 72 hours? How would you look after your personnel? How do you make sure you salvage the business so that, after 72 hours, you can get back up and running. These aren’t questions that we naturally posed at the moment because again, we tend to park these things.
“The mentality may be, ‘The world certainly feels like it’s getting dangerous, but my life actually looks okay.’ That isn’t the right attitude. If you go to Sweden or Finland, who are much closer to the war with Russia, they are preparing in a way that we are not for a major event or incident. It may well be that when something happens and it’s the moment where governments wake up, but you shouldn’t be waiting for that moment.”
Villablanca then highlighted the recent, universal example of poor supply chain resilience bringing business, both domestic and international, to a grinding halt. “Did we learn nothing from COVID?” she asked. “Did we not take the opportunity to stress test our supply chains and look for the vulnerabilities within multiple layers?”
In response, Ellwood invited guests to consider whether the muscle developed in response to COVID’s interruptions had been allowed to atrophy. “I think that’s a question for everybody; how much of that was retained?” he asked before blending the conversation of supply chain agility with the potential for organisations to support national security should their respective nations go to war.
“During COVID, supply opportunities came about,” he said. “Everyone here today represents diverse businesses. What services do you provide that you could tweak or add value to where something else has fallen short?
“That’s where life really becomes interesting because that’s what happened in the First and Second World Wars. We called on organisations that previously had no interest in helping out with the war effort to add support and value to the wider machine and protect ourselves from a resilience perspective.”
Challenges faced by supply chains, he explained, have analogues to business that clearly marry the political and business spheres: “When we say ‘war effort’ today, it isn’t just Army, Air Force, Navy, air, land and sea. It’s now cyber, it’s space, it’s coastguard, it’s AI. This greater warfare is where a lot of the real pain will happen. As happened in COVID, it’s going to be the clever people in the industry that step forward to say, ‘I’ve already thought about this’. They’re in the patent-esque mode, they’ve done the work to say, with a few tweaks here and there, give us some extra money, and I can alter what I’m producing to provide a solution.”
The roles of government and industry
While there are clear precedents for, and incoming needs to, prioritise supply chain resilience in both the political and business spheres, the conversation made it clear that a unified front stands to offer the most impact.
The challenge, particularly in a political environment preoccupied with economic stabilisation, increased productivity, and soothed international relations, is identifying a shared north star or galvanising body to lead the shared project.
Striking at the heart of the conversation, one guest posited: “If we want to align supply chain and geopolitics moving forward with a mutually-reinforcing relationship and shared goals, joint risk assessment, a focus on resilience over efficiency, and heightened cross-disciplinary talent and data, what are the forward steps?
“What can we within industry do in partnership with governments to move this forward?”
Representing the political voice, Ellwood replied: “There are certainly supply chain improvements that you can do on a national, sovereign basis. But from where I sit, there is a wide political threat that we face and are losing right now. One of them is to do with the energy supply, and another is the threat of AI. The quantum race will be won or lost in the next five years’ time, and that will be game-changing. It simply means that if the winner can harness the power of computing on that scale, everything’s over.”
Ellwood then invoked the technological advancements made in modern wartime, stressing that political figures must wield the mindset of those times to accelerate progress.
“I would like to see some two or three Manhattan Project equivalents, if you like, to ask, ‘How do we harness modular nuclear power?’,” he said. “That’s a very easy way to keep our lights on locally. Then, how do you harness AI? Let’s make sure it is this side of the world that wins that.
“Again, there isn’t that coordination, that sense of urgency, because it’s too far down the road,” he concluded, then highlighting that opposing forces on the world stage already have the unified capabilities that many Western nations lack. “State, industry, and academia in China, for example, are all morphed into one and that gives them huge benefits in the race for these key arenas.”
Köse elaborated on this point by highlighting Turkey’s effective coalescence of business and government.
“If you think about the private-public national defence sector in Turkey, it came from being totally dependent on the US armoury to a leading innovator of drone wars,” Köse explained. “When you think about asymmetric warfare, innovative, impactful and economic weaponry, from drones to secure soldier transportation and all of that, think about what Turkey is producing right now in technology compared to others. The headway Turkey experienced in the last decade in the defence sector is unprecedented.
“That private-public sector coalition and symbiosis has covered such a need for them in a decade that many are surprised. I think that is something that Europe has to relearn, because Europe thinks a lot about public sector dominance in an area where the private sector should actually take charge. In the US, it’s the opposite. They say, ‘keep the public sector out’. The solution lies in collaboration and bringing each sectors strength to the table while leaving out their weaknesses and flaws.
While of course not advocating for adopting the political model, he agreed with Ellwood that nations like China have an innate advantage in this race. “When you think about the way that the autocratic countries are going about it, it’s the public sector dominating the private sector environment,” he said. “That’s why they’re so hyperfocused on things and they can scale but not necessarily innovate in this sector.
“I love the government when it’s in the right place to actually do something positive and impactful. But when I’m exposed to it, I usually get anxiety issues due to the lack of pragmatism, innovation and agility. But hopefully there’s this convergence of politics, business and academia driving intelligence into critical sectors and industry, and we’re trying to drive it through this think tank here.”
The unified case for supply chain sovereignty
Exiger’s Supply Chain Sovereignty in a Fractured World event was an enlightening review of the supply chain landscape and the myriad challenges and stakeholders it encompasses.
While the panellists’ conversation in many ways highlighted the disconnect between government, business, and academia, the resonating message was one of shared pressures and goals. Where governments have pulled back on the reins of public spending, many organisations have in kind adopted a cost-optimisation mindset that may protect the bottom line but opens the door to heightened vulnerability.
Where governments must consider challenges around energy sovereignty and insulating populations against the breakdown of globalised networks – as was demonstrated upon Russia’s invasion of Ukraine in 2022 – supply chain executives must create redundancies to cover lapses and minimise potential disruptions to production and wider organisational integrity.
The guests’ final comment, that states which can marry both the public and private spheres towards shared interests, neatly encapsulates the urgency with which those worlds must reunite. While much work remains to enmesh those spheres, it is clear that the conversation is progressing at pace.
Simon Bowes, CVP Manufacturing Industry Strategy EMEA at Blue Yonder, on how to navigate challenging situations in supply chain.
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Organisations worldwide continue to face severe supply chain disruptions, creating immense operational challenges. Compounding these difficulties is a bleak economic outlook that shows few signs of improving, keeping consumer confidence stubbornly low.
Meanwhile, experts are claiming that President Trump may stand firm on his plans for sweeping global tariffs. This is despite a US trade court ruling that the President had exceeded his authority in imposing the duties and ordered an immediate block on them – only for a federal appeals court to temporarily reinstate the most sweeping of the President’s tariffs. This means tariffs remain an ongoing problem and, the UK market will likely face further disruption.
When you factor in increased costs, labour shortages, escalating geopolitical tensions, cybersecurity attacks, and weather-related disasters (like the $27 billion in damages seen in the US alone), it’s evident that constant instability has become the new normal for supply chains.
Senior executives agree, with 84% stating in a recent survey, that they have encountered disruptions within their supply chain over the past year. Therefore, organisations must be prepared for the unexpected, understand the potential consequences, and have a plan in place to mitigate such risks.
How can organisations create a strategy for the unpredictable? The answer is by building a comprehensive plan that integrates the capabilities, processes, and technologies needed to operate efficiently, no matter what happens.
End-to-end supply chain planning
The first step is to create an overarching strategy that encompasses the entire supply chain. Having visibility across all areas will support synchronised planning and communication across disparate functions.
When organisations bring together teams and processes, they can start to overcome the traditionally fragmented approach to supply chain management. Uncoordinated procedures inevitably create an inefficient and weaker supply chain, which makes it particularly vulnerable to disruptions.
Whereas, resilience is strengthened by collaboration between functions, if backed with integrated data systems and communication methods to enable sharing of real-time information. Keeping all parties in the loop, with relevant data and meaningful insights, encourages better and faster responses to problems, as well as increases awareness of potential forthcoming issues.
Ideally, what’s needed is an end-to-end connected platform where all departments, offices and sites are working from the same consistent, up-to-date data. And, are not required to change systems to find or cross-check relevant information and iron out anomalies.
Smart decision making with AI and automation
Next, it’s vital to incorporate intelligent automation to improve and speed up decision making. Companies are already using data tools to forecast supply and demand planning, but they now can incorporate AI’s ‘always-on’ capabilities to dynamically evaluate and adapt to changes in supply and demand.
AI-powered solutions can assess how work is progressing by automating data gathering for analysis and optimisation. Automation can handle routine issues, leaving supply chain professionals free to focus on more strategic tasks. Furthermore, AI can facilitate transparent, trackable decision-making to accommodate predicted supply chain disruptions or react to unexpected ones. This level of auditing provides vital insights that will help refine future decisions and actions for the next time similar circumstances materialise, improving outcomes in the long-term.
Additionally, organisations can leverage AI to predict the likelihood of disruptive events happening. Knowing how often they occur and how they have unfolded in the past can inform decision-making and planning. Whether that’s examining competitor behaviour or economic trends, AI tools can process millions of pieces of real-world data to model likely what-if and worst-case scenarios that could impact the supply chain. While these instances may seldom occur, proactive scenario pre-planning provides the foundation for an effective response in the event of real-world disruptions or disasters.
Organisations should identify the specific issues which present the highest risk to their business and ensure appropriate mitigation measures are ready to be activated immediately they are needed.
Investment in flexible, agile solutions
Restrictive working practices coupled with outdated technology can make it harder to react effectively when disruptions occur. Building long-term supply chain resilience means finding a best-in-class solution and partner with deep domain expertise to guide deployment of appropriate modern technologies.
When considering options, businesses should keep in mind fundamental requirements for flexible, agile technologies. These include checking how a software or platform supports data integration and cross-organisational collaboration, whether it can simulate market conditions in near real-time, if the technology architecture is compatible with AI, and how easily does it scale.
It’s critical to have a technology platform that’s designed for scalability and extensibility to manage changing workloads and requirements. Therefore, organisations should look for products with a cloud-native architecture for scalability and resilience, a microservices-based approach for flexibility, and solutions that are easy to configure and maintain without specialised IT expertise.
Building a resilient supply chain
In today’s volatile business landscape, organisations must embed resilience into their end-to-end supply chains, supported by the right technical infrastructure. Investing in modern technologies and platforms offers additional advantages. Advanced solutions that adapt easily to changing conditions, automate manual processes, and harness the power of AI can also provide a competitive edge. For instance, AI’s ability to crunch and analyse vast amounts of data can reveal hidden opportunities stemming from unexpected events—opportunities that might have been overlooked previously.
By making smart technology decisions, organisations can build more resilient supply chains, enabling them not only to survive in current unstable conditions but also to optimise performance and operate more profitably.
By Mohammad Mesgarpour, Head of Data Sciences at Microlise, discusses why we need to think beyond data when it comes to logistics.
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Data is everywhere — often invisible, but constantly at work behind the scenes. As we move through our day, it quietly powers much of what we experience. A simple card payment in a shop sets off a chain reaction: your bank processes the transaction, the store updates its stock levels, capturing vehicle location and driving behaviour location data by telematics box, and the company’s central system records the sale.
It’s data that informs the display board on a train platform, letting you know your train is just two minutes away. From our morning routines to our evening commutes, data is woven into how we live in 2025.
And the scale of it is immense.
Today, it’s estimated that there are around 181 zettabytes of data globally. That’s equivalent to one trillion gigabytes or one billion terabytes. In just a few years, this figure is expected to soar to 394 zettabytes — a rapid expansion that highlights just how central data has become to everyday life.
We may not always see it, but at every digital touchpoint, data is shaping the world around us.
Data in logistics
The logistics industry has long recognised the value of data and has been quick to adopt technologies that help improve performance and efficiency. As new tools and systems have emerged, the sector has consistently found ways to use them to its advantage.
It started with the basics. Early telemetry services, such as GPS tracking, gave operators a clear view of their vehicles’ location on a map – a simple yet powerful tool. From there, the industry moved into deeper insights, analysing fuel consumption patterns and driving behaviours to improve overall fuel efficiency and road safety.
Since then, the capabilities have expanded significantly.
Today, vehicles can generate ten times more data than they did just ten years ago. Thanks to advances in both hardware and software, operators now have access to a wealth of information that can transform decision-making and drive smarter logistics operations.
But this volume of data doesn’t come without challenges. More data doesn’t always mean better outcomes or deeper insights. Businesses are beginning to recognise that without the right systems; high-quality and relevant data; and effective analysis, they can become overwhelmed rather than empowered.
The real opportunity lies not just in capturing data, but in turning it into meaningful, manageable and actionable insight. It can drive operational efficiency, informed decision-making and measurable business outcome.
The appliance of data science
It’s easy to assume that simply collecting data is enough to transform logistics and haulage operations. But in reality, raw data alone won’t deliver results. To drive real value, that data needs to be refined, analysed in context of strategic business objectives. This is where the real analytical challenge begins.
There’s a well-known saying in data science: garbage in, garbage out. And it’s more relevant than ever in an era where artificial intelligence tools – like ChatGPT – are increasingly part of the conversation where the quality of data directly determines the accuracy and effectiveness of the AI model’s output.
Anyone with deep subject matter expertise will quickly spot the flaws when these models are asked about highly specific topics. They may generate convincing answers based on flawed or outdated sources, and while experts can see through the inaccuracies, others may accept them at face value. When that misinformation is reused and reinforced, the cycle continues, leading to skewed conclusions and poor decisions.
The bottom line? Better data leads to better outcomes.
This principle becomes even more important in real-world applications, such as complying with the government’s updated requirement to inspect trailer braking systems at least four times a year instead of once. With accurate, well-managed data, operators can confidently predict when inspections should take place, helping to reduce downtime, avoid unnecessary checks and keep fleets moving efficiently.
Turn around, go back
Geofencing is another area where accurate data is critical to the success of logistics operations. When systems misreport how long a delivery takes after entering a geofence (delivery site), the ripple effects can disrupt far more than just one delivery.
Inaccuracies here can throw off turnaround times, leading to incorrect arrival and departure times, delayed subsequent jobs, inaccurate performance metrics and ultimately frustrated customers. What begins as a small data issue can quickly escalate, leading to missed expectations, strained relationships and inefficiencies across the board. Moreover, if this inaccurate turnaround time is fed into a machine learning model to improve future logistics planning, it can lead to a systematic degradation in the model’s reliability and usefulness, and consequently, in the effectiveness of the plan itself.
High-quality data helps avoid these pitfalls entirely. When the source information is precise, the systems built around it work as intended. And importantly, solving data issues upstream before they feed into larger workflows is far simpler than trying to fix the consequences later on.
In logistics, precision isn’t a luxury. It’s essential.
Open source informs much more
Modern technology plays a key role in identifying the behaviours that impact operational efficiency. Actions like harsh braking, rapid acceleration or excessive cornering speed all contribute to increased fuel consumption. And today’s systems don’t just monitor them, they help correct them. Moreover, onboard sensors and telematics devices track and monitor vehicle health in real time, flagging issues before they become costly problems. Whether it’s the driver, the transport manager or fleet manager, having this information early enables proactive maintenance rather than reactive fixes.
The story doesn’t stop at the vehicle.
Open-source and crowd-sourced data brings another layer of intelligence, offering a broader context that goes beyond what’s happening inside the cab. By combining internal data with external sources, hauliers can gain insight into accident-prone areas, localised weather patterns or planned road closures; all of which influence route planning and delivery performance.
This level of enrichment adds real value. Rather than simply receiving updates every mile or minute, operators benefit from a fuller picture of the journey, making location data smarter, not just more frequent.
Reporting for duty
Accurate data – whether it’s tracking punctuality, fuel consumption or driver performance – underpins a wide range of operational reports. These insights can be tailored to suit each customer’s needs, helping them streamline operations, drive efficiencies and stay competitive in a fast-moving industry.
As we move toward an expected 394 zettabytes of global data by 2028, the value of this information lies not just in volume, but in context and quality. Future data won’t simply indicate what happened, it will increasingly help explain why it happened, too.
Take driver behaviour as an example. Instead of just recording that a driver braked harshly, new systems will identify the circumstances behind the action. This shift means drivers will be recognised for making safe, responsive decisions rather than penalised by isolated statistics.
It’s a powerful step forward. But unlocking the full potential of this data-driven future depends on how well the information is used. Data must be processed, applied and interpreted thoughtfully.
When done right, it not only enhances internal operations, but it also delivers measurable value to customers as well.
Charles Crossland, Managing Director at Goodman UK, discusses the unique challenges the food supply chain is facing.
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The food supply chain operates under unique pressures. With short product life cycles and a complex journey from source to shelf, it must navigate strict regulatory demands, price volatility, and increasing consumer expectations – all while maintaining speed, freshness, and traceability.
In recent years, global disruptions have exposed vulnerabilities. From reduced access to imported goods to increased transport costs, the sector has had to rapidly adapt. In response, many businesses are turning to technology and data-driven strategies to build resilience and agility into their supply chain operations.
Building resilience in a volatile market
Stock shortages are no longer unusual, and customers are increasingly aware of the fragility of food supply systems. There’s now greater scrutiny on how food moves through the supply chain and growing pressure on businesses to deliver consistency and transparency.
Businesses are adopting new technologies such as artificial intelligence (AI), predictive analytics, and automation to improve supply chain visibility and performance. AI-powered forecasting tools, for example, can help businesses respond faster to demand fluctuations, minimising waste and reducing risk.
At the same time, many have moved away from “just-in-time” approaches for non-perishable goods and are reassessing their sourcing strategies. Dual sourcing, diversified supplier bases, and increased inventory holding are helping to minimise risk and prevent single points of failure.
Smart logistics and strategic warehousing
The transport and distribution stages of the supply chain are also evolving. Soaring fuel prices, labour shortages, and carbon targets are forcing businesses to review delivery routes and optimise their warehouse networks. Proximity to customers is now more important than ever.
By investing in strategically located distribution hubs — close to major infrastructure and consumer populations — businesses can reduce lead times, optimise last-mile logistics, and cut transport-related emissions.
All logistics operations, from warehousing to transport, are increasingly equipped with smart systems for real-time tracking, allowing for greater control over stock movement and condition. For temperature-sensitive goods in particular, the use of tracking sensors helps monitor freshness, reduce spoilage, and maintain product quality throughout transit.
Extending freshness through technology
Warehousing is undergoing a quiet revolution. Robotics and automated systems are now performing tasks such as picking, sorting, and packing with improved accuracy and speed. This is especially valuable in the food sector, where shelf life and freshness are key.
Technologies being deployed include:
Grading visibility systems which assess produce quality and reduce manual handling
Advanced freshness testing which pinpoints stages of ripeness with precision
Specialised climate control systems, including zoned heating and cooling, to maintain product quality
By reducing errors, extending shelf life, and improving product flow, these innovations contribute directly to reduced food waste.
Sustainability as a supply chain driver
Sustainability is no longer a nice to have — it’s becoming central to how supply chains are designed and operated. The environmental impact of food production and distribution is under growing scrutiny from regulators, retailers, and consumers alike.
Businesses are now expected to track and report on carbon outputs across their operations. Efficient route planning, electrified fleets, and eco-friendly packaging are just some of the areas seeing rapid investment.
Data is critical here too. By using detailed analytics, organisations can identify hotspots for energy use or waste and adjust operations accordingly. Many are now measuring not only emissions but also transport efficiency in a bid to reduce their environmental footprint.
Looking ahead: A tech-enabled, resilient future
Incorporating smart technologies into warehouse workflows and logistics strategies is already delivering benefits — from productivity gains to improved safety and fewer errors. But this is just the beginning.
As food supply chains grow more connected and responsive, businesses will need to continually adapt. The future will be shaped by those able to combine agility with long-term planning — embracing innovation, forming deeper supplier relationships, and keeping sustainability at the core.
Without trust, AI cannot deliver on its full potential, leaving manufacturers hesitant to go beyond pilot projects, says Darren Falconer.
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It’s no secret that trust is the foundation for successful AI adoption. By addressing scepticism, prioritising data quality, and ensuring algorithms are explainable and auditable, AI can become a powerful force-multiplier in manufacturing operations.
Manufacturers are increasingly looking to AI to boost efficiency, streamline operations and automate routine tasks. 75% are planning to step up their AI spending in 2025. However, much of this attention is focused on Generative AI – something that we believe is poorly suited to factory settings.
Part of this misalignment stems from a lack of understanding of AI’s practical applications in industry. With only 7% of manufacturing leaders feeling “very knowledgeable” about AI applications, scepticism and trust issues loom large.
Feedback from vendors and end-users consistently points to trust as a leading barrier to adoption. Without trust, AI cannot deliver on its full potential. This leaves many manufacturers hesitant to go beyond pilot projects, XpertRule’s Technical Director, Darren Falconer explores this further.
Overcoming the AI ‘fear factor’
The portrayal of AI in the media has long been dominated by dystopian headlines and Hollywood blockbusters, with fears of mass unemployment and doomsday narratives. For manufacturers, this continuous, subliminal bombardment creates a trust deficit before any AI project even begins.
Business leaders are having to overcome not only technical hurdles but also the deep-seated scepticism that AI solutions are uncontrollable or inherently risky. To counter this, companies must approach AI with transparency and explainability at every stage, showing that AI is a tool to amplify human capability not replace it.
For a simple comparison, think about cruise control in a car. [within cars today,] Traditional cruise control maintains a set speed but that’s all. Compare that to adaptive cruise control, which considers real-time conditions, adapts to your driving preferences and responds intelligently. Similarly, AI in manufacturing must adapt to the unique needs and complexities of each operation.
For those implementing these systems, understanding the ‘mechanics’ – how algorithms interact with data inputs and external influences – is a vital part of building trust. Explainable AI bridges the gap between automation and operator oversight, providing a clear view of how the system reacts and adapts. This clarity increases confidence among users, fostering trust in AI’s outputs.
But of course, building trust also requires a mindset shift – from a data-centric focus to a decision-centric approach.
Trust starts with decisions, not data
A common misstep in AI adoption is starting with the data instead of focusing on the desired outcomes. Many manufacturers think, We have all this data – what can we do with it? However, this approach often leads to complex systems that lack focus, transparency, fail to deliver meaningful outcomes and reinforce doubt over AI’s value.
A decision-centric approach begins by asking, What do we want to achieve, and what decisions need to be made to deliver those outcomes? Only then should businesses ask, What data supports those decisions and what are the models linking these decisions to this data?
From there, manufacturers must focus on ensuring data quality – calibrating sensors, cleaning data streams, validating inputs and standardising formats. Remember, the vast majority of AI success lies in data preparation and only a small percentage in the modelling itself.
Imagine a manufacturer aiming to improve quality control. They might gather extensive data from every step of the production process to find possible defects, leading to an overwhelming volume of disjointed data with no clear path to action.
Using a decision-centric approach, they would:
Define the goal: Improve product quality and aim to reduce defects by 10% over the next quarter.
Identify key decisions: What factors directly impact product quality? What parameters should trigger quality checks? How can inspection processes be optimised to catch defects earlier? What actions should be taken when deviations are detected?
Use AI to model the outcomes: Build AI models that analyse historical production data , to discover explainable patterns relating outcomes to metrics like machine settings, material consistency or environmental conditions. The system can then use these models in real time to flag anomalies that indicate potential defects and recommend adjustments to maintain product quality.
This clarity in purpose makes AI implementations transparent, explainable and, ultimately, more trustworthy. It also provides a clear framework for measuring success, helping to build greater confidence from engineers, users and management alike.
Decision intelligence – the missing link
A key factor in building trust is recognising that AI doesn’t replace human insights and experience – quite the opposite. Human operators and engineers bring a level of expertise, contextual knowledge and intuition that machines cannot replicate. Having a ‘human in the loop’ is therefore critical to an AI system’s effectiveness.
Decision Intelligence connects Explainable AI principles with operational trustworthiness by embedding human oversight at its core. For example, experienced technicians possess knowledge built up over years of practice. While they can’t be everywhere at once, their expertise can be integrated into AI systems to automate routine decisions while reserving complex or ambiguous scenarios for human intervention.
This balance between human and machine intelligence ensures AI systems remain transparent, reliable and dynamic. It also enables manufacturers to scale the knowledge of their experts, reducing variability across shifts and locations while maintaining trust and accountability.
From pilots to trusted partner
For AI adoption to move from pilot projects to the heart of manufacturing operations, trust must come first. A decision-centric approach offers a practical pathway to achieve this, ensuring AI systems are transparent, aligned with business goals and designed to augment human expertise.
When manufacturers trust their AI systems, they can harness the technology’s full potential, creating new opportunities for efficiency, resilience and competitive advantage. Decision Intelligence becomes the connector between Explainable AI and operational trust, moving AI from being perceived as a risk to becoming a trusted partner.
Sylvain Rottier, General Manager at Tennant Company, explores how supply chain professionals are shoring up against labour shortages.
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Europe is facing an ongoing workforce crisis that demands major solutions, meaning business leaders can’t really afford to wait. The numbers are disconcerting: labour shortages across the European Union have grown from 1.7% in 2014 to 2.6% in the first quarter of 2024—a 53% increase that shows no signs of slowing.
Indeed, Europe’s demographic crisis seems to be accelerating, with projections indicating the continent will lose 95 million working-age people by 2050 compared to 2015 levels. For supply chain executives, this threatens operational continuity and competitive positioning.
The impact may vary dramatically across sectors, but few industries will feel the pressure more acutely than essential services like cleaning and facilities management. Annual turnover rates in janitorial services have reached 200-400%, creating a revolving door that diminishes institutional knowledge and operational effectiveness.
The impact beyond empty positions
Twenty-five percent of EU businesses now report production problems directly attributable to labour shortages, transforming what was once a staffing inconvenience into an operational constraint.
The financial implications are potentially severe. Companies experiencing 200% annual turnovers —unfortunately common in labour-intensive sectors—spend six-figure sums annually just on replacement hiring. This figure encompasses recruitment costs, training expenses, and the hidden price of reduced productivity during onboarding periods. However, these costs represent a small part of the problem.
Quality degradation becomes inevitable when organisations rely heavily on inexperienced workers. Higher error rates, missed cleaning protocols, equipment damage, and inconsistent service delivery damage customer satisfaction and brand reputation. In supply chain environments where precision and reliability are paramount, these quality issues can trigger costly disruptions throughout the entire network.
Perhaps most concerning is the competitive disadvantage that emerges when labour shortages force companies to reject new business opportunities. Constrained order books and inflated production costs create a vicious cycle where struggling organisations become less attractive employers, further exacerbating their staffing challenges.
From automation to intelligence
Traditional automation offered limited relief because it required extensive programming for specific tasks and was often an awkward-at-best fit for changing conditions. Today’s AI-enabled robotic systems represent a huge leap forward, delivering true operational intelligence that can learn and adapt, and also optimise performance in real-time.
Modern robotic platforms (such as BrainOS, which power Tennant AMR Machines) leverage machine learning algorithms to improve their performance based on environmental feedback and operational data. Unlike their predecessors, these systems can navigate complex, dynamic environments while avoiding obstacles, adjusting cleaning patterns based on usage data, and even predicting maintenance needs before equipment failures occur.
Integration capabilities have also come a long way. Contemporary AI-powered robots connect with existing warehouse management systems, inventory tracking platforms, and facility management software. This connectivity enables centralised monitoring, performance optimisation, and data-driven decision-making that extends far beyond the robots’ immediate task purpose.
The technology’s greatest advantage lies in its ability to maintain consistent performance standards. While human workers may struggle with fatigue, illness, or high turnover, AI-enabled robots deliver consistent results that enable accurate capacity planning and service level guarantees.
Implementation strategy
Successful AI-robotics deployment requires a shift in thinking from replacement to augmentation. The most effective implementations complement human capabilities rather than eliminate human roles entirely. This approach not only addresses practical concerns about workforce displacement but also maximises return on investment by leveraging the unique strengths of both human intelligence and artificial intelligence.
Smart organisations begin with pilot programmes that target specific, well-defined tasks within controlled environments. This approach allows teams to understand integration challenges, optimise workflows, and build internal expertise before scaling to full deployment. Critical success factors include ensuring compatibility with existing systems, establishing clear performance metrics, and maintaining open communication with affected workers throughout the transition.
The skills landscape is evolving rapidly, creating new job categories in real time. Rather than eliminating careers, thoughtful implementation transforms traditional roles into technology-empowered positions that offer greater career advancement potential and higher compensation. For sectors like cleaning services, which have long struggled with “dead-end job” perceptions, this transformation can meet turnover rates with higher-calibre talent.
Training programmes should prepare workers for collaborative environments where human judgment combines with robotic precision. These hybrid roles often prove more engaging and rewarding than traditional positions, creating career pathways that retain institutional knowledge while embracing technological advancement.
Building tomorrow’s competitive advantage
The demographic trends driving current labour shortages will intensify over the coming decades. Organisations that delay AI-robotics adoption risk falling behind competitors who embrace these technologies early and develop operational expertise while the market is still developing.
However, successful transformation requires more than technology acquisition. Companies must strike a balance between technological capabilities and the human touches that drive innovation, customer relationships, and adaptive problem-solving. The goal isn’t to create fully automated facilities but to build resilient, flexible operations that can weather demographic headwinds.
Leadership teams must think beyond immediate cost savings to consider long-term strategic positioning. AI-enabled robotics offers the foundation for sustained growth in an environment where traditional staffing models look increasingly untenable. Early adopters will develop competitive advantages that compound over time, while late movers may find themselves perpetually disadvantaged in both talent acquisition and operational efficiency.
The question isn’t whether AI-enabled robots will reshape supply chain operations—that transformation is already underway. The critical decision facing business leaders is whether they’ll proactively shape this evolution or reactively respond to competitive pressures once their options become more limited and expensive.
Europe’s demographic winter demands timely action. For forward-thinking supply chain executives, AI-enabled robotics represents not just a solution to current staffing challenges, but a strategic foundation for long-term competitive success in a potentially shaky marketplace.
Mark Wilkinson, Senior Vice President for OpenText’s Global Business Network, discusses AI-driven success in supply chains.
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AI in industry
AI might be transforming industries, but its ability to drive accurate workflows relies on a foundation of reliable data. For those working with supply chains, this data can generate assessments of global circumstances and highlight upcoming disruption to operations before it’s felt by the consumer.
In the past year, extreme weather, trade disputes, and geopolitics have tested the limits of business preparedness. For example, in October 2024, it was estimated that the storms that hit Valencia caused damage to its farming industry worth almost £1bn. That includes the produce lost and the rendering of underlying infrastructure as unusable. As the impact of the climate crisis drives an increase in natural disasters, supply chains must prepare for widespread disruption.
Looking to 2026 and beyond, this trend is unlikely to change for the better. To best future-proof business processes, AI will be fundamental. But where should organisations start?
Which data is good enough?
High-quality, accurate data is important for driving AI success in supply chains and providing users with accurate predictions. This enthusiasm is reflected in the expectation that the big data market will be worth over £300 billion by 2028. Despite this significant investment, most organisations, surveyed across industries, still face data-quality issues.
At present, only 12% of data and analytics professionals believe that their company’s data is ready for AI adoption despite 76% recognising data-driven decision-making as a priority. To drive success in supply chains, this lack of readiness needs to change.
Data preparation
Though action must be taken to remedy these concerns, companies shouldn’t view the quality of their own data as a blocker to innovation. Instead, they can ‘test’ the data before using it to drive insights.
As a first step, it’s essential to identify the format and quality of existing data assets. With complete knowledge of all the information available, corporations can integrate AI tools that work with their data, instead of trying to fit it into incompatible solutions.
Next, team leaders must be certain that their employees are trained on noticing hallucinations and changing processes to ensure accurate AI forecasting. Creation of the right procedures will feed into a successful long-term data governance strategy, ensuring full value is extracted by AI tools.
For ongoing insights, directly reflecting global circumstances, data must be continually fed into AI systems. By setting up the extraction of data from a reliable platform, companies can ensure that the insights they receive directly correspond with the most pressing logistical concerns.
Incompatible sources
Strategic partnerships can bring essential expertise for agile transformation, helping companies to scale at speed and improve their assessment of risks. For instance, by integrating data from a partner organisation, visibility across the global logistics landscape will be increased. Concerns arise, however, when data is formatted differently at each company. To mitigate the chance of hallucinations, data-trained workers should be proactively advised to scan insights for duplicates, misspellings, and inaccurate information.
Visibility
For operational success amid an ever-changing global landscape, the importance of preparing and ‘cleaning’, data should not be understated. To ensure accurate insights are produced by AI tools, integrated solutions should be compatible with current data-formatting, proactively mitigating the chance of hallucinations. To derive full value, the same ‘cleaning’ procedure should be used for partner data. By taking the right steps at the beginning of the adoption journey, business leaders can drive effective insights, consistently being updated, to support future growth.
Camilla Gilone and Jorge Gouveia de Oliveira from Heidrick & Struggles, explore how supply chains can maximise the value of new AI tools.
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The potential for artificial intelligence to transform supply chain costs and performance is immense. From forecasting and procurement to customer delivery and service, it’s a sector to which the data analytics, automation, and modelling capabilities of AI are ideally suited.
But despite the potential for a perfect partnership, AI adoption in supply chains remains low. What’s more, companies implementing AI solutions often seem to be doing so without a clear value proposition. Adoption is driven by hype, not business need.
The Chief Supply Chain Officer (CSCO) should be the driving force in achieving intelligent AI implementation through the supply chain. Successful adoption will require leaders who understand where to employ AI for the most significant impacts.
Why supply chain AI adoption is lagging
Adoption of AI in the sector is being delayed by several limiting factors. Foremost is the skillset gap. From the board to the CSPO, leadership needs to improve AI fluency in order to make the right implementation decisions. Competition is also fierce across the talent market for AI and data experts, with a premium on those experienced in the operational nuance of complex supply chains.
AI continues to receive criticism for not presenting its ‘thought process’. Poorly designed supply chain systems risk becoming ‘black boxes’, making unchallengeable decisions without giving stakeholders clear rationales. While GenAI can provide reasoning narratives, full explainability remains limited, especially for deep learning or complex statistical models.
Risk accompanies the introduction of any new technology, and is multiplied when rolled out across a complex supply chain. AI implementation requires meticulous design, with an emphasis on transparency. As AI expands into warehouse operations, maintenance, and planning, critical questions must be asked around whether systems should be modular or integrated end-to-end; and where governance for autonomous decision-making lies.
A perception barrier to AI adoption also exists. By focusing on cost-cutting, and implementing point solutions to fix specific issues, organisations are overlooking AI’s strength in optimising value across the supply chain. By enhancing margins, resilience, and service levels, it can be a value creation enabler, not just an efficiency tool.
Where AI can benefit supply chain management
Overcoming these barriers presents opportunities to improve supply chain efficiencies, increase capacities, and lower costs, with use cases including:
Responding rapidly to market shifts
AI’s use of real-time data to predict, optimise, and adapt means it can prioritise inventory for high-margin products; guide dynamic pricing, allocation, and fulfilment; and circumvent bottlenecks.
Improving logistics decision-making
AI maps likely scenarios and plans responses, helping leadership to make faster, better-informed decisions. It uses learning loops to adapt, delivering smarter outcomes over time.
Bridging business and technology
GenAI improves accessibility and adds transparency by allowing users to interact directly with complex systems in natural language, making it a collaborative business partner.
Improving customer experience
By detecting patterns in customer churn, AI can drive operational improvements, while also performing sentiment analysis, aggregating high volumes of unstructured feedback to identify what issues influence customer satisfaction.
Aligning stakeholders
For supply chain stakeholders, AI offers shared visibility on cross-function activities. By integrating planning and procurement through data, organisations can gain greater resilience and commercial agility.
Meeting ESG goals
AI tools can measure emissions, evaluate ethical sourcing, and ensure regional regulatory compliance to help reach sustainability targets.
The role of the CSPO in harnessing AI
With these advances, the role of the CSPO is evolving. What was once an operational and tactical job, focused on the movement of goods and management of supplier relationships, is now a broader strategic one, designing an AI-enabled central nervous system to create competitive advantage.
To harness the potential of AI, CSCOs will need to be data-fluent: understanding how AI algorithms reason, and able to manage intelligent systems spanning automated procurement, real-time shipment routing, and inventory optimisation. They will oversee global supply chains via an AI dashboard, making fast, agile decisions based on multiple live information streams, and surfacing enterprise risk factors.
CSPOs will simultaneously have to spearhead a talent transformation, shifting teams from manual and operational roles to strategic ones where they work alongside machine intelligence. This means reskilling existing talent, creating cross-functional partnerships, and hiring data specialists who can apply their skills to supply chain challenges.
How the supply chain sector can reap the rewards of AI
The evolution of supply chains through AI is not a distant vision. It’s today’s reality, and it’s defining how organisations operate and compete. For the modern CSCO, AI is more than an efficiency tool. It is a catalyst for strategic leadership which enables smarter decisions, greater resilience, and customer engagement.
Realising the trechnology’s full potential goes beyond an adoption program. It demands thoughtful business strategy, cross-functional talent, and commitment to transparency and explainability. Companies that align AI initiatives with positive business outcomes and empower people to work with intelligent systems will unlock unprecedented value.
In an increasingly complex, volatile environment, AI-powered supply chains will be the difference-makers. The technology will turn risks into opportunities and supply chains into engines of innovation and growth.
Dr. Jan Kunkler, Principal Data Scientist at Lobster, looks at the potential of agentic AI to solve supply chain problems.
Published
6 June 2025
Estimated Read time
6Mins
Dr. Jan Kunkler, Principal Data Scientist at Lobster, looks at the potential of agentic AI to solve supply chain problems.
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The global supply chain is in constant motion. Organisations face persistent disruptions, evolving regulations, and urgent calls for greater sustainability and resilience. Artificial Intelligence (AI) is widely seen as a transformative solution to this ongoing turbulence.
Yet, beyond the general buzz, a specific evolution – agentic AI – offers a profound, actionable pathway to not just automate, but to fundamentally rethink and intelligently orchestrate future supply chains. This involves thoughtfully integrating AI systems not merely as tools, but as true digital collaborators.
The evolving AI landscape: from automation to agency
Making a case for thoughtful AI integration means noting that AI already plays a key role in logistics.
Logistics organisations have used traditional AI for years, with machine learning algorithms acting as a reliable workhorse. It is deeply embedded in optimising routes, forecasting demand by analysing vast datasets, and automating routine warehouse tasks, forming a robust foundation for efficiency gains.
Generative AI, particularly Large Language Models (LLMs), however, have become more prominent recently.This form of AI excels at creating new content, ranging from drafting communications, generating insightful reports, and enhancing human-computer interaction through more natural language interfaces. While valuable, agentic AI introduces a new paradigm. These are not merely predictive models or content creators; agentic AI systems are proactive, goal-oriented digital agents.
They possess defined profiles (identity, objectives, constraints), maintain relevant knowledge bases, utilise memory for context, and crucially, feature reasoning and planning capabilities. This empowers them to autonomously decompose complex tasks, make inferences, develop sophisticated action plans, and interact with software systems and data sources to execute them.
They are designed as ideal digital collaborators, working synergistically alongside human experts.
The core triad: what powers agentic AI?
Agentic AI is successful when powered by three key things. The first is intelligent algorithms, or agentic systems. These engines orchestrate complex, multi-step processes. Multi-agent systems, for instance, involve specialised agents collaborating on intricate workflows, effectively mirroring the dynamic teamwork of human expert teams.
Another important factor is the use of high-quality data. This is the lifeblood of agentic AI, seeing as it is critically dependent on it. Reliable, integrated, and semantically rich data are vital for sound decisions and meaningful ecosystem interaction. Comprehensive supply chain visibility and robust data integration are the non-negotiable bedrock of intelligence.
The last factor to guarantee successful agentic AI use is to program it with the knowledge that it elevates, not replaces, the human’s role. People define strategic goals, oversee agent performance, and critically, manage novel situations beyond predefined parameters.
Effective agent design requires a “behavioural lens”: data scientists and supply chain professionals collaborate to translate nuanced human expertise, critical judgment, and adaptive decision-making logic into the AI’s operational blueprint. This transforms professionals from process executors into architects of intelligent workflows, focusing their unique ingenuity on higher-value strategic challenges and innovation.
Agentic AI in action: towards the proactive and resilient supply chain
Agentic AI promises to shift supply chains from a predominantly reactive firefighting mode to one of proactive orchestration and significantly enhanced resilience.
It can revolutionise planning and proactive responses. Traditional AI enhances forecasting, but agentic AI takes this further.
It can autonomously generate, evaluate, and dynamically adapt operational plans from these predictions. Imagine professionals using natural language for complex queries, like, “What’s our optimal strategy for the upcoming Singapore port closure, factoring in inventory, alternative routes, lead times, and contractual obligations?” agentic systems could then provide detailed, actionable recommendations or initiate pre-approved adjustments. When unforeseen disruptions strike – geopolitical turmoil, climate-driven weather, or abrupt tariff changes – a coordinated team of digital agents can act.
Similarly, it can help in transforming operational efficiency and achieving visibility. Beyond planning, agentic AI can fundamentally transform daily operations. It enables dynamic inventory optimisation across the network, reacting to live demand signals and anticipated disruptions, not just historical trends. These systems can also autonomously coordinate complex logistics, intelligently managing assets and adapting to fluctuating capacity constraints. This cohesive, intelligent action is key for achieving genuine end-to-end traceability—vital in sensitive sectors like food and pharmaceuticals—and for constructing a robust, shock-resilient supply network.
Lastly, it can elevate supplier relationships and strategic cost management. While fully autonomous AI negotiation is still nascent, current agentic AI can readily automate routine procurement, manage supplier communications, and track contract performance. This frees human procurement specialists for strategic relationship building and complex negotiations. Sustainable cost savings then result from enhanced operational efficiency, significant waste reduction (e.g., through better demand-supply matching or optimised routing), and proactive risk mitigation, rather than being a standalone, short-sighted objective.
Navigating the frontier: embracing opportunity and mitigating risk
Although agentic AI offers immense potential for adaptive, efficient, and intelligent supply chains, users must be cautious and aware of its risks.
One cannot expect an agent to produce a good output if its input is poor. The adage “garbage in, garbage out” is critical here; agent efficacy depends entirely on data quality, timeliness, and integrity.
Similarly, agentic AI can face agent-specific challenges. These include:
“Hallucinations”: Poorly designed generative components can produce plausible but flawed outputs, leading to costly decisions.
Lack of Explainability: Difficulty understanding an agent’s decision-making can hinder error correction, accountability, and trust-building – vital for SLA-governed environments.
Unforeseen Consequences: Semi-autonomous actions could yield unintended negative outcomes if agents aren’t meticulously designed, constrained, and rigorously tested.
The solution is a human-centric, pragmatic approach focused on augmented intelligence. Agentic AI should be viewed as a powerful tool to amplify human capabilities, not blindly replace them. This means robust governance, rigorous testing (akin to critical software), and clearly defined roles for human oversight and intervention.
Critical thinking, domain expertise, and the human touch remain indispensable. This is especially true when navigating unprecedented disruptions or making complex judgment calls when weighing strategic priorities and unquantifiable factors. A “reality check” is vital, focusing on clear use cases where agentic AI delivers measurable value for specific pain points like disruption management, regulatory compliance, or managing operational complexity.
Moving beyond hype to actionable intelligence
The conversation around artificial intelligence is often saturated with futuristic promises, yet agentic AI offers a clear path to tangible, present-day improvements within your supply chain. This isn’t about a distant technological horizon; it’s about deploying “digital collaborators” now to address persistent operational friction.
Consider the immediate impact of agentic AI in coordinating swift responses to volatile demand surges across your multi-enterprise network, or its power to sift through millions of daily transactions to pinpoint that tiny fraction of critical shipments or processes that truly demand human insight, thereby unlocking unique competitive advantages. These are not abstract concepts but concrete operational advantages.
For supply chain leaders, the imperative is clear: move beyond observing the AI trend and begin a pragmatic exploration. Identify specific pain points where intelligent automation and collaborative AI can yield measurable results by focusing human talent where it’s most valuable.
The future of the supply chain hinges on this intelligent augmentation – a dynamic partnership where human expertise is amplified by sophisticated agentive systems. This synergy is the key to navigating an ever-shifting global landscape, not with more buzzwords, but with enhanced operational control, resilience, and a distinct competitive edge.
Jon White, Chief Commercial Officer, EMEA at InXpress, looks at the dual roles of humans and AI in the future of the supply chain.
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AI and automation aren’t here to replace humans entirely. It is an important tool for businesses to incorporate into their strategies to remain competitive, but it is still crucial to preserve a human touch.
One of the most important aspects of the new era of automation in logistics is how it is helping to mitigate supply chain disruptions and improve resilience, problems that have existed in the courier industry for years. Companies can utilise automation to make more informed decisions, improving overall efficiency.
The power of automation and human fusion
Modern supply chains are complex, with supply disruptions and ever evolving customer expectations. By fusing automation and a human touch, it can best utilise the strengths of both, creating a harmonious collaboration. Rather than viewing AI as a replacement for humans, it can be used to approach challenges as complementary partners.
AI has a role in supply chain management. This is especially the in areas of demand forecasting. Here, advanced technologies analyse historical data and market trends to improve the demand accuracy. It is also vital for inventory management. In these cases, AI algorithms can dynamically balance inventory across locations to minimise stockouts and overstocks. By incorporating AI technology into these areas of the supply chain, it can transform supply chain management, optimising at scale.
However, human judgment remains critical. AI may be powerful, but incorporating a human touch is crucial for effective strategic decision-making and ethical oversight. Humans provide contextual understanding with a long-term vision, inputting a strategy that AI can’t replicate to the same level.
In crisis management, human adaptability is also so important. Unprecedented situations that require a human to reply and respond to customers need to be empathetic and understanding, helping customers feel heard and seen, as well as mapping out a response strategy that can’t be replicated by automation.
Combining the two and integrating them into business strategies can help processes become efficient and seamless.
Leadership in the era of AI
Leadership remains critical as AI technologies become integrated into logistics and planning. A strong leadership team can determine the correct steps to take in an evolving and competitive environment, along with the right level of emotional intelligence.
Leaders must be able to lead people through disruption. Whereas AI can tackle the problem, leaders must communicate clearly with their teams and empower and reassure them.
As technology becomes more advanced and is implemented into business strategies, leaders must understand their teams’ varying levels of comfort with new technologies. By having nuanced empathy for each member, leadership can acknowledge how jobs are shifting and help the team approach automation with enthusiasm and excitement.
Automation should be designed to help speed up jobs, not replace them. Therefore, having skills of emotional intelligence cannot be replaced by AI. It is a critical skill in an increasingly AI-driven world.
Ethical and cultural considerations
AI systems can directly influence decision-making, customer experiences, setting standards, and the trust of the public. Therefore, having ethical and cultural considerations with the use of AI is important.
AI bias can occur when the algorithm produces results that are systematically prejudiced by assumptions in the machine learning process. It can have severe business implications if not addressed or rectified. These can include reputational risk or being unable to meet compliance and regulation standards. AI is not advanced enough to overcome these hurdles by itself.
We still have an ethical responsibility in the ways that we use AI, hoping to benefit the working environment and avoid any type of harm. It can have implications such as governance, long term viability, and social impact.
By having a strong team, the human touch goes a long way to combat these issues that can occur. Fostering cross-functional teams that are well-trained with automation and regularly auditing and testing AI algorithms being implemented in business strategies can prevent this from becoming a problem in supply chain management.
As AI and automation become integral to modern business strategies and supply chain management, it is clear that it is not a replacement for human intelligence.
Only the human touch can deliver empathy and leadership, a role that remains paramount in logistics leaders. Automation has proven its value by enhancing supply chain resilience, but it’s the fusion of automation and human touch that creates an adaptive and forward-thinking business.
The newly-launched Kinaxis Tariff Response promises to help companies simulate tariff exposure, run strategic scenarios, and make data-informed decisions quickly using AI.
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The (new) new normal
The norms that defined global trade in the postwar era have been functionally abolished. What took 80 years to take shape has been dismantled in less than 80 days as the Trump administration continues to levy tariffs against foreign imports, accelerating a protectionist trend that threatens to disrupt supply chains in the US and beyond.
Pierre-Olivier Gourinchas, Economic Counsellor and Director of Research at theInternational Monetary Foundation (IMF) wrote this week that the “epistemic uncertainty and policy unpredictability” resulting from the new tariff-defined landscape was “a major driver” of the an increasingly bleak economic outlook. “If sustained, this abrupt increase in tariffs and attendant uncertainty will significantly slow global growth,” he added.
Throughout the global supply chain, organisations are looking for ways to tackle these challenges, and solutions providers are already stepping up with new offerings.
“Global supply chains aren’t operating by the old rules anymore,” Fabienne Cetre, EVP EMEA at Kinaxis said on Wednesday. “Tariffs are hitting faster, with broader consequences, and our data shows just how disruptive they’ve become. When trade policies shift overnight, companies need more than spreadsheets.”
Kinaxis Tariff Response
Kinaxis, the leader in real-time supply chain orchestration, has launched a new offering on the company’s AI Maestro platform. The solution, Kinaxis Tariff Response, uses artificial intelligence (AI) to help companies simulate tariff exposure, run strategic scenarios, and make data-informed decisions quickly.
Kinaxis explains that, as ongoing tariff pressures and trade uncertainty continue to reshape global supply chains, Kinaxis Tariff Response is helping meet the rising demand for scenario planning.The service gives planners access to tariff modelling without the cost or complexity of building it internally – providing a faster and more accessible way for companies to shift from reactive firefighting to proactive orchestration.
Many Kinaxis customers already reportedly use Maestro’s scenario planning to stay ahead of disruptions in an increasingly unpredictable supply chain landscape. During the last 12 months, usage spiked significantly around key tariff discussions. Kinaxis reported a 124% scenario usage spike after the June 2024 presidential debate that first mentioned tariffs, alongside a 112% increase following the January 2025 White House tariff memo.
As AI tools get more sophisticated, companies are increasingly turning to simulation to cultivate the visibility they need to evaluate risks and respond faster to disruption.
AI powered visibility
Built on Kinaxis’ AI-powered Maestro platform, customers can spin up the new tariff response platform in as few as 21 days, giving planners access to tariff modeling without the cost or complexity of building it internally.
While Kinaxis’ Maestro platform has had an AI-powered “what-if scenario planning” feature for a while, the new Kinaxis Tariff Response builds on that foundation with a focused solution for trade disruption. The tool combines tariff-specific inputs, sourcing logic, pricing levers, and demand modeling so companies can assess margin risk, test strategies, and evaluate trade-offs in seconds, not days or weeks.
“With Kinaxis Tariff Response, they get visibility into cost, demand, and sourcing implications in real time, giving them the confidence to act with speed and precision,” Cetre added.
Andy Coussins, Executive Vice President at Epicor, explores the impact of AI on the process of supply chain management.
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Essential industries like manufacturing, distribution, and building supplies have long relied on technology to navigate supply chain disruptions, rising costs, and labour shortages.
In recent years, cloud computing and Internet of Things (IoT) have become vital tools for streamlining operations and building resilience in the face of supply chain uncertainty.
Now, with the development and advancement of the possibilities of AI, we’re seeing an even bigger impact of technology on supply chains. Traditional AI has proven its value by automating processes, analysing data and providing useful insights — helping businesses streamline operations and reduce inefficiencies.
And with the rise of agentic AI, businesses can go a step further — and move beyond reactive crisis management towards AI driven predictive intelligence. The focus is no longer just on adapting to supply chain issues when they arise, but on the ability to anticipate and prevent disruptions before they occur.
The rise of predictive intelligence
Predictive intelligence relies on advanced AI capabilities, such as machine learning (ML) and agentic AI, to analyse vast amounts of data in real time. These technologies go beyond traditional AI systems by enabling more adaptive and autonomous decision making.
One of the most significant advantages of predictive intelligence is its ability to identify potential disruptions before they happen. By looking at historical data, market trends and external factors, AI can pick up on risks ahead of time like supplier delays, inventory shortages or demand fluctuations. This allows businesses to take preemptive action — whether that means changing production schedules, finding new suppliers, or reallocating their resources to prevent bottlenecks.
The role of agentic AI in supply chain optimisation
Unlike traditional AI, agentic AI can act autonomously within defined parameters, executing complex tasks without requiring constant human input.
One example of this in action is the automation of supplier communications and decision making, where AI can handle tasks such as sending requests for quotes (RFQs), parsing responses to compare pricing and delivery times, and helping to select the best option — all without manual intervention. This not only streamlines procurement but also minimises delays – optimising the supply chain.
Agentic AI is particularly effective in specialised domains like manufacturing and logistics, where efficiency and precision are key. By operating within defined boundaries — guided by ethical standards, policy constraints, and human oversight, it means that businesses can optimise operations without sacrificing control.
A practical approach to AI adoption
For businesses considering agentic AI, taking a strategic and measured approach is essential. This starts with looking at existing data structures to make sure they align with the capabilities of an AI system. Then, working with trusted digital transformation experts, such as enterprise resource planning (ERP) specialists, can help streamline AI powered integrations while dealing with concerns around cybersecurity and adaptability.
Working with such suppliers means software solutions deliver context based intelligence through an ecosystem of industry focused platforms, cloud technologies, and people centric AI capabilities – cognitive ERP. Gone are the days of transactional ERP and ahead lies a world of automated and increasingly cognitive business solutions to build a truly connected, efficient and resilient enterprise.
Research shows that nearly two thirds (63%) of high growth companies have embedded AI into their ERP and supply chain management systems, while 58% of organisations have already integrated generative AI into their digital supply chain operations. Don’t get left behind.
The future of AI in supply chains
As businesses continue to embrace AI, the focus will shift from reactive resilience to predictive intelligence — not just withstanding disruptions, but anticipating and preventing them.
Using agentic AI and predictive analytics, companies can transform their supply chains into agile, proactive ecosystems that drive long term growth and innovation.
The path toward predictive intelligence requires collaboration, investment, and a commitment to continuous improvement. But for those willing to take the leap, the rewards are game changing — a supply chain that is not just resilient, but intelligent, cognitive, agile, and future proof.
David Kelly, Executive VP, Global Professional Services at Kinaxis and Rozena Dendy, Global Sales and Operations Planning Manager at ExxonMobil, on the two companies’ business relationship amidst a transformative supply chain landscape.
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A successful partnership thrives on mutual benefit, and Kinaxis and ExxonMobil exemplify this well.
With over 140 years of industry experience under its belt, ExxonMobil is renowned as one of the largest energy companies globally, while Kinaxis brings its market-leading supply chain expertise and digital innovation to the party.
In October 2024, Kinaxis announced a co-development deal with ExxonMobil to create supply chain technology solutions designed specifically for the energy sector. Empowered by the growing demand for energy products that support modern life, the companies are working together to identify supply chain challenges unique to the energy sector and create a potential industry solution to mitigate them.
Kinaxis and ExxonMobil: Inside partnership
Now, Kinaxis and ExxonMobil focus on a supply and demand planning solution for the complex fuel commodities market which has no industry-wide standard and relies heavily on spreadsheets and other manual methods.
The solution enables integrated refinery-to-customer planning with timely data for the most accurate supply/demand planning, balancing and signaling. Some of the benefits include automated data visibility, improved inventory management and terminal replenishment, and enhanced supply scenario planning that are expected to enable arbitrage opportunities and decrease supply costs.
Today, ExxonMobil has centralised its supply chain function across the enterprise. Rozena Dendy, Global Sales and Operations Planning Manager at ExxonMobil, explains that in the past few years, her organisation has made a significant amount of effort to transform businesses and how it views its centralised offering.
“We’re organised with three value chains, so that’s the upstream where we take crude oil out of the ground, product solutions where we have fuels and products we use every day, as well as having our low carbon solutions which are all part of our ambition to net zero,” she explains. “With those three value chains, they provide scale and as well as how we maximise competitive advantage. Where we come into play is our centralised organisation and we are organised to make sure we have those capabilities deployed across those value chains so that we can deliver more value. Ultimately, our supply chain organisation stood up in the last two years to be able to scale and exemplify supply chain excellence and provide additional value to our bottom line.”
Competitive advantage
David Kelly, Executive VP, Global Professional Services at Kinaxis, believes that one of the key differentiators that makes ExxonMobil’s approach unique lies within the freshness of the supply chain team. “A lot of companies we are involved with already have a global team in place. But with ExxonMobil, there were so many different product lines that they were running with their supply chain operations that they decided to bring it all under one umbrella,” he explains.
“We’re working very closely with them to be innovative in coming up with capabilities, mainly in the upstream and in the fuels area to create solutions for the industry that will drive greater value and efficiency across the board. That’s a key differentiator from what we see with many of our other customers on a large-scale basis. Other companies typically had Chief Supply Chain Officers in place for many, many years. This is a little different, it’s very exciting and innovative, especially to be working with a company that has been around for 140 years too. We’re breaking new ground with such an established company in the world.”
David Kelly, Executive VP, Global Professional Services at Kinaxis
ExxonMobil partnership
As ExxonMobil is one of the world’s largest global oil and gas companies and sells multiple products, harnessing agility and efficiency into operations is essential. To achieve this, Dendy explains that supply chain orchestration is a key enabler. “What is nice is how we’re truly organised with having both capabilities and the execution teams all under one umbrella,” she affirms.
“With that, we are organised to have supply chain end-to-end planning, which I actually own. We have logistics excellence, we have materials management, and we have the digital network and advanced analytics, which we call our DNA as far as how we’re applying that across the entire corporation. What’s unique is we’re under one supply chain president who reports to our management committee. Ultimately what we are doing is how we are not only just managing but truly transforming and harmonising the processes and the technology across the entire corporate enterprise. There are spaces where we’re innovating, there are also spaces in which we’re actually deploying. We’re pretty excited and we are also on our transformation journey with upstream as well.”
Change management
Many companies struggle to fully scale supply chain solutions. Dendy believes there are three key factors that are helping ExxonMobil to successfully implement these technologies at scale. “For us, it starts with three things,” she says. “You have to have alignment at the actual leadership level and we have alignment all the way through our management committee to make sure we are focused on delivering the best from the capabilities that the supply chain actually has. Then with the alignment, it also goes into the business line and making sure they are adopting it.
“The second thing is ensuring there is strong change management through your organisation with the changes that you’re trying to adopt. Then it is about how you focus on user adoption. It’s not just about deploying the magic cutting-edge tool of the day, but actually deploying tools that are solving a business problem and making sure that we’re maximising the effort so that we not only demonstrate supply chain excellence but also get the value out of the tool and enhance the user experience as well.”
Kelly adds that one of the special parts of working with ExxonMobil in the upstream and midstream area is that Kinaxis is not replacing existing technologies but instead phone calls and spreadsheets. “What’s interesting about that is that change management and user adoption is even harder than replacing their technology because people are so accustomed to calling someone they know personally to get something done,” discusses Kelly. “This has been one of the biggest drivers for us.”
Technology transformation
Kinaxis Maestro is the only AI-infused end-to-end supply chain orchestration platform for fast, intelligent decision-making. Fusing together multiple proprietary analytical technologies and techniques, Maestro empowers customers to find the right answer at the right time and speed for businesses. This allows for agility and efficiency despite the situation. Maestro infused AI across supply chains in an approachable way to allow for smarter decision-making, faster and at a lower total cost. Kelly explains that while AI is one of the biggest buzzwords in the industry today, it is important to collaborate with companies on how to correctly use the data.
“It’s about figuring out how can we use AI capabilities to make decisions more efficiently and even potentially remove the human element from making a decision,” he explains. “From a supply chain orchestration perspective with ExxonMobil, it’s important that we get the orchestration right first and then we can get a better understanding of where the capabilities are going long-term. AI requires data, so you have to have lots of data for AI to work effectively. It’s not just data within the four walls of ExxonMobil, but external data as well. It could be weather signals, transportation signals or any number of elements like that. That has to be locked in too to make the AI capabilities highly effective.”
Rozena Dendy, Global Sales and Operations Planning Manager at ExxonMobil
Navigating AI’s challenge
For Dendy, the key element to leveraging AI properly is ensuring it isn’t used for the sake of it. Getting people on board to adopt new systems and ways of working is an essential part of any change management journey and is an area that Dendy does not underestimate. “We are working across the enterprise on our AI, not just having our foundation in place, but making sure that we’re truly using it to solve an actual problem,” she discusses. “It’s about finding out what problem are you trying to solve, how you are extracting value, and making sure that you have the data, people and process in place. Enhancing and elevating what humans are doing is important.”
However, despite technology’s draws sometimes the workforce is committed to falling back on familiar legacy systems and processes. But the way to combat this, as Dendy explains, is fostering a process ‘designed to win’ which is the secret sauce to success in any technology transformation journey. “Your culture has to be one about winning or competing to actually win,” she affirms. “It’s not just about winning on its own, it’s about how you win with an actual standard. It’s critically important, you’ve got a process that’s designed to win. Getting the hearts and minds on board is vital because it’s about getting the most out of new tools, changing the way people work to extract the most value and bringing users along that process too.”
Managing the value of AI
Kelly adds that one of the biggest misconceptions surrounding advanced technologies is believing that AI is a magic wand that will hold all the answers. Kelly stresses that organisations should adopt a more strategic and thoughtful approach to leveraging AI for the best results.
“A lot of people want to deploy AI for AI’s sake,” he reveals. “Sometimes they believe it’s going to do so many great things for them, but what they need to understand is you need the specific data signals and data in place normalised to be able to leverage the capabilities that AI has to offer. We are working with a number of companies today, particularly retail or consumer packaged goods who are suppliers to retail, and getting their data signals so they can drive greater forecast accuracy. We’ll be doing the same with ExxonMobil and we will be working with them in the same capacity in AI. But to get that right, you’ve got to have that data and those proper signals in place to be able to have the AI models work effectively.”
With an eye on the future, Kelly has several focus areas on the agenda about how to drive profitability for his organisation, ExxonMobil and the companies it serves. “It’s about looking at how we can drive forecast efficiency, reduce forecast volumes and increase bottom line profitability for the likes of ExxonMobil and our customers,” says Kelly. “While efficiency is good, what most companies and shareholders care about is maximising the profitability of the overall organisation. It’s about how we can focus on that for our customers and drive that efficiency which will be key in the industry moving forward.”
Kirk Knauff, President and Chief Executive Officer at Kaleris, discusses his company’s journey to driving advanced optimisation across the supply chain.
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In today’s fast-paced supply chain landscape, even the slightest delay can become costly bottlenecks, inefficiencies and missed commitments.
Enter Kaleris.
The company’s cutting-edge software allows customers to take control. They streamline critical workflows and harness real-time data to allow for smarter, faster decisions to be made with confidence and keep operations moving forward. And Kaleris can back it up too – the company works with more than 650 organisations in over 80 countries.
Advanced optimisation technology
Kirk Knauff is the President and Chief Executive Officer at Kaleris. Knauff explains that his company’s customers place a high value on software for mission-critical operations. “AI, machine learning, GenAI are part of the next frontier in every industry, but not on their own,” he says.
“What we’ve seen in terms of what our customers ask – driven by what their customers are asking of them – is, ‘What can you do to help us make our operations more efficient, reliable and safer?’ We help our customers execute better through advanced optimisation, which includes components of AI and machine learning, so they can see where bottlenecks and disruptions occur. Tools like AI help them make sense of all the operations data and make informed decisions about how to best use their network and assets. We are always looking for use cases to serve our customers better, even internally with our own operations, so we become more efficient, which allows us to invest more in our customers’ applications.”
Headquartered in Alpharetta, Georgia, Kaleris is a leading provider of supply chain execution technology. Many of the world’s largest brands rely on Kaleris to provide mission-critical technology for yard management, transportation management, maintenance and repair operations, terminal operating systems, and ocean carrier and vessel solutions. By consolidating supply chain execution software assets across major nodes and modes, Kaleris addresses the dark spots and data gaps that cause friction and inefficiency in the global supply chain.
Kirk Knauff, President and Chief Executive Officer at Kaleris
Key considerations of new technologies
In addition to being the world’s largest provider of terminal operating systems, Kaleris has been recognised as a global leader in yard management solutions for more than 20 years. Kaleris YMS offers a broad range of solutions that are trusted by leading brands and offer unique capabilities for real-time location systems, automated gate check-in, task automation, and more. Customers are at the forefront of decision-making within Kaleris, with Knauff noting the key is to ensure any new processes are carefully integrated into successful workflows, instead of starting from scratch.
“GenAI or large language models are not a magic button we can press and suddenly all of the industry’s technical challenges are over,” he says. “When employed by companies with our expertise, it can be used to innovate faster. The software and technology in place today are truly mission-critical. It’s about building around what’s working versus replacing for the sake of new trends. We’re excited because we see huge potential ahead for advanced optimisation and how new elements like AI enable it.”
Data challenge
One of the most important aspects to achieve sustained success within the supply chain of 2025 is gathering quality data and managing it properly. Today, how companies collect their data and what they do with that information can ultimately make or break them. Knauff believes advanced technology tools are helping to connect a supply chain landscape full of bespoke single-point solutions.
“Nodes on the supply chain and different ways of moving things from point A to point B are part of the legacy of the industry,” he says. “Consider all the different players in the value chain—when something moves from point A to point B, numerous parties play a role in the process. From the very physical nature of what happens from moving things around to who provides technical solutions, this is where bespoke single-point solutions have come in to try and fix the handover challenges.
“However, everyone is looking at it and saying, ‘We have all these disconnected points across the supply chain, why can’t we have data that’s more integrated and collaborative across the supply chain?’ It’s a big challenge of our time, and there’s a lot of legacy to navigate. We have a lot of providers of technical solutions and not everyone is open to the idea of sharing workflow data and creating interoperable systems.”
Global positioning
Kaleris is quite the powerhouse. Today, it stands among the largest providers of multimodal solutions for transportation, with more than 50% of the world’s cargo managed by Kaleris solutions. According to Knauff, it acts as something of a competitive advantage for the organisation and sets it apart from competitors. “Our scale and footprint are helpful for us,” says Knauff. “What makes us unique is our ability to collaborate with our broad customer base and understand what their challenges are as a group. There’s no other company in the world that has the install base of customers that we have and can innovate with.”
With the AI revolution in full force, the importance of companies learning as quickly as possible what works and what doesn’t is essential to get ahead of the competition. As far as Knauff and Kaleris are concerned though, there is a lot to be excited about. “The inherent challenges in terms of the legacy problems to solve are a big hole to dig out of, and that means opportunities for us and our customers to do even better,” he reveals. “One of my favourite things about this industry is the physical nature of the problems that you’re trying to solve. Until someone tells me otherwise, you still can’t snap your fingers and move something from point A to point B. There are always going to be challenges across the supply chain, and that means more areas for us to help. I am very excited about the future.”
Oana Jinga, Co-Founder and Chief Commercial and Product Officer at Dexory, discusses how owning the world’s tallest autonomous robot sets her organisation apart from others in today’s dynamic and competitive supply chain space.
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Possessing the world’s tallest autonomous robot is quite the accolade.
Standing at a towering 46 feet tall and weighing 1,500 pounds, Dexory’s robot is designed to operate seamlessly across warehouse environments. The robot is equipped with state-of-the-art sensors, including high-definition cameras, temperature gauges and humidity monitors which autonomously navigates vast warehouse spaces while scanning more than 100,000 pallets every 24 hours. This efficiency doesn’t just enhance operational speed but also allows for meticulous inventory management.
Indeed, Dexory is on a mission to uncover intelligence via technology that empowers businesses to optimise, predict and grow. The company is revolutionising the warehousing and logistics industry through AI-driven automation and advanced robotics, delivering real-time data intelligence that elevates operational efficiency. Dexory’s digital twin technology is the only platform for autonomous robots that continuously delivers data and insights on warehouse operations in real-time. The company’s robots and data visualisation platform work together to measure, track and locate goods across their supply chain journey within the warehouse.
Oana Jinga, Co-Founder at Dexory
Dexory’s secret sauce
At the heart of Dexory’s journey are the company’s three founders; Andrei Danescu, Adrian Negoita and Oana Jinga. The trio moved to the UK more than a decade ago and worked in several different jobs while living together in a house share. Jinga began her technology career at O2 before spending six years at Google, managing strategic partnerships across EMEA, and being part of the team that launched the first Google Pixel phone. She explains that from her company’s perspective, the company always had the idea of using robotics to do more than the traditional use cases of picking and moving things around warehouses. This mindset has been taken one step further by introducing the record-breaking robot.
“We realised that if we equip them with the right sensors and cameras, then we can capture ridiculous amounts of information on a continuous basis,” Jinga tells us. “This is real-time data from inside warehouses, which was previously unheard of, you would likely need over 10,000 cameras across the entire warehouse to get the same amount of data that we do with one robot.
“The big advantage is that we offer our customers the possibility to know at any point in time exactly what they have and where it is. By being able to scan as fast as we can and capture as much data as we can every single day, then that allows our customers to know in real-time exactly what they have and where. This is instead of manual processes of other technologies which take weeks and months to get that level of data. We do that every single day, which has changed the game for our customers and how they can use that data to operate in real-time.”
Data management
Upon launching the new technology almost two years ago, Dexory’s customers were not prepared for the plethora of data the robot provided. Jinga explains that it took a few months to get used to the vast amount of information that customers now had at their fingertips and efficiency rose significantly. “Their picking became much more efficient and they are utilising the space much better. One of the biggest improvements we were told about was that there were much fewer issues with orders leaving the warehouse,” she says. “We have customers that reduced errors leaving the door from about 50 or 100 errors a week to zero because the correct stock is in the right location. Until you see that data and you start utilising it on site, you likely don’t even realise what you can do with it because it’s never been done before.”
Indeed, the supply chain space is in the midst of a digital transformation filled with exciting and dynamic innovations. While Jinga was speaking to SupplyChain Strategy at Manifest Vegas, Dexory’s robot was in full flow and drew lots of attention to the company’s stand which was located towards the front of the expo hall. Another new advanced technology offering that has captured interest has been the acceleration of generative AI and the potential that large language models offer. “I think we haven’t even scratched the surface of what GenAI can do, especially in the enterprise environment,” she says.
Advanced technologies
“ChatGPT and Google’s Gemini are one thing but being able to make enterprises more efficient and help them be much more proactive rather than reactive to their environments hasn’t even started yet. The sheer amount of data and information that we track every single day is around one million data points from every warehouse. This helps our modules become much better, helps machine learning improve and identifies what we’re looking at. It also gives us the opportunity to build our own language models.
“In order to be able to do that you need this amount of data and information to pile up because it doesn’t currently exist to be able to train the models. The more data you capture then the better it becomes which is why it needs to take a while for that to amount. For example, with ChatGPT, language is something that everyone uses and the amount of information out there is ridiculous, but data from inside warehouses doesn’t exist yet. It’s building up and we are very fortunate to be one of the few out there that has the capacity to capture so much information and then filter it through our models and bring value to the customer at the end.”
Sustainability drive
When it comes to sustainability, no one can go it alone. It is no longer just about what any singular company does, much of it revolves around how green their supply chains are too. Close collaboration is at the heart of making sustainability stick in supply chain and logistics.
“We all have to work together to make it happen because we can do our part but if the next supplier down the line picking up the data from ours doesn’t do it in the right way, then it doesn’t mean anything,” Jinga affirms. “You need to follow it through. I believe we’ve developed a few features for our customers around sustainability that they requested us to help them with. It’s about giving them visibility on the stock that might become waste and flagging it in the correct way with the right team so they can act on it at the appropriate time. It is important to keep our suppliers accountable because we are part of a wider chain of events that needs to happen.”
Meeting global goals
With an eye on keeping aligned with the United Nations 2030 Sustainable Development Goals, the importance of balancing cost and sustainability is an important factor for most companies and their supply chains. For Jinga, she insists there are two key sides to the story.
“Firstly, it’s about how we are internally tackling it and about our sustainable supply chain,” she tells us. “We work a lot with our own suppliers to make sure that whatever we put in the robots, how we utilise the robot and recycle the robots is done properly. But the biggest impact we have is with our customers. Going back to the fact that we have all this data, it means we can show them where the leaks are when it comes to their stock.
“We keep track of their goods that might be going out of date or they might be wasting around on the shelves. Being able to reduce that waste in the warehouse is very, very important for our customers. Because we have the capacity to scan the sites every single day, multiple times a day, it highlights things exactly as they happen and it allows them to then pick that pallet, get it out in the system and send it to the stores instead of leaving it there to become waste. It’s about the impact we can have on our customers.”
Future focused
The future of Dexory looks promising. In October 2024, Dexory announced it had successfully closed a $80 million Series B funding round, following a $19 million Series A funding round the year before. Over the past few years, the team has grown from 15 members of staff to 80 employees which demonstrates the company’s drive to scale. Led by Jinga and her two co-founders, Dexory is set to continue to grow, evolve and sustain its impact on the world of supply chain and logistics and beyond.
“The pace of change and technology coming into the sector is absolutely insane,” she discusses. “We started working in logistics just after the pandemic in late 2020. Seeing how things have changed over those past four years is making me extremely excited about what’s coming ahead. Robotics is finally becoming mainstream, and people are not afraid to adopt technology anymore and to understand the benefits of a full return of investment in automation. Then you have all the additional technologies like scanners and sensors and all of those becoming much better and cheaper which then makes our technology easier to implement with customers too. I’m very excited about the years to come.”
Paul Heitlinger, Venture General Manager, and Lisa Mulholland, Vice President of Sales at Sientis, discuss how their organisation is transforming inventory management in supply chain.
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Complete visibility is the key ingredient to success in today’s supply chain.
It is the reason why autonomous drones are becoming increasingly popular in warehouses. Drones allow warehouses to automate inventory counting seven to 10 times or even faster with higher accuracy and increased efficiency than manual counting.
Sientis links computer vision-based localisation, barcode scanning, full autonomy and multi-drone orchestration technology in one seamless warehouse management service. The company’s customers can benefit from detailed, up-to-date inventory analytics that reduces low-value manual labour and transforms productivity and efficiency. Overall, Sientis helps its customers improve overall efficiency with a minimum 40% return on investment over a three-year period.
Inside Sientis
Having originally been part of Nokia Bell Labs and also formerly named Nokia AIMS, the founding of Sientis began by looking at vertical farming and how to automate the analytics of plant health. This work then expanded into the warehouse space and eventually saw Sientis transition into its own autonomous business group.
“We are an internal startup that is being incubated by Nokia,” Paul Heitlinger, Venture General Manager, tells us. “Now, we are focused on providing the best possible solution for the warehouse industry for cycle counting by using our in-house developed autonomy stack for the drone. We do our own analytics and interpret the data. We are essentially a full-stack organisation from the image capture, the drone autonomy, the analytics and the UI – we do it ourselves with a really small team that is both very agile and smart, so we are able to develop these solutions quickly and efficiently.”
Heiltinger adds that his company builds its own products to best meet customer needs. “We’re always advancing, researching and moving the product forward and building the best possible solution for cycle counting,” he adds. “We are part of Nokia, so they are invested in this business. They believe that this is a growth business for the company.”
Lisa Mulholland was recently appointed Vice President of Sales at Sientis. She explains the company’s past few years have been filled with rapid growth and transformation fuelled by advanced technology. “With the tools that have been provided, the technologies have significantly improved analytics, automation, decision-making and are enabling businesses to optimise operations,” she reveals. “With these improvements, our Autonomous Inventory Monitoring Service (AIMS) division is transforming the space.”
Power of data
Data is a big piece of the puzzle for Sientis and its people. According to Heitlinger, one of the biggest advantages of leveraging new, advanced digital tools is the visibility over what customers want to see and what they actually need. “I think one of the powerful things about natural language is that we don’t have to predict what customers want to see,” he explains. “We will have models that are trained on specific kinds of data and they can use natural language queries to find the data they are looking for. It will really open up the reporting to what a customer wants to see.”
As a result, customers will have access to a powerful tool that can mean unprecedented access to Sientis’ data. Heitlinger explains that as long as the information his organisation provides is useful and can be interpreted from LLMs then it doesn’t matter how customers utilise the data.
“The other part is that we want to ensure that customers can access their data quickly too,” he adds. “One of the things that we are working on is digital twins, and we are doing this in conjunction with Bell Labs as well. How do we get customers an overview of their warehouse, where at a glance they can see all the missing inventory? How do we ensure that inventory analysis is provided as quickly as possible to customers so they can come in and find that missing inventory quickly? We are implementing digital twin solutions and natural language queries to ensure that customers get access to the data and how they want it in a really quick and efficient way. It’s not just a simple solution, it becomes a much more powerful solution because the customer decides how they want to see their data.”
Navigating disruptions
Given the nature of the complex world the supply chain faces today, things don’t always go to plan. Over the past half-decade or so, the world has encountered a series of ‘black swan’ events that have caused significant problems to companies and their supply chains. Geopolitical issues such as COVID-19, elections, wars, inflation and more have all had their own effect on global supply chains in one way or another and those that have overcome such challenges have done so by being agile, flexible and ready to respond quickly. Helping Sientis to do that has been through leveraging data analytics.
“The best warehouse operators are the ones that are going to manage their accuracy, their customer service, being able to ship on time and not lose inventory,” explains Heitlinger. “It’s important to let workers, who are a scarce commodity, do the higher value things like picking, shipping and packing, while letting Sientis do the work that no one else wants to do that is only done because of inaccuracies that humans cause. We’ll do it much more accurately, much faster and allow our customers to become the best warehouse operators amongst their peers.”
Mulholland adds that the importance of transitioning from a reactive to a proactive approach cannot be understated and she is already witnessing the seismic shift underway within the industry and beyond. “We’re starting to see the signs of the true value that these technologies hold and the full potential is still unfolding,” she tells us. “Many organisations are in the process of integrating these AI-powered solutions. Like Paul said, it reduces human error, cuts costs and enables data-driven decisions. As adoption increases, we’ll continue to see greater efficiencies, lower operational costs and enhanced supply chain resiliency powered by this technology.”
Setting boundaries
Over the past few years, GenAI and the potential it brings has become the name on most supply chain executives’ lips. This is partly a result of the rise of OpenAI’s ChatGPT model which has accelerated the topic of large language models and brought it to the forefront of conversations. However, one of the biggest concerns with chatbots is the possibility of hallucinations and how answers that aren’t true could be presented as fact. Fortunately, Sientis hopes to one day have an answer for that. The organisation is training its model on customer data and its technology is learning structured data.
“It’s not something that lends itself to hallucination,” says Heitlinger. “By the time we release it into production, it’s been thoroughly tested and trained. We beta-tested with customers first so nothing’s going out to production that we’re not completely happy with. It would be really bad if we released it and a customer said, ‘Tell me what my most lost product is’ and it was totally wrong. But it’s not dealing with complicated data either so there’s not loads of opportunities for these models to go wrong from my perspective.”
For Mulholland, one of the biggest considerations when introducing new ways of operating is determining what the practical value is. “It is important to have clear business objectives and align them with specific goals like cost reduction, efficiency, real-time visibility,” she explains. “One of the things that myself and my team pride ourselves on is getting to know our customers, the ins and outs of their business, and how our solution is tailored to their direct needs.”
The future
Looking ahead, Heitlinger believes the future of Sientis could go in several different directions. “We have drone autonomy, so there are always new opportunities that we can use our platform for,” he tells us. “The drone ultimately captures the data on the shelf at a customer site and the other half of this is around how we interpret that data and how we present it to the customer. There’s a lot of opportunity in the future.
“For our immediate future, we are going to continue to enhance the service. We really want to make the data as useful as possible for our customers. We are very agile, so we’re always built to what our customers want. One of the things that also differentiates us is that we look at all our customers as a partnership. We’re always trying to learn from our customers and trying to make our product better to help our customers operate their businesses better. We’re only successful if our customers are successful. It’s in our interest to listen to our customers and work with them on making our service to what they want and how they want to use it. The future is bright.”
William (Bill) Wappler, CEO and Executive Chairman at Surgere and David Russler, Senior Manager at Trane Technologies, discuss the partnership between the two companies and how Surgere’s delivery of 99.9% data accuracy acts as a competitive advantage.
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In a world with so much uncertainty, being accurate with your supply chain data is essential.
And when it comes to data accuracy, Surgere is second to none. Surgere is an industry pioneer and leverages IoT technology to revolutionise and reshape the supply chain for the world’s leading automotive, manufacturing, logistics and food and beverage companies. The company’s engineering and operations team work with its customers from day one to plan, test and deploy IoT supply chain solutions that deliver data accuracy and reliability to allow for better decision-making across the entire organisation. Via Interius, Surgere’s SaaS platform, supply chain transactions combine with enterprise tools and systems for complete visibility and accuracy to drive real-time, proactive decision-making.
William (Bill) Wappler is the CEO and Executive Chairman at Surgere. In 2004, the company was actually born at his kitchen table in North Canton, Ohio. Initially, Surgere served as a packaging consultant for major companies such as Timken, Alcoa, and Whirlpool. However, after witnessing significant failures taking place throughout supply chains, Wappler began searching for software to support his existing clients’ needs. But he couldn’t seem to identify a solution that worked. “It was then that I took a leap of faith and recreated Surgere,” he says. “We extended our supply chain expertise into software; directing our team to build highly specialised software that could provide absolute visibility throughout supply chains. This was the first critical step in ending the chaos.”
Today, Surgere is on a mission to save the supply chain. By using the Interius platform, its clients can fully identify supply chain weaknesses. Surgere built its foundation on delivering 99.9% accuracy, valuable insights, proven cost reduction and increased productivity. The company’s clients are moving far beyond identity, location, and insight into ML/AI-directed corrective action. More than 15 billion monthly transactions from IoT sensors moving between more than 2,000 client locations, are made visible 24/7, 365 days a year with Surgere’s technology.
SupplyChain Strategy chatting to William (Bill) Wappler, CEO and Executive Chairman, at Surgere and David Russler, Senior Manager at Trane Technologies
Developing partnerships
Over the past couple of years, Surgere and Trane Technologies have formed a key, strategic partnership. David Russler is the Senior Manager at Trane Technologies. With over 27 years of experience in the automation and automotive industries, Russler possesses a strong background in engineering management, having previously worked as a Product Interface Manager and an Engineering Group Manager at General Motors. Today, as part of his role within Trane Technologies, he leads the development and integration of automation solutions.
Reflecting on how the alliance was born, Russler explains that around two years ago his company decided an area of interest was around material tracking.
“We had a number of solution providers in our plants. We have roughly 40 plants around the globe and different plants had tried a range of solutions without much success to be very honest,” he reveals. “Firstly, we began a competitive analysis to try and understand what the technology actually offers today and what was important to us. Then we found that getting the reliability of the data and the solution that we implemented was the key. We went through very extensive analysis on what technologies were available, and which partners were available out in the space, and that really is a key piece of what we were looking for. We were truly looking for a partner, not just a hardware provider or a software provider.”
And so they found Surgere. With an automotive background, Russler believes long-term and mutually beneficial relationships are more common in that industry. However, he reveals the relationship Trane Technologies has built with Surgere is particularly special. “We wanted a partnership that would allow us to work together to develop solutions that were unique to our applications,” he tells us. “We’re really trying to drive that culture and foster that relationship building so that we can have established relationships, develop solutions, and then move much more quickly as we try to implement solutions within our factories.”
Having completed business with a host of multinational companies such as the likes of Caterpillar, Toyota and Honda, Surgere has seen its fair share. But Wappler is keen to outline that the Trane Technologies alliance is unique.
“Trane is unique in that their commitment by the executive team is not momentary – it lasts throughout the partnership,” he discusses. “Secondly, Trane understands the importance of what governance is all about, how to take two teams and make them into one and that increases the success of technology deployment exponentially. Technology deployments, much like ours, in supply chain, fail about 43% of the time. Think about that. You almost have a 50/50 shot on whether or not it’s actually going to work. The trouble isn’t always the technology that’s in play but in many cases it’s the partnership. As we look down the line, one of the things that we’re certain of is that this project’s going to succeed and it’s going to succeed because of David and his team.”
Russler reveals that when he looks at what Trane had out in its facilities today, the company actually had a much worse than 50/50 chance of the technology succeeding on the legacy equipment that it possessed. “One of the things that was really appealing to us about working with Surgere is a 99.9% reliability rate in ensuring that the data is being read accurately and shared appropriately to the individuals who need it to get the data and make good decisions.”
William (Bill) Wappler, CEO and Executive Chairman, at Surgere
Introducing Sophia
At Manifest Vegas 2025, Surgere introduced a new agentic AI assistant called Sophia. The technology is an intelligent supply chain companion fully integrated into Surgere’s Interius platform. The benefit of Sophia is to make supply chain professionals’ lives easier by delivering real-time analysis and action based on their unique supply chain data.
“Everything is based on accuracy and fidelity. I can’t help David and his team much if I’m not at nearly 100% accurate and that’s at all points across the supply chain,” reveals Wappler. “What built our company is accuracy. That requires a confluence of different technologies. By the time we’re finished, we will have probably deployed anywhere between five and seven different technologies that can give him that accurate data throughout his entire enterprise. That’s a very unique thing. As an example, we’re currently providing our software about 15 billion transactions a month in data relative to ‘Where’s my stuff?’ Our software ingests that. Then we provide that data to people who are running the supply chain operations they begin to synthesise, analyse and think about how to react. And that’s been traditional in the world of software forever.
“However, with 15 billion transactions, David and his team cannot possibly keep up with that kind of transaction volume, let alone synthesise, analyse, and direct their team. It’s overwhelming. So when we started looking at AI, we didn’t look at AI in a large language model to do someone’s homework. What we really needed was a digital coworker that could stand next to our clients and analyse that data for them, prioritise what they should pay attention to, and then tell them how to react. Across their supply chain, billions of transactions are being made gathered by software fed to Sophia and she is standing next to David saying, ‘Here’s what you need to think about and here’s what I would suggest that you do’. She’s a game-changer.”
According to Russler, the introduction of Sophia is a critical piece of the puzzle to ensure the right data at the right time to make the right decisions. “What’s been missing for us is not knowing where our components or finished goods were and that was what was driving waste in our systems that we needed to eliminate. Where Sophia really comes in is helping us to eliminate that waste and to help us to get to the decisions that we need to make more quickly.”
2025 Vision
Russler calls 2025 “the year of execution” for Trane Technologies. Over the past year, his team has dedicated significant time to developing standards and establishing a foundation to streamline its 40+ manufacturing facilities worldwide.
“2025 is about implementing those plans and putting those plans into action. We’ve got a number of projects that we’ve brought online in the last couple of months alone,” he says. “We have a number of other plans that we’re in the process of bringing online this year, and our challenge was to have Bill and his team try to get to as many of our facilities around the globe this year as possible so we can then begin executing those plans more efficiently into our sites. This year and the next couple of years are really going to be exciting for us because now we’re going to start reaping the rewards for all of the technologies that we are actually developing and bringing those efficiencies into our operations.”
With an eye on the future, Wappler is in no uncertain terms optimistic about what lies ahead for his company, the industry and beyond.
“The future is so interesting,” he stresses. “We are under a transformation that has never been seen by technology, much less manufacturing, and that is happening right now. I believe that AI is going to unleash power that we can only begin to imagine. Part of that will knock down the old silos that exist within our clients and it will turn away single point solutions. If you can’t exist in a solution set that embraces an entire enterprise and supports what everyone wants to do at one time, then I think that you’re a dinosaur. We’re being told that we’re just trying to understand it as a society and we are now starting to get a glimpse of what that might mean. I wish that I wasn’t just my children, I wish I was my grandchildren because they’re going to be able to see unimaginable things.
“AI is going to supplant human intervention with data and it’s going to be able to act and think for us in a way that supports this transformation in ways we’re just imagining. I think that if anything, we should all be living in a world of optimism and I’m quite excited by it. I just can’t wait because we’re just getting a glimpse, but it’s coming and it’s coming quicker than we think.”
Sreedhar Patnala, general manager at Systech, looks at the impact of AI and Machine Learning on the future of the pharmaceutical supply chain.
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The pharmaceutical sector has seen significant growth in recent years—a trend that shows no signs of slowing down. The industry is already comparable in size to the gross domestic product (GDP) of countries like Spain, Mexico, and Australia, with revenue predicted to increase by 6.12 percent annually between 2023 and 2030. This expansion brings both challenges and innovative solutions to meet industry needs.
2025
As 2025 continues, the pharmaceutical industry will likely face a familiar challenge in the form of supply chain disruptions. Pharmaceutical leaders recently highlighted significant supply chain issues as one of their biggest concerns, citing increased pressures from raw material and labour shortages, geopolitical instability and extreme weather events.
These supply chain challenges are an ever-growing threat to the industry as they not only cause shortages of medicines but can lead to an increase in counterfeiting and diversion. As such, it is more important than ever for pharmaceutical organisations to build resilient supply chains while also ensuring they are compliant with the ever-evolving regulatory landscape.
Beyond regulatory requirements, there is a gap between consumer and patient demand for greater transparency—including product origin, materials, environmental impact, and recommended usage—and the data currently provided by pharmaceutical brands and supply chain stakeholders. By fully leveraging serialisation, aggregation, track-and-trace, and authentication solutions, many of which are already in place for the EU Falsified Medicines Directive (FMD) and the US Drug Supply Chain Security Act (DSCSA) compliance, pharmaceutical manufacturers can unlock valuable data to enhance supply chain effectiveness.
Partnering with an expert with deep industry knowledge can help pharmaceutical companies harness this data to improve supply chain transparency, streamline inventory management, strengthen connections with customers and patients, and protect brand reputation. Such experts can also help integrate the latest AI-driven innovations and machine learning capabilities, further enhancing predictive analytics, automation, and real-time decision-making across the supply chain.
Rise of counterfeit goods through pharmaceutical e-commerce
Counterfeiting and diversion continue to present a major challenge within the pharmaceutical industry, a problem exacerbated by the rise of online marketplaces. The growth of e-commerce in recent years has increased accessibility and convenience for consumers, providing an easy way to obtain medicine that otherwise would have been difficult to source from local vendors. However, the loosely regulated nature of online markets poses a threat to the legitimacy and safety of pharmaceutical goods.
The number of illicit online pharmacies has significantly increased in recent years, with many of these masking as trustworthy, easily accessible options for customers. For instance, a recent Royal Pharmaceutical Society investigation found that fraudulent internet pharmacies target vulnerable patients who are experiencing medication shortages, including hormone replacement therapy (HRT), ADHD medication, and obesity medications. Prescription medicine sales on these unregistered websites are unlawful and put patients’ health at risk.
The uncertainty and danger instilled in online markets confirms the importance for pharmaceutical organisations to implement solutions that can help them combat the rising number of counterfeit and diverted products entering the pharmaceutical supply chain.
Regulatory environment: a key driver for supply chain innovation
Regulatory compliance remains a major driver of pharmaceutical supply chain innovation, including the established EU FMD and the US DSCSA. These regulations have been introduced to safeguard patients and improve the safety of the pharmaceutical supply chain and manufacturing process. Nevertheless, even with the implementation of these regulations, counterfeiting and drug diversion continue to plague the industry.
Adhering to regulations strengthens supply chain visibility for pharmaceutical and moves them closer to achieving true traceability. Enhancing the transparency of production and shipping procedures can also improve operational efficiency. In a time when the development of a strong pharmaceutical supply chain depends on traceability, authenticity and transparency, digital track-and-trace technologies are becoming the norm.
Leveraging technology to address supply chain issues
New technological developments are transforming multiple sectors. This includes the pharmaceutical industry, where technology is leading the way in helping improve supply chain resiliency in the face of disruptions.
For example, the growing usage of artificial intelligence (AI) is set to have a major impact on the pharmaceutical supply chain. One notable development is AI-powered authentication technology, which uses machine vision and machine learning to create a digital blueprint of packaging artwork features—enabling precise product identification through pattern recognition. Additionally, AI will enhance real time monitoring and secure pharma supply chains by detecting irregularities and possible risks as they occur.
Moreover, smart packaging technologies, such as Radio Frequency Identification (RFID) and Near Field Communication (NFC), are increasingly being adopted by pharmaceutical companies, for speciality drugs. Although this innovation has been present in the pharmaceutical industry since the early 2000s, it has become more affordable and accessible in recent years. These technologies, which can scan large quantities of products, boosting efficiency in warehouses and distribution centres, have become more affordable and accessible in recent years. RFID technologies, along with RFID readers, can scan large quantities of products, boosting operational efficiency in warehouses and distribution centres.
Beyond efficiency, smart packaging technologies provide access to invaluable insights that can inform future decision making. Once a company has implemented the latest technologies and solutions, it can start exchanging data and capturing end-to-end data about a product’s journey. For example, access to information like inventory levels, item status, and location can help pharmaceutical manufacturers optimise production and meet customer demand efficiently. Smart packaging technologies also enhance interconnectivity and collaboration across the value chain. By providing in depth visibility and actionable insights, these solutions align production and supply chain requirements, streamline internal processes, and boost efficiencies, ensuring a steady product flow and addressing drug shortages.
An uncertain future
The pharmaceutical industry continues to face multifaceted supply chain challenges which compromise brand integrity, threaten patient safety and reduce revenue. To address this, businesses must go beyond regulatory compliance by leveraging advanced traceability and authentication technologies to unlock the power of their data.
This approach will not only be crucial in enhancing digital connectivity and strengthening brand protection—it will also support pharmaceutical organisations in creating a more resilient supply chain to safeguard patient health.
We speak to Jonathan Horn, CEO and Co-founder at Treefera, about using AI, satellites, drones, and data analytics to create transparency in the murky world of carbon credits.
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One of the biggest issues facing the global carbon credits industry is a lack of transparency in supply chains with regard to Scope 3 emissions. Tracking the real carbon impact of an organisation’s supply chain is a challenging and murky process. As regulations in regions like the EU (the world’s biggest market for carbon credits) become stricter, organisations are turning to Artificial Intelligence (AI) as a way to improve the credibility of their carbon credits.
The carbon markets are a dirty place
Amid unrelenting reports of a worsening climate crisis, a pro-fossil fuel administration in the White House, and the increasing quietude of tech giants on the subject of their sustainability targets, it’s hard to feel positively about the fact the global carbon trading market is worth about close to a trillion dollars per year.
In cold, hard figures, the total value of traded global markets for carbon dioxide (CO2) permits reached an all time high of $948.75 billion in 2023. Selling sustainability gains for profit to companies looking to absolve themselves for irreparable environmental harm is big, big business. So were indulgences in the 13th century.
The case for carbon credits is that they provide a stepping stone for companies to balance their emissions chequebooks. A large manufacturer, for example, might invest billions in reducing its carbon footprint, but at the end of the day, it requires metal dug from the earth and power from the grid to operate. Discussions with carbon market advocates often revolve around using them to bridge the last few percent of an organisation’s emissions — the irremovable impact — after an operation has been decarbonised as much as possible.
However, critics of carbon credits argue that carbon markets are a way for large polluters to buy permission to pollute. What’s worse is that many credits fail to achieve the offsets or reductions that they promise. Studies show that most offsets available on the market don’t reliably reduce emissions, and instead function as a way for the worst polluters to launder their reputations, while robbing the race for net zero of much needed urgency.
Could AI be part of the solution?
Ironic as it might seem that a technology on track to consume as much energy as the whole of Japan by the end of the decade could be a key part of the answer to a sustainability problem, some industry figures believe it could be just that.
Jonathan Horn, CEO and Co-founder, Treefera — a data platform that aims to help businesses decarbonise their supply chains — argues that AI is “fundamentally reshaping the way supply chain organisations approach carbon credits.”
Supposedly, the technology is changing the ways that transparency and reliability are ensured. “Previously, the process of verifying offsets was slow and prone to error, relying on outdated systems. By applying advanced models, AI can synthesise vast datasets to measure, verify, and monitor offsets with unparalleled accuracy and precision,” he says. If it works, it could be an essential step in taking carbon credits from where they are — murky, unverifiable, and often a lot less gren than they look — to where they need to be. “Carbon credits that are credible and backed by robust, transparent data help businesses meet regulatory requirements, build trust with stakeholders, and support decarbonisation goals,” Horn argues, citing the idea that “trust is critical for scaling sustainability initiatives and maintaining reputational integrity.”
A-eye in the sky — How does integrating satellite, drone, and ground data enhance supply chain sustainability strategies?
Of course, the trouble with AI is that, no matter how advanced the model you’re using it, if you’re data’s bad, your results won’t be worth the trees you burned to run your city-block-sized data centre.
Horn proposes a “synthesis of satellite, drone, and ground-level data” fed into AI. By leveraging multiple high-level image and data gathering methods, AI could provide supply chains with “a multi-layered view of risks. This, Horn continues, is vital for supply chain leaders managing risks like flooding, deforestation, or biodiversity loss.
“These diverse and comprehensive data inputs offer the ability to monitor changes at the first mile validating findings and providing precision where needed,” he says. Also, he notes that as regulations such as the EUDR require stricter environmental reporting, these tools enable companies to deliver more verifiable data than before, allowing them to remain compliant in a stricter regulatory environment.
AI takes centre stage in the climate crisis
In many ways, AI is a totem for the many (often contradictory) ways we are tackling (and refusing to tackle) the climate crisis. AI can be a powerful tool for gaining transparency into supply chains, potentially reforming a broken carbon credit system and helping to hold the world’s biggest polluters accountable. It is also one of the biggest sources of emissions growth in the world. Does the good that it has the potential to do outweigh the benefits of, say, just turning those servers off? If we’re going to talk about offsetting emissions, how about balancing out the emissions of a large industrial nation by just turning off all servers powering a technology that Microsoft’s CEO admitted is generating basically no economic value?
However, optimists like Horn argue that “the next 5 to 10 years will see AI take centre stage in transforming the approach taken to addressing climate-related risks.” The technology’s ability to analyse and reconcile vast datasets could help accelerate methane avoidance projects, conduct real-time risk assessments, and predict extreme weather events like floods, droughts, or wildfires before they take place, helping businesses protect their operations from disruption. This, he notes, “will be especially critical as extreme weather events become more frequent.”
Whether the impact of AI on the carbon credits market is positive and transformative, or just another way for a dirty sector to look clean, remains to be seen.
Holly Clarke, Product Manager Inventory AI at Peak, looks at using digital tools to better predict demand in the construction supply chain.
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The UK construction industry took a hit last year. In September, PwC predicted there would be an overall real spend contraction in the sector of -2.1% for 2024. But it’s not all bad news – it also estimated the sector would “return to a growth rate of 2.9% in 2025, overcoming headwinds linked to sustained high interest rates and investor caution”. So, we could see a significant increase in demand as the year goes on. But swings in predictions and several potential cuts to interest rates this year epitomise a market that remains uncertain and unpredictable.
Either way, the need to swiftly adjust prices and inventory levels to optimise performance and hit goals like On-Time In-Full (OTIF) is crucial for business success. For building materials suppliers in particular, optimising quotes to get good margins and ensuring inventory is in the right place at the right time can make all the difference in overcoming supply chain challenges and variable demand.
Getting inventory to the right place at the right time
Unlike running out of food in a restaurant, where customers can order other items off the menu, not having crucial materials for a construction project can bring development to a standstill. But because of this, organisations can end up holding too much stock in some locations to mitigate this risk, or holding too little at other locations without the ability to move it swiftly to where it needs to be.
Consequently, such an inefficient inventory management system can create added risks: too much stock generates waste from unused materials and higher storage/operational costs, too little leads to supply chain delays and missed sales opportunities, and both aspects impact profitability.
So, the question arises: how can you ensure you always have the right materials at the right sites? The key factor? Real-time visibility of inventory levels across your network. This enables you to order, balance and forecast stock levels throughout your network to ensure optimal stock levels at each location with high OTIF performance. And that’s made possible using AI.
A(I) dynamic approach
The supply chain disruptions in recent years have made ordering the right levels of products and materials increasingly challenging. What’s more, high inflation and low economic growth have also contributed to a market with fluctuating demand, making it harder to predict how much stock to hold for potential construction projects.
But the latest AI inventory optimisation platforms use AI to offer dynamic inventory capabilities. Through these platforms, manufacturers can accurately forecast demand, with AI analysing data like inventory, sales, service and availability – alongside the costs of holding too much stock – to build ideal inventory levels at each location. This includes harnessing stock replenishment capabilities, with AI analysing data across the network to match quantities of stock with demand and free up working capital tied up in slow-moving stock.
In a construction context, for example, AI-generated insights might show that one manufacturing site has sufficient materials to meet customer orders, but that another site only three miles away is low on stock. So, instead of the low-stocked site producing or buying more stock, transferring a certain quantity between the sites or making the delivery from the better-stocked location could be a cost-efficient and effective alternative.
Of course, from bad weather disrupting deliveries and sales to new materials needed for an influx of orders, there are so many variables that can impact inventory levels. That’s why AI is so beneficial in analysing a vast range of factors across a vast array of systems and providing supply chain managers with the information needed to make accurate, data-driven decisions.
Securing the best quote
The costs of materials and services, alongside demand, can fluctuate throughout the year, so material quote prices should do the same.
But pricing lists can remain stagnant for months, with teams reliant on spreadsheets. What’s more, potential clients want quotes delivered quickly, tailored to their needs. Again, trying to work out the right quote can be a complex and time-consuming activity. Not only that, but with quotas to hit or pressure to secure business, companies might over-discount, or price the service too high. All of this risks losing business to competitors.
The optimal price, however, will win new business without leaving money on the table. AI can automatically provide companies with recommendations for optimal price recommendations, including list pricing and quotes. By digesting data from across the company and balancing complex manufacturing demand with business KPIs, technology can preserve margins while also driving revenue.
This dynamic pricing, coupled with the financial and performance gains made from keeping optimal stock levels, allows these companies to offer far more competitive, tailored and flexible quotes.
Empowering manufacturing teams to stock smarter and build better
As we begin 2025, for now, predictions of growth in the sector from last year stand in contrast to an economic landscape still struggling to recover. Hopefully this takes a turn for the better and, along with it, demand for construction. But such uncertainty simply points to the need for tools to optimise inventory levels and quotes to best protect business and profits.
Using AI, building materials suppliers can maximise their margins while avoiding stockouts, cost overruns and lost deals. It provides a dynamic strategy for both inventory and pricing – and that’s vital in such a volatile landscape.
By maintaining optimal stock levels and providing the optimal pricing in every instance,manufacturers are primed to consistently meet sales targets and service level agreements with their customers. By using AI to stock smarter, they can build better.
Anthony Michael, Senior Practice Director at Searce, looks at the role of AI in helping supply chain organisations elevate their location intelligence.
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The global supply chain industry is at an inflection point. Rising demands, sustainability pressures, and evolving consumer expectations are pushing companies to rethink operations. Modern technologies like AI and location intelligence are no longer optional – they’re essential. To navigate this complexity, companies are actively exploring modern technologies like AI and location intelligence – not as optional tools, but as essential drivers of efficiency, resilience, and cost savings. And we’re already seeing the real impact. Benefits range from enhancing demand forecasting and optimising delivery routes to enabling real-time decision-making. With AI, supply chains are beginning to unlock their full technological potential.
Forward-thinking enterprises are leading the charge, proving that the right innovations can drive measurable outcomes. Admittedly, some use cases may initially seem generic. However, their real value becomes clear when they deliver tangible improvements in key KPIs. These improvements include, for example, profitability and improved customer lifetime value (LTV).
Location Intelligence as a catalyst for efficiency
Simply put, location intelligence uses geospatial data – such as routes, distances, and landmarks – to generate actionable insights for transportation, logistics, and inventory management. For supply chains, location intelligence plays a pivotal role in improving operational efficiency, enabling smarter decision-making across site selection, delivery optimisation, and fleet tracking.
Consider the case of one of Southeast Asia’s largest utility companies. In conversation with its CTO, they shared a unique challenge. The organisation struggled with ensuring that all utility drivers operating across multiple routes finished their shifts at the same time. This wasn’t just a matter of convenience – it was critical for avoiding union disputes and maintaining operational harmony. Location intelligence proved to be key. By analysing routes, stop times, and driver schedules, the company synchronised shift end times across its workforce. This not only prevented potential conflicts but boosted overall efficiency, showcasing how geospatial insights can solve complex challenges.
A similar transformation took place with a logistics provider in EMEA. Faced with rising toll costs and inefficiencies in cargo delivery, loading, and unloading times, they turned to location intelligence to optimise operations. By analysing optimal routes and streamlining workflows, they successfully reduced toll expenses from 4% to 1%. Also, they managed to cut overall unloading times by 40%.
Elevating customer experience through real-time insights
For supply chain businesses, transparency and communication are critical. Customers expect real-time updates on their orders, and companies that provide accurate tracking can improve satisfaction while reducing service costs by minimising inquiries and complaints.
Beyond basic tracking, real-time insights powered by AI and location intelligence are transforming supply chain management. Predictive analytics enable businesses to anticipate order surges, optimise inventory, and provide more accurate delivery timelines. Advanced delivery prediction takes this further, allowing companies to forecast delays and proactively re-route shipments to minimise disruptions.
AI’s pervasive influence on supply chains
We’re living in a transformative era where no article on any industry is complete without the mention of AI and the impact it’s started to have on key industry KPIs. AI is revolutionising how the supply chain industry operates, transforming every aspect from route optimisation and demand forecasting to risk management and predictive maintenance. By harnessing advanced algorithms and real-time data analysis, AI empowers businesses to anticipate disruptions, enhance safety, and improve efficiency across the supply chain.
One of the most impactful applications is predictive analytics. By analysing historical data and external factors like weather patterns, traffic conditions, and geopolitical risks, AI can forecast supply chain bottlenecks before they occur. This allows businesses to proactively adjust routes, optimise inventory levels, and avoid costly delays.
The GenAI factor
Generative AI, a subset of the larger AI universe, is also helping businesses by streamlining customer service through AI-powered chatbots, significantly reducing complaint resolution times. Additionally, Gen AI models are being trained on company-specific documents – legal, operational, and financial – to make sure disputes are managed efficiently.
But AI’s influence extends beyond text-based solutions. Video and audio analytics are being applied across a wide range of use cases. For example, AI-powered cameras installed on trucks can capture real-time road conditions, enabling drivers to adjust routes and rest periods for safer, more efficient journeys. Meanwhile, Optical Character Recognition (OCR) technology, once limited in its scope, has advanced significantly, now achieving greater accuracy in address recognition and faster delivery times. This not only speeds up order fulfilment but also cuts operational costs. In fact, we’ve seen up to 100x cost savings in courier companies by reimagining workflows and optimising document extraction models.
That said, AI’s influence extends beyond operational improvements. As businesses face mounting pressure to adopt environmentally responsible practices, AI is emerging as a critical enabler of sustainability, helping companies reduce emissions, optimise energy use, and build more resilient supply chains.
Building a sustainable future
As the earth experiences record-high temperatures, with global warming predicted to pass 2.9°C this century, the need for sustainable supply chain practices has never been more urgent. Supply chains account for a significant portion of global greenhouse gas emissions, particularly Scope 3 emissions – those generated across the value chain, from production to transportation. These emissions are both dangerous and complex to measure, as more than 70% of them stem from supply chain activities and often extend beyond a company’s direct operations.
AI plays a crucial role in addressing these challenges. By optimising transportation routes, improving energy efficiency, and enhancing supplier audits, AI helps companies reduce their carbon footprint without compromising operational performance. Real-time data analytics enable smarter decisions, such as consolidating shipments and choosing lower-emission routes.
AI-powered carbon tracking provides clear insights into supply chain emissions. This helps businesses set realistic sustainability targets and meet evolving ESG requirements. With frameworks like the EU’s Corporate Sustainability Reporting Directive (CSRD) driving accountability, adopting AI-driven solutions is key to staying compliant and competitive.
Navigating ethical and practical challenges
AI holds significant promise for improving supply chains’ operational efficiency. However, the technology also poses ethical challenges.
Concerns around data privacy, algorithmic bias, and job displacement are among the most pressing. Without clear frameworks, AI-driven decision-making can undermine trust and expose companies to reputational and regulatory risks.
Addressing these challenges starts with establishing a strong governance. Businesses need clear AI frameworks that ensure ethical standards, data security, and regulatory compliance. This involves an inclusive approach through cross-functional collaboration across departments and stakeholders. Bringing together employees, partners and customers, ensuring AI systems are transparent, fair and accountable needs to be a holistic effort.
Equally important is ensuring workforce readiness. As AI reshapes supply chain operations, businesses must invest in upskilling employees to work alongside intelligent systems. Ideally, this will turn potential disruption into an opportunity for innovation.
By embedding ethical practices into AI adoption, companies can not only unlock supply chain efficiencies but also build resilience and trust across their ecosystems.
The new crop of tools is allowing Flexport to expand supply chain visibility and management capabilities for its customer base.
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Supply chain technology firm Flexport has announced the launch of more than 20 tech and AI-powered products designed to transform global logistics. The tools aim to help logistics and supply chain organisations increase visibility into their operations, and are based on Flexport’s own reserves of proprietary logistics data.
This new wave of AI-powered supply chain products and tools has made Flexport “the largest provider of AI tools for global supply chains,” according to Flexport CEO Ryan Petersen. “While many startups are emerging to provide AI tools for logistics, they lack the data required to train the AI models and struggle to sign up customers to use their technology. Our scale as one of the largest logistics providers in the world gives us huge advantages in both creating the technology and getting it into the hands of businesses operating in the real world.”
Highlights from the release
The flagship product released this week is Flexport Intelligence, which allows businesses to ask questions in natural language and receive immediate insights about their supply chain performance. Flexport customers can use this AI-powered tool to build reports and create dashboards with no technical skills required, making it extremely easy for operations managers to take control of their global supply chains.
Another major announcement within the release is Flexport Control Tower. This product helps businesses use Flexport’s supply chain technology even for shipments where they’ve contracted another carrier or forwarder to move the freight.
Flexport “will build the smartest supply chains in the world”
The company argues that it is “uniquely positioned” to harness AI’s full potential, combining proprietary data, enterprise-scale operations, and AI-ready tech platforms to make new innovations easily accessible to customers.
“Flexport has been leveraging AI for years, but with the explosion of large language models and new open-source tech, we’re able to innovate faster than ever before,” said Petersen. “AI is incorporated throughout the new products and features you’ll see today. Our vision is to make global commerce as simple and reliable as flipping a light switch, and today’s technology release is the clearest sign that we’re well on our way to bringing that to life.”
Flexport Intelligence consolidates fragmented data into easily accessible, actionable insights. The tool allows businesses to ask complex logistics questions in simple terms and receive instant answers and interactive reports. The business is also enhancing Flexport Fulfillment’s AI Demand Planning and Inventory Placement solution. Using advanced AI models, Flexport can process a multitude of client and industry data points to optimize inventory distribution across the Flexport network, ensuring we allocate the right levels of inventory as close to consumer demand as possible. The company is also expanding its use of AI Voice Agents, deploying them to work with carriers to improve quality and efficiency in its behind-the-scenes operations.
“Flexport’s technology isn’t just about automation—it’s about augmentation,” said Sanne Manders, President of Flexport. “Our tools free up human ingenuity to tackle challenges AI alone can’t solve, delivering the highest quality service at the best value.”
Durgadutt Nedungadi, Sr. Vice President of International Business at Netradyne, looks at the impact of AI on logistics in the supply chain.
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Logistics, the most critical pillar in the Supply Chain, grapples with many challenges. From driver shortages to increasing road accidents, logistics operators are increasingly turning to AI-powered fleet management systems to enhance safety, improve visibility, and build more resilient, agile fleet operations.
In today’s complex global supply chain ecosystem, ensuring fleet safety and visibility is crucial to maintaining seamless operations. While fleet operations are a critical link in the supply chain, traditional technologies often fail to deliver real-time asset visibility and management, making it difficult to mitigate potential risks effectively.
However, organisations are increasingly recognising the benefits of artificial intelligence (AI) technology in improving driver safety, operational visibility, and the overall efficiency and sustainability of supply chains. Research that we conducted last year—based on responses from the top Supply Chain leaders in the UK and EU—revealed that while only 33% of supply chain professionals currently use AI for fleet safety monitoring, 81% plan to implement AI solutions within the year.
Organisations can improve accuracy, efficiency, and profitability in their supply chains by using AI-driven fleet safety systems with computer vision, predictive insights, and better operational control.
Speed and accuracy — the top priorities for goods delivery
Our survey revealed that 57% of supply chain professionals consider accuracy and timeliness the top priorities for goods delivery. This reflects broader consumer trends as today’s shoppers increasingly demand near-instant delivery and greater convenience when receiving their purchases. A recent Retail Week report, ‘Shopper Unlocked: Inside the Minds of 1,000 Consumers‘, highlights that delivery experiences now outweigh loyalty perks or alternative payment options in importance for shoppers. Real-time order tracking has also emerged as a key factor in customer satisfaction, underscoring the growing demand for transparency throughout the delivery process. Businesses that fail to meet these expectations risk losing customers to competitors and potentially damaging their brand’s reputation.
Poor fleet visibility and driver shortages are two significant challenges hindering delivery precision in logistics and transportation. Accidents are another critical issue, causing product damage during transit, harming brand reputation, affecting driver well-being and availability, and driving up operational costs.
Enhancing delivery precision with AI-driven insights
While data is at the core of effective fleet management and safety, many existing systems rely on older technologies like telematics and GPS. These technologies are often limited in their functionality and cannot provide the level of granularity that modern AI solutions based on vision can. Integrating such advanced tools into goods delivery processes can significantly enhance delivery precision and predictability by improving fleet visibility and driver engagement.
Modern AI tools serve as powerful data mining assets for fleet managers, analysing large volumes of data from a wide range of sources to deliver actionable insights. For example, motion sensors such as accelerometers and gyroscopes, which track the speed and orientation of vehicles, can provide valuable insights into driving manoeuvres. When combined with data from computer vision systems, these insights offer fleet operators an accurate and holistic view of their operations, helping them to make proactive adjustments to routes or schedules and helping maintain fleet safety while ensuring the timely delivery of goods. By improving operational efficiency, businesses can provide real-time customer updates, ensure precise delivery timelines, and offer greater transparency—ultimately meeting consumers’ growing demand for reliability and visibility in the delivery process.
Smarter fleet safety management
AI’s real time data analysis capabilities also play a crucial role in fleet safety. Research shows that human error accounts for over 70% of road accidents, with driver fatigue, excessive speed, and inattention cited as the most common contributing factors. AI systems work to minimise these errors by actively identifying and addressing safety risks. For instance, AI-powered video-telematics and analysis can detect dangerous driving habits such as speeding, distracted driving, and tailgating. By providing real-time alerts—which automatically factor in environmental and contextual data—to drivers and fleet managers alike, these systems offer accurate risk assessments, enabling corrective actions before an incident occurs.
The advanced edge computing-based mapping and analysis technology integrated within modern AI solutions provides valuable insights, helping fleet operators make informed decisions about driver behaviour patterns. Not only that, but these insights also enable operators to draw unbiased conclusions in the event of an accident. According to a joint report by NETS, NHTSA and OSHA, road accidents cost employers nearly $60 billion annually. Leveraging advanced driver safety systems is critical to cutting down costs in the long run while enhancing fleet safety.
Furthermore, modern AI-powered fleet management solutions can also create comprehensive driver performance profiles using advanced driver-scoring systems to evaluate behaviour in detail. These insights allow fleet operators to positively reinforce good drivers and reward safe driving practices through incentive programs. Gamifying the driving experience in this way helps to enhance overall fleet performance and establishes a proactive safety culture within organisations. These insights also offer critical data to support driver exoneration in road accidents, ultimately helping reduce driver churn, a significant issue within this sector.
The benefits of these advanced technologies extend beyond the fleet itself. Improved safety and visibility directly impact the broader supply chain, driving greater efficiency, cutting operational costs, and reducing disruptions.
AI-powered data driving safer and more efficient fleet operations
As transportation remains one of the most challenging aspects of supply chain management, ensuring fleet safety and visibility is more critical than ever.
AI-powered solutions are revolutionising fleet management by delivering real-time insights that enhance efficiency, improve safety, and enable proactive decision-making. By leveraging AI-driven data analysis, logistics providers can overcome operational challenges and gain a competitive edge in an increasingly demanding industry.
As businesses prioritise speed, accuracy, and transparency in goods delivery, AI will play a pivotal role in shaping the future of fleet management and supply chain resilience.
Jonathan Colehower, Global Supply Chain Strategy Practice Leader at UST, looks at the trends that are poised to redefine supply chains in 2025.
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Supply chains have undergone profound transformations in recent years. These changes have been driven by disruptions ranging from the global pandemic that brought economies to a standstill to ongoing trade tensions and climate-related challenges. This persistent state of uncertainty suggests that disruption is far from over. Right now, it appears that the supply chain landscape will only grow more complex and politically charged.
To navigate this evolving environment, supply chain leaders must prioritise resilience, sustainability and innovation. Embracing technology, forging strategic partnerships and enhancing omnichannel experiences are key strategies that will empower companies and leaders to thrive amid uncertainty. Below we take a look at these three elements and the value they bring.
AI’s Transformative Role
Firstly, artificial intelligence is emerging as the ultimate shock absorber for supply chains. The technology is automating operations, generating real-time insights and seamlessly connecting systems. However, even before the pandemic, supply chain managers struggled with increasing complexities and rising customer expectations.
In e-Commerce, for example, acceptable delivery times shrunk from 7-10 days to 24 hours or less. Today customers demand real-time visibility and traceability. Therefore, AI’s ability to track every supply chain touchpoint from manufacturer to consumer has become an essential solution.
Beyond real-time tracking, AI enables predictive insights that help businesses proactively address disruptions and enhance resilience. However, for AI to deliver maximum impact, companies must align generative AI deployment with business objectives and workflows.
According to UST’s AI in the Enterprise survey of 600 senior IT decision makers the overwhelming majority ( 92%) said that their company’s AI implementation aligns with their strategic goals, demonstrating that leaders recognise the importance of this.
The key lies in identifying areas where AI adds the most value and re-thinking end-to-end processes accordingly. Done right, AI can revitalise business operations and elevate the industry as a whole.
The Power of Strategic Partnerships
Next, globally strategic partnerships are becoming a cornerstone of modern supply chains. With globalisation intensifying interdependence – companies are finding that traditional business models no longer suffice.
The growing complexity and vulnerability of supply chains has made collaboration essential for reducing costs, increasingly agility and meeting customer demands. By leveraging each other’s strengths, companies can co-develop solutions, enhance operational efficiency and drive long-term growth.
At UST, we partnered with a global retailer to support the launch of a seamless “shop from home” digital store, ultimately helping the client achieve customer conversion rates of 4.5%. However, successful partnerships require a thoughtful approach – businesses must carefully assess the level of collaboration they require and adopt a forward-looking strategy to ensure sustained success.
The Rise of Omnichannel Customer Experiences
Lastly, the shift towards omnichannel customer experiences has become a defining trend in global supply chains.
The pandemic accelerated consumer demands for seamless, personalised interactions across multiple touchpoints including e-Commerce platforms, mobile apps and physical stores. As such, businesses can no longer rely on siloed multichannel options – instead they must integrate data and systems to provide a consistent and tailored experience at every stage of the customer journey.
Additionally, as customers continue to operate more frequently on digital channels, the demand for varied order fulfillment options from home delivery to shop in-store has increased. As such, omnichannel strategies and the ability for supply chains to communicate behind the scenes has become of utmost importance.
The future of supply chains lies at the intersection of technology, collaboration and customer-centricity. AI-driven intelligence, strategic partnerships and omnichannel integration will define the next era of supply chain management, helping businesses build resilience and adaptability in an increasingly complex world. Companies that proactively embrace these trends will not only mitigate risks but also unlock new growth opportunities, ensuring they stay ahead of disruption and continue to meet evolving customer expectations.
Julian Geiger, Vice President AI Product and Transformation at the Nemetschek Group, explores the role of AI in transforming the construction industry’s supply chain.
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The construction industry is one of the sectors with the lowest level of digitisation to date. Given the scale of the sector, its considerable contribution to the global economy and its impact on the environment, it’s somewhat surprising that this should be the case.
Few within the industry would doubt that an increase in digitisation would have many positive effects. The efficiency and sustainability of the construction supply chain in particular would benefit from this, according to the assessment of industry experts. A practical solution for this is offered by modern, software-based construction planning systems that rely on artificial intelligence (AI).
AI powered solutions to today’s challenges
No industry can currently ignore the issue of sustainability. The construction sector in particular has a lot of catching up to do here and must react accordingly. It’s a lesser-known fact that the construction industry is responsible for around 38% of global CO₂ emissions. Given its carbon footprint, arguably it has a duty to decarbonise to a more palatable level.
Therefore, innovative and promising concepts that contribute to achieving climate protection goals are urgently needed.
An indispensable prerequisite for achieving this goal, is the consistent digitisation and automation of processes. The main goal here is to relieve the burden on supply chains and thereby also reduce CO₂ emissions. However, the construction industry in this country does not yet have the reputation of being a digitalisation pioneer. The processes are still very rigid. This is especially true when it comes to planning the requirements of building materials and designing logistics chains.
Most processes are still based on paper documents, which hinders consistent processes. Waybills and delivery documents are often still signed by hand and can easily get lost. The relevant data must be entered manually into IT systems, which presents many sources of error.
In addition, little attention is paid to the environmental friendliness and CO2 footprint of materials when selecting them. There is also usually no comprehensive overview of which building materials are needed in what quantities, where and when. This leads to complicated and often unnecessary transport routes for trucks and other vehicles.
Material requirements planning: the key to efficiency and sustainability
In order to increase the efficiency of workflows here, maximum transparency is required along the entire supply chain. Those responsible must carefully determine how to adjust the ordering of materials to actual requirements.
This is the only way to effectively counteract excessive waste of valuable resources. According to GIRI somewhere between 10% and 25% of project costs are lost through errors. That’s a double-digit percentage of building materials ordered unnecessarily or used incorrectly. This leads to inefficiencies in construction, drives up costs and is an obstacle on the way to greater sustainability. However, optimised demand planning alone is not enough – attention should also be paid to where the material comes from. It is important to keep in mind that building materials such as concrete are produced in different regions and countries according to different standards. This has a significant impact on quality and therefore also influences the CO2 footprint.
Therefore, it makes sense to purchase materials from regional suppliers. This shortens transport routes, which in turn conserves resources and minimises pollutant emissions.
AI-based construction planning for maximum process efficiency
In order to adequately address all of those challenges, well-thought-out project planning tools are required that are optimised with regard to the processes in the construction industry.
The solutions work particularly effectively when they are equipped with AI. For example, the technology can independently recognise certain conflicts in the procurement workflows. This is the case, for example, when ordering building materials that do not match the type or quantity of the building in question. Here, AI can raise the alarm and initiate an optimisation of the processes. The result? Significantly less material waste and unnecessary transport, which noticeably relieves the burden on the supply chain.
Another advantage of AI-based planning systems is that they can handle large amounts of data extremely well, analyse them comprehensively and draw the right conclusions from them. By way of example, large construction companies work on numerous different projects in parallel and cooperate with a large number of suppliers who are spread across the entire country. The AI-supported evaluation of relevant data makes it possible to quickly see which delivery partners are suitable for a specific construction project.
This brings more efficiency to the supply chain. However, it is important to always keep an eye on the entire ecological balance. This includes the production of the materials, the type of transport and the delivery distance. It is possible that environmentally-friendly concrete with a longer journey proves to be more sustainable when compared to a conventionally produced building material from the neighbouring town.
Such an overall view requires a large amount of valid data, which can be evaluated quickly and thoroughly using an AI solution, thus paving the way for sustainable and economically sensible decisions.
Construction companies and suppliers benefit from demand forecasts
In addition, AI-supported planning tools based on big data analyses can be used to precisely predict future demand for building materials. Depending on the project workload, those responsible in the construction companies can realistically estimate how much concrete, gravel or wood will be needed in the coming weeks.
This improves the coordination of logistics processes, optimises the use of budgets and makes a significant contribution to cost savings. On the other hand, the manufacturers of building materials also benefit; they can use demand forecasts to closely monitor the market and align their production capacities accordingly.
The current share of renewable energies in the power grid can also have an influence on this. If, for instance, a lot of solar and wind energy is currently being fed into the grid, the production rate can be adjusted and increased accordingly. If there is less surplus energy, manufacturers can reduce production again.
AI tools determine the future of the construction industry
The analysis of large amounts of data and the targeted use of AI-based planning tools will significantly drive the digitalisation of the construction industry in the future – that much is certain. In this way, a variety of positive effects can be achieved, such as an efficient and sustainable supply chain.
Slavena Hristova, Director of Product Marketing at ABBYY, examines the role of artificial intelligence in meeting supply chain challenges.
Published
29 January 2025
Estimated Read time
4Mins
Slavena Hristova, Director of Product Marketing at ABBYY, examines the role of artificial intelligence in meeting supply chain challenges.
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Kick-started by the global pandemic, the transportation and logistics industry has seen a boom in digital transformation over the past five years. While we’ve started to see companies embrace general technology, however, a recent study from HERE Technologies and AWS found that just 19% of logistics companies are using AI for advanced use cases, such as demand forecasting.
In 2025 logistics companies should ensure they don’t fall behind their customers in other industries in putting to use advanced automation, powered by AI.AI-driven automation can streamline multiple complex processes for logistics organisations. These include inventory management and warehouse automation, which has the potential to transform functions across the supply chain. These efficiency gains will help businesses counter tight margins while staying agile. Perhaps most importantly, they will help logistics companies deliver better service in an increasingly demanding market.
Embracing new, advanced technologies will increasingly be key to success for logistics companies. So, what steps do they need to take to see the benefits?
Modernise infrastructure
Logistics companies must make substantial investments in modernising infrastructure, operations, and workforce skills. A Neos Network’s study revealed that 63% of UK logistics companies report a shortage of digital skills. Therefore, a successful AI implementation will, however, require not only technology upgrades. Companies will also need a strategic focus on upskilling personnel to manage and optimise these new systems.
Integrated cloud-based platforms will be essential, enabling companies to unify their logistics needs into a single, centralised dashboard.
Intelligent document processing is a logical first step towards implementing AI-powered technology. The pocess can deliver immediate value in this document-heavy industry, creating quick business wins with minimal investment. Businesses in the logistics sector handle large volumes of documents such as invoices, shipping documents, and customs forms. AI-powered intelligent document processing can extract data from these documents accurately, reducing manual effort and errors. AI like this can reduce costs, increase transparency and accuracy, and allow for faster, data-driven decision-making.
Focus on becoming greener
Green logistics will become a key focus as companies strive to align with sustainability goals. Motivated by regulatory pressures and consumer demand, logistics companies will further integrate eco-friendly practices across their operations. This will become increasingly important as these sustainability regulations become less flexible over time.
The HERE Technologies and AWS study also revealed that over 60% of logistics companies lack defined sustainability goals. The study highlighted this as an opportunity for organisations to leverage technology to streamline fuel usage and routes. Not only did this address environmental concerns, but it also reduced spending on fuel.
By integrating eco-friendly digital practices into their supply chain and operations, businesses can reduce their carbon footprint, lower energy consumption, and minimise waste. One example is using AI-powered technology to speed up customs clearance through Intelligent Document Processing (IDP). IDP enables fast-moving consumer goods (FMCG) manufacturers to accelerate their trucks through border customs, cutting clearance times by over 90%. Portumna Pastry Ltd, a pastry supplier based in Ireland, leveraged AI-powered IDP to reduce their customs clearance time at the EU/UK border from one hour to only five minutes.
Purpose-built AI can significantly optimise energy usage, streamline logistics operations, and minimise emissions. By enhancing operational efficiency, it not only predicts maintenance needs but also reduces delays across the supply chain, ensuring smoother and more sustainable processes.
Mistakes in freight forwarding documents can stop a shipment in its tracks at the border, grinding operations to a halt and causing delays for customers while fuel and demurrage costs rack up. To keep logistics smooth and efficient, AI-powered intelligent document processing can extract exactly the right information from huge volumes of documentation, delivering the right information to the right systems at the right time.
Embrace real-time monitoring of the supply chain
Finally, logistics businesses can rely on real-time monitoring to improve transparency across the supply chain. Using IoT and data analytics in monitoring can provide end-to-end visibility, ensuring a more customer-centric and resilient supply chain.
Access to real-time AI-powered insights gives businesses the ability to proactively address challenges like delays, shortages, or changes in demand, minimising the impact of these challenges on customers. Embracing AI-powered digital tools will enable businesses to adapt more quickly and reduce costs, even as the market remains volatile.
The opportunity is immense: by adopting AI-powered, digital solutions, logistics businesses can significantly increase operational efficiency, streamline processes, and ensure better decision-making. Into 2025, leveraging these technologies will not only drive efficiency but also position logistics companies at the forefront of innovation, enabling a more sustainable and responsive supply chain for the future.
Organisations are racing to inject AI into their supply chains, but often fail to reckon with the carbon cost of the technology.
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Artificial intelligence (AI) was the buzzy technology of 2024, and it looks set to define 2025 as well. The technology promises to unlock new efficiencies and increase visibility for organisations. In particular, many organisations believe that AI could be a powerful tool for taking control of their environmental impact and making critical strides towards their sustainability ambitions.
“Throughout 2025, the supply chain sector will only continue to innovate further through the use of advanced artificial intelligence,” HaulageHub Co-Founder Scott Robertson told SupplyChain Strategy. According to Robertson, the climate crisis means that “visibility and sustainability within the supply chain have never been more important.” Therefore, it’s imperative that supply chain organisations embrace AI, which he believes will “be pivotal in improving the industry’s carbon footprint.”
Robertson isn’t alone in his support for AI as an effective weapon in the fight against climate change (or in the pursuit of visibility, efficiency, and profit). Across the supply chain sector, organisations are racing to inject AI into their operations — from more traditional analytical tools to a new wave of more independent “agentic AI” that can function with even greater autonomy.
Investment in AI (generative or otherwise) throughout global supply chains is set to grow from around $600 million in 2020 to well over $51 billion by 2030.
Driving sustainability in the supply chain with AI
In many ways, the argument that AI is poised to have a positive impact on supply chains is a persuasive one. For example, let’s look at short-haul, last mile delivery networks — one of the most fraught areas of the supply chain when it comes to emissions.
Robertson notes that, as of now, empty runs — in which an unladen vehicle travels to or from a delivery — account for over 30% of all HGV miles in the UK. This contributes over 5 million tonnes of needless CO2 emissions annually. Through leveraging AI systems, he believes, supply chain organisations could reduce this figure significantly.
“The technology enables hauliers to track and measure emissions in real time, thereby allowing them to make informed and data-driven decisions to improve their sustainability efforts across the supply chain, while also reducing costs,” he explains.
With the transport industry poised for even further transformation this year, Robertson argues that “AI and machine learning are facilitating even more innovations such as autonomous trucks, advanced telematics, and the integration of electric and hydrogen-powered vehicles.”
He continues: “The supply chain sector will need to embrace these developments with open arms to ensure companies are at the forefront of a digital, more efficient, and more sustainable future. The business case for sustainable logistics is clear and the sector will only benefit from implementing AI in their processes to achieve this in 2025.”
AI for sustainability? There’s a catch, obviously
Because of course there is. Specifically, there’s a problem with the idea that AI (especially generative AI) could be a cure-all for supply chain sustainability woes. First of all, even if AI can deliver critical efficiencies and visibility that Robertson suggests, efficiency and visibility aren’t the whole battle.
Logistics organisations need to examine alternative fuels, more circular economic practices, and a collaborative and holistic approach to tackling the climate crisis. AI is only able to fight half of that battle. Not only that, but AI may also be doing more harm than good.
Since the launch of Chat-GPT and other GenAI tools, demand for data centres has skyrocketed. An industry that fought for over a decade to reign in its electricity and water usage is abandoning its climate commitments as the demands of an AI age become apparent.
“What is different about generative AI is the power density it requires,” explains Noman Bashir, lead author of an MIT impact paper released earlier this month. “Fundamentally, it is just computing, but a generative AI training cluster might consume seven or eight times more energy than a typical computing workload.”
As a result, generative AI could consume as much energy as Japan by next year. Chat-GPT alone uses power equivalent to around 180,000 US households every day, and a single conversation with Chat-GPT uses about one regular plastic bottle of drinking water. According to OpenAI, the platform (which is just one of several AI models on the market) processes about a billion queries per day.
How can a technology that is actively contributing to the climate crisis be an instrumental part in solving it? Can the efficiencies AI creates offset the damage it does? Or will AI emissions be the next big sin shuffled under the rug of “untraceable” scope 3 emissions?
Supply chain experts from Ivalua, DataDocks, SCALA, Brookfield, Project44, and more share their predictions for the future of the sector in 2025.
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With 2024 drawing to a close, we reached out to some of the industry’s leading experts to get their predictions on what the next year might hold for the global supply chain sector.
The responses we received covered a wide range of topics, from warehousing to AI and cybersecurity. One thing remained constant, however: 2025 will be a year that poses significant challenges for supply chain professionals around the world, and it will take a combination of technology adoption, strategic planning, and collaboration to rise to them.
Understanding the supply chain to manage risk has never been more important
“More in depth risk assessments will become increasingly essential. It’s crucial for businesses to have a deep understanding of their supply chain, conducting thorough risk assessments and scenario planning in order to foresee and mitigate risks before they become major problems.
Organisations need to ensure that they are mapping their supply chain network, ideally collaborating with suppliers to get as far down the supply chain as possible: consistently providing updates and regularly communicating to avoid any disruptions.”
Visibility, technology, and risk mitigation will separate 2025’s winners and losers
“We’ve experienced a series of turbulent years for global supply chains. With ongoing geopolitical changes and technological progress, 2025 is set to be another crucial year for building supply chain resilience.
“Furthermore, ongoing global conflict could threaten supply and distribution in certain global territories, necessitating more resilient and adaptable supply chain strategies. Nearshoring is emerging as a strategic response to disruption, with companies opting to bring production closer to key markets, thereby reducing transportation costs and mitigating risks.
“One area that could be increasingly key in creating resilience is effectively deploying emerging technologies. Those businesses choosing to integrate Artificial Intelligence (AI) across supply chain operations may reap the benefits of improved demand forecasting, inventory management, and general efficiency, for example.
“Ultimately, understanding your operations, making the most of technology, and mitigating risks in the supply chain will be critical in 2025.”
2025 will be the year of smart, strategic warehousing
“Throughout the latter part of 2024, we saw a return of confidence to the European logistics market as inflation began to turn and interest rates cooled off. As a result, we are seeing a number of large asset portfolios come to the market, as well as occupancy rates within our own portfolio growing – largely driven by built-to-suit projects with large corporates. As we look ahead to 2025, the European logistics market is poised for significant activity and transformation as tenants demand high-quality spaces.
“The primary themes driving the logistics landscape in 2025 will be automation, digitisation, and sustainability. Companies across the entire supply chain, from sourcing to fulfilment, will prioritise these elements, even as they navigate the challenges of rapidly evolving trends.
“This is why the role of the landlord will become ever more important in 2025. Businesses will increasingly turn to warehouse and logistics partners who can leverage the power of ‘connected networks’ to achieve maximum optionality from their space, such as unlocking access to land banks and the grid.
“There will be a particular focus on premises in strategic, best-in-town locations that offer excellent transport links, as well as spaces which attract talent. A move to campus locations, such as multi-functional logistics parks, is therefore an emerging trend that I believe we will see more of as we progress through 2025.”
The next generation of supply chain leaders will accelerate tech disruption
“2025 will be a transformative year for the supply chain – not just through the implementation of disruptive technologies, but also through new business models driven by a new generation of supply chain leaders.
“This will undoubtedly cause a shift in processes and technological adoption across the supply chain, with millennials open to innovation based on their ability to quickly adapt and learn to use new platforms.
“Here, we can expect the next generation of supply chain leaders to increasingly harness automation and AI to streamline workflows without sacrificing productivity.
“At the same time, millennial employees prioritise sustainability and ethical practices in the companies they work for. With more millennials stepping into leadership roles, we can expect this shift to push more organisations to adopt new processes and technologies that enable more sustainable supply chain operations, as well as enhanced traceability to ensure socially responsible sourcing. Ultimately, this unique perspective and new set of leadership skills will help to drive innovation and enhance the resilience of supply chain operations.”
“In 2025, data will be as important as ever as organisations face increasing regulatory pressure and growing consumer demand and expectations for sustainable practices. Organisations’ ability to collect, manage, and utilise data will be key to ensuring they don’t fall behind the competition.
In addition to the need to comply with regulations such as CSRD and CS3D, initiatives like Digital Product Passports (DPPs) will gain traction, particularly in sectors like retail and battery production, to respond to growing consumer demand for transparency. Added pressure for circular initiatives will come from the EU’s forthcoming introduction of DPPs in 2027 which aims to tackle unsustainability by providing detailed digital records on product origins, materials, and recyclability. Forward-thinking brands, like Tesco’s F&F clothing range, and fashion brand Nobody’s Child have already taken steps toward this change, and more will follow suit next year.
“The real challenge and opportunity we’ll face in the coming year lies in identifying which solution providers will effectively address the comprehensive data management challenges presented. The technology must enable companies to facilitate data collection from different sources to track metrics, monitor progress, and identify areas for improvement, as well as report. We’re likely to see a phased approach, with the key focus being on balancing regulatory requirements with practical implementation. This will require significant investment in both technology and process transformation, but sustainability should be seen as an investment, not a cost.”
Cybersecurity problems in the supply chain aren’t going away
“In 2025, cybersecurity is likely to remain a priority for supply chain businesses. As supply chain companies leverage innovative solutions and digitise their operations, the risk of cyberattacks can also increase.”
“According to Statista, approximately 183,000 customers were affected by supply chain cyberattacks worldwide in 2024. This makes cybersecurity a critical issue to address for supply chain businesses. Cyberattacks can easily disrupt supply chain operations, resulting in delays, lost revenue, and a damaged reputation. This, in turn, can hinder the long-term growth of supply chain businesses.”
“By deploying advanced solutions based on the Zero Trust Architecture (ZTA), supply chain operators can ensure that suppliers, warehouses, and logistics systems operate securely without interruption.”
In 2025, organisations will struggle to juggle cost reduction with managing supply chain risks
“In 2025, as investment into peak procurement staff has stalled, organisations will need to juggle a stubborn focus on cost reduction against demand to re-architect supply chains so they are more flexible than ever before. This comes as geopolitical tensions mount, a shortage of critical materials remains, and more extreme weather events loom – all making the risk of supply chain disruption even more unpredictable.
“Procurement teams will face a tough balancing act next year, so understanding how to optimise suppliers and spend in these complex times will be critical. Organisations will need to focus on diversifying supply chains to reduce risk of disruption and reliance on China. This means making sure they can build strong relationships with their strategic suppliers, and that they can identify alternative sources of supply in case of unexpected disruptions.”
Geopolitics, economic pressure, and AI will shape the post-pandemic supply chain landscape
The post-pandemic supply chain transformation is about to hit its stride. 2025 will mark the end of reactive digitalisation and the beginning of truly intelligent operations.
Three forces will define the year.
First, geopolitical tensions will intensify supply chain scrutiny. Border checks will become more stringent, documentation requirements more complex, and origin verification more demanding.
Second, the economic climate will force a bifurcation in the industry. Companies that have invested in automation and AI will pull decisively ahead of those still relying on manual processes and disconnected systems. The performance gap between digital leaders and laggards will become too wide to ignore, particularly in warehouse operations and logistics coordination.
The third and most interesting force is the maturation of AI-powered compliance tools. These systems will transform how organisations handle regulatory requirements, turning what was once a burden into a competitive advantage. Supply chains will become simultaneously more compliant and more agile – a combination that would have seemed paradoxical just a few years ago.
These changes won’t happen all at once. Most companies will take a “wait and see” approach in the first half of the year. But those waiting for perfect certainty before acting will find themselves scrambling to catch up when the market accelerates.
The supply chain industry has received its lessons about preparedness – 2025 will show which companies took those lessons to heart.
The future of supply chain innovation lies with emerging technologies
“Emerging technologies like Gen AI, blockchain, and IoT are revolutionising supply chain operations, with AI taking centre stage in marketing procurement categories, including in-store marketing materials, printed communications, and marketing incentives such as in-store purchase-linked redemption programs and couponing for large brands.
As businesses in this sector aim to streamline complex processes, the granular insights provided by AI are proving indispensable. AI enables real-time monitoring and analysis, offering the visibility needed to optimise workflows and make data-driven decisions that directly impact efficiency and outcomes.
For marketing procurement, advanced AI models are set to transform demand forecasting, particularly in areas like production scheduling for printed communications and inventory management for in-store marketing materials. AI-driven insights can also anticipate fluctuations in redemption program participation or coupon usage by analysing historical and IoT data patterns. These capabilities help prevent overproduction, reduce waste, and align procurement strategies with actual consumer demand, ultimately improving sustainability outcomes.
Moreover, AI’s ability to automate routine tasks—such as processing procurement documents, analysing supplier data, or tracking marketing asset delivery—through intelligent automation and robotic process automation (RPA) will allow teams to focus on higher-value activities. This means marketers and procurement professionals can dedicate more energy to creativity and strategic decision-making, ensuring campaigns are innovative, impactful, and aligned with brand objectives as we move into 2025.
In short, AI is not just a trend but a transformative force for marketing procurement, enabling smarter, faster, and more sustainable operations across categories. As these technologies evolve, their role in shaping efficient and creative supply chains for brands will only grow.
From risk and resilience, to AI and sustainability, supply chain industry experts weigh in on the biggest trends set to shape the future of the sector in 2025.
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The past 12 months have been a challenging time for the world’s supply chains. 2024 was shaped by geopolitical conflict, pivotal elections in the majority of the world’s largest nations, worsening symptoms of climate collapse, and the ever-changing conversation surrounding technology’s role in day to day life. If there’s one thing that’s remained consistent and predictable over the course of the past year, it’s a marked trend in chaotic, inconsistent, disruptive conditions throughout global supply chains.
Throughout this year and now, going into 2025, supply chain leaders have responded to these challenges — exploring new ways to unlock resilience while containing costs, embracing new technologies while remaining cyber secure, and walking the increasingly narrow line between failure and success that the supply chain industry is forced to tread. As the year draws to a close, we spoke to 10 experts from organisations throughout the supply chain sector, from technology vendors to logistics analysts, to find out what the supply chain industry’s leaders expect from the next 12 months (and beyond).
“There are a few key strategies that distributors will need to focus on in the face of supply chain disruptions and inflationary pressures as we move toward 2025. First, it’s important to recognise the significant demand for products from the UK to Europe and beyond, which presents both opportunities and challenges. Managing this effectively hinges on one crucial asset: inventory.
“Visibility and control are key. Distributors must optimise their ability to monitor stock — they need to be able to ensure that they have the right amount of product in the right areas to meet customer demand. Technology will be a major enabler in this, providing faster insights and helping to optimise decision-making processes. Distributors will need systems that allow them to act quickly, repositioning inventory closer to customers to reduce costs and improve delivery times.
“AI will play a big role in helping distributors manage this. By analysing vast amounts of data — whether it’s from different distribution partners, product types, or warehouse locations — AI can provide insights that allow distributors to make more informed decisions on where to position stock for optimal efficiency. This will help with cost management and also enable faster, more agile responses to customer demands.”
… Supply chain strategies and business strategies will become increasingly intertwined.
“Before the pandemic, the planning and execution of a company’s supply chain strategy resided with only a few technically minded specialists. Next year, however, supply chain strategy will become even more intertwined with wider business strategies that centre around cutting costs, creating competitive differentiation and ensuring excellent customer service and delivery experiences.
“Currently, supply chain and logistics costs account for 10% of an organisation’s overall spend. However, ongoing economic uncertainty will put supply chain efficiency high on the priority list for executive teams looking to cut costs. You can’t streamline what you can’t measure, so gaining end-to-end visibility of supply chain operations will be essential to identify areas to automate and minimise excess spending while enabling staff to focus on higher-value tasks. At the same time, this level of visibility will be important to compliance teams within large organisations that are faced with increased pressure to report on Scope 3 emissions reductions.
“Meanwhile, customer service teams will become more involved, with the last mile of the supply chain having the potential to make or break customer loyalty. Here, new technologies to enhance supply chain visibility and provide real-time order intelligence will be invaluable to communicate with customers, particularly when it comes to unprecedented delays. Next year, digital tools that promote visibility and collaboration will be key to breaking down internal siloes and ensuring greater alignment.’
Tariffs and geopolitical unrest will see new sourcing hubs appear across Asia and beyond – Alex Saric, Smart Procurement Expert at Ivalua
“In 2025, we’re likely to see sourcing hubs appear in new areas across Asia and Eastern Europe – with the US, EU, and the UK continuing to impose tariffs against suppliers in countries like China and Russia. New supply chains will be created in areas close to tariffed nations, as organizations find new ways to buy critical materials or components while sidestepping eye-watering tariffs. This will be particularly important for industries impacted by shortages like raw materials, fuel, and semiconductors.
“For example, the Taiwanese chipmaker TSMC has already agreed to build a third factory in Arizona, while U.S. chipmaker Onsemi has invested $2Bn to set up a full semiconductor production chain in the Czech town of Roznov pod Radhostem. We will likely see more of this type of investment over the next 12 months.
“It will take time and investment to shift operations fully, but organizations will need to bolster their supplier visibility to identify new sourcing hubs and gain access to the products they need at a lower price.”
“In 2025, Generative AI (GenAI) will tackle the procurement and supply chain industry’s AI skills gap by becoming more autonomous and user-friendly. Despite plenty of experimenting taking place since 2023, many teams have not integrated GenAI into their day-to-day workflows. But, as semantic data retrieval, AI orchestration, and LLM technologies advances, Generative AI systems are becoming more intelligent and more autonomous. Next year, we will see the emergence of AI agents that are capable of understanding high-level directives and act autonomously on specific events, evaluate options, make decisions, and generate detailed analytics, forecasts, and recommendations. Procurement and supply chain professionals will be able to interact with those AI-powered assistants by simply describing their needs in natural language, without having to master complex prompt engineering or coding skills. This will dramatically lower the barrier to entry for using – and benefitting from – AI.”
“With more users across the business, GenAI will become the de facto corporate ‘business operating system’, fundamentally reshaping the user experience. Rather than being simple “one-and-done” features sprinkled across the spend management suite, assistants will act as a central interface or in the background, seamlessly integrating data sources, decision-making models, and workflow automations into one unified space. As a result, AI will dynamically adapt to support everything from procurement to demand forecasting, helping teams to focus on more high-value tasks and adding strategic value.”
… Retailers will focus on nearshoring and resilience.
“Supply chain disruptions have been a cold shower for retailers this year. From the Red Sea crisis to the recent US port strikes, these events have been a shock to the system. Retailers didn’t realise how big of an impact it could have on their operations. They’ve been bitten, and now they’re shy. As a result, CFOs will be nervous about over-exposing themselves.
It’s cognizant of when COVID-19 hit. Initially, we experienced a massive shortage of products. Then, supply chains opened up and people over-ordered and overstocked. A lot of brands fell by the wayside as they overspent on purchasing products they couldn’t turn into revenue. It’s a balance between feast and famine – one that retailers will be paying closer attention to in the coming year.
Learning from these events, retailers will change the way they source goods. More near-shore supply chains could emerge as companies look to reduce reliance on the Far East. The introduction of export taxes in the US may also have a significant impact on overseas trade, possibly leading to shifts in market strategies for European brands as they reconsider their expansion plans.
Retailers will also be looking closer at how they orchestrate and manage their inventory to ensure they can fulfil the customer promise. With real-time inventory data that shows what stock is available now and in back order transit, retailers can know for certain what they can promise to their consumers – and provide timely updates if disruptions occur.”
… Supply chains will enter a new age of efficiency.
2025 will be the year of supply chain efficiency. With the explosion of Generative AI in 2024, excitement will begin to settle in the New Year. The focus will shift; emphasis will be less about the expectation of it doing ‘everything’ within the supply chain, and more about its practical use.
This means supply chain staff will see the true value in AI’s breakdown of data, automation of some manual tasks, and the ability to ask questions about next steps. In the coming year, GenAI’s role will be focused on helping supply chains optimise efficiency and output within its strongest capabilities.
Production planners, too, will see their roles change in 2025. With AI continuing to reshape the role, it is vital production planners are AI-literate, particularly as tech’s importance will grow. With less supply chain staff in the industry, leaning on tech is going to be more important than ever and production planners must embrace AI as a supporting tool in the workplace. Those who don’t risk being left behind. There may be less resources at hand, but AI will guarantee stronger outcomes.
On top of this, there’s a misconception around AI that production planners need an extremely granular focus when it comes to planning, but this can actually hold you back. Higher level planning is much more effective, especially as it prioritises flexibility and the ability to be as agile as possible in the face of global issues.
… Regulation has a role to play in maintaining supply chain resilience.
“Today’s supply chains remain volatile. From the ongoing Red Sea crisis, US port strikes, rising inflation and new global pandemic health emergencies, businesses are under immense pressure to identify and manage systemic risks in supply chains.
However, there is an answer and a way in which the Government can build a secure supply of critical goods, mitigate risks within the global trading environment, and support businesses with supply-chain resiliency. Introducing a government-mandated electronic supply chain trading network with end-to-end visibility would aid organisations with insights to see, understand, act, and learn from real-time information from the entire digital ecosystem. This should be based on an AI-powered unified platform that enables multi-tier orchestration, planning, and collaboration to accelerate processes with autonomous and semi-autonomous decision-making.
Think of it this way: just as services such as electricity and broadband are provided via government-mandated markets, creating an engine for supply chain planning could also be provided via a government-rolled-out network. If all trading partners in a supply chain can derive confidence in each other from having confidential electronic visibility of forecasts, inventory, shipments and invoices they will reduce lead times and excess inventory which releases working capital.
It is time to take control of the systematic risks in our supply chains with one unified global supply chain operating system – unlocking the barriers essential for delivering long-term, sustainable, inclusive, and resilient growth.”
… Supply chains will need to carefully navigate regulatory changes.
“Next year will be impacted by the European Commission’s recent decision to delay the EU Deforestation Regulation (EUDR), giving businesses across the supply chain the new deadline of compliance by December 30, 2025. Looking forward to 2025, affected businesses, including our own, will be refining preparations, to ensure readiness to comply with the legislation.
“While the EUDR is well-intentioned, it has faced considerable challenges. Developing nations have raised valid concerns about the intense compliance requirements and the investment needed from some of the world’s poorest farmers. Additionally, major economies like the US and China have expressed reservations, complicating traceability efforts for commodities.
“This next year will be crucial for us all. It will allow us to thoroughly assess our supply chains, engage with our partners, clients, and suppliers to understand how we can work together to satisfy legislative requirements. A significant part of this effort will involve evaluating the systems we use and what we need to provide along the value chain to ensure compliance across all stakeholders. It’s also an opportunity to explore, in even greater depth, innovative technologies such as AI and blockchain to help meet these requirements effectively.”
… Cyber security will be more important than ever.
“As we look toward 2025, it is more crucial than ever to remember the importance of securing our supply chains against the ever-growing threat of cyber attacks and the harm these can cause.
“With increasing interconnectivity and supply chain complexity, breaches in one part of the ecosystem can quickly ripple through to other areas, making collective defence strategies more vital than ever to maintain business resilience. Organisations must stay vigilant and acknowledge the need to assess, monitor, and review their own cybersecurity practices as well as those of their third-party vendors. This shift will likely push companies to not only improve their own security postures but also to collaborate more effectively across industries.
“The coming year is set to be significantly influenced by regulatory frameworks like the EU’s Digital Operational Resilience Act (DORA) and the Network and Information Systems Directive 2 (NIS2). These regulations are already shaping the landscape by imposing stringent requirements on organisations to secure their supply chains and critical infrastructures, particularly in sectors such as finance and essential services. In the coming years, it is likely that such regulations will expand to encompass more industries, creating a uniform standard for operational resilience and cybersecurity risk management across the board.
… AI and RFID will be technological cornerstones of the supply chain.
“As supply chain requirements evolve and businesses are presented with new challenges, the role of innovative technologies such as AI and RFID will become more important in 2025. Omnichannel retail has already taken retail by storm, and the supply chain industry acts as the foundation to any omnichannel success, where businesses need increased accuracy, visibility, and transparency of their supply chains.”
“Solutions powered by AI and RFID are likely to remain in demand in 2025, solving supply chain challenges for businesses. The integration of AI into operations is expected to become more common as supply chain operators strive to gain higher precision and improve predictive analytics.”
… The retail supply chain will move beyond logistics.
“In 2025, the retail supply chain will redefine itself as more than just a logistics process, it will be a strategic driver of customer loyalty. As competition tightens, Artificial Intelligence (AI) and data analytics will take centre stage, and supply chains will shift from multiple experimental investments to larger scale transformative tech solutions that deliver tangible ROI and impact the bottom line. This means no more AI for AI’s sake and retailers will double down on solutions that directly impact sales and optimise store operations.
“One way we’ll see this step change come to fruition is the implementation of high-value product vending machines. In this system, instead of high-value and/or rarely purchased stock occupying shelf space, customers take a ticket for the product and retrieve the item at the checkout. This innovation not only frees up in-store real estate for more products but also mitigates theft and ensures consistency of product availability across locations—key to maintaining customer loyalty.”
As part of our ASCM CONNECT coverage, we speak to Velosio Consulting Manager Amir Hemani about helping the supply chain sector embrace digitalisation.
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This year at ASCM CONNECT, we caught up with some of the supply chain sector’s leading executives to learn more about them, their analysis of the trends shaping the industry, and how their organisations are responding to the challenges ahead. Amir Hemani is a Consulting Manager in Velosio with 15+ years of experience in business applications. Velosio specialises in Microsoft cloud ERP and CRM solutions, as well as productivity and analytics tools like Microsoft 365, Power Apps, Power Automate, Power BI, and Power Virtual Agents. Velosio comprises more than 400 members and supports over 4,000 clients in their digital transformation initiatives.
What are your biggest takeaways from this year’s ASCM CONNECT and how they relate to the broader supply chain landscape?
The focus on digital transformation and sustainability, as well as the practical case studies on how companies are leveraging AI and latest trends to solve complex supply chain problems.
The supply chain space is in a state of transformation, adapting to new disruptions and leveraging technology to build resilience. Flexibility and innovation are now core to modern supply chains. Supply chains have learned the importance of flexibility, resilience, and digital adoption. Companies that invested in these areas were better prepared for black swan events, and modern supply chains are now more agile and capable of handling future disruptions.
Sustainability is also increasingly non-negotiable. Companies face pressures from both regulators and consumers to adopt sustainable practices, and ignoring this can lead to reputational damage and regulatory penalties.
Where are generative AI and data analytics having the biggest impact in the supply chain?
Generative AI helps in demand forecasting, procurement optimization, and risk management. It enables faster decision-making by analysing vast data sets in real time, something that was far more manual just a few years ago.
Of course, data security and trust in AI-generated outcomes are common concerns. Companies need to choose platforms that prioritise data governance and transparency to address these issues. Many companies have siloed and unstructured data, making it hard to gain actionable insights. Generative AI and knowledge graphs can organise and structure this data, providing a more holistic view of the supply chain.
How do you approach change management and get people on board with innovation?
Effective change management and continuous training are key. Involving employees early in the transformation process and demonstrating how technology can improve their work leads to better adoption.
Promoting the dynamic and tech-driven nature of modern supply chains is crucial. Offering mentorship, flexible career paths, and emphasising the impact supply chains have on global issues will attract younger talent.
What strategies can be implemented to support the supply chain sector going forward?
Embracing advanced technologies like AI, and IoT, while also promoting collaboration across the supply chain ecosystem, will drive the next wave of innovation and efficiency.
As part of our LogiPharma coverage, we speak to pharma supply chain expert Sankalp Raviprolu of ZS about the industry’s most pressing challenges.
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At this year’s LogiPharma 2024 event, we caught up with some of the pharmaceutical supply chain sector’s leading executives to learn more about them, their analysis of the trends shaping the industry, and how their organisations are responding to the challenges ahead.
Sankalp Raviprolu is an experienced supply chain advisor who works closely with clients to drive operational excellence, build differentiated digital capabilities, and enhance supply chain strategies across manufacturers, wholesale distributors, and retailers. At this year’s event, we spoke to him about the pain points facing the industry and how he leverages his expertise in technology, advanced data science, and AI to achieve his goals.
ZS is a management consulting and technology firm that partners with companies to improve life and how we live it. ZS’s supply chain and manufacturing team has deep domain and industry expertise. They help their clients optimise planning and operations, design agile and resilient supply chains, achieve supply chain visibility and digitise manufacturing using data, analytics and technology.
Inside LogiPharma 2024
1. What is the value of events like LogiPharma 2024? How important is this conference in the supply chain pharma calendar?
Events like LogiPharma provide industry practitioners, academics, and thought leaders a forum to collaborate, share perspectives, and learn best practices in a dynamic setting.
These events create a unique opportunity for logistics solution providers, technology partners, and product companies to demonstrate their latest innovations to a relevant and engaged audience within the pharma logistics industry. The opportunity to network and form partnerships is invaluable in solving some of the industry’s biggest challenges.
2. What are the biggest takeaways from this year’s LogiPharma for you?
The pharmaceutical logistics industry is evolving rapidly. If there was ever a time to embrace data, technology, and strategic partnerships, it’s now. We’re seeing a meteoric rise of new modalities such as cell and gene therapies and radiopharma therapies. In this new context, supply chain operations must become even more adept and agile.
End-to-end visibility solutions are moving from descriptive and predictive models towards prescriptive and autonomous supply chain solutions. Track-and-trace devices, temperature monitoring sensors, advanced data platforms, and robust partner ecosystem—including 3PLs and logistic providers—are pivotal in achieving supply chain excellence from raw material at source to the point of care for the patient. Carbon emission tracking, network orchestration, and n-tier supplier visibility are no longer “nice-to-haves” but essential elements in identifying and addressing the weakest links in supply chains before they become larger disruptions.
The global supply chain
3. How would you sum up where the pharma supply chain space finds itself today?
The pharmaceutical supply chain has experienced significant challenges in recent years including supply shortages, volatile demand, and geopolitical shifts. The industry now faces a more complex landscape with an increasing number of modalities across biologics, small molecules, and advanced therapies lined up. To navigate this environment, supply chains must ensure that the right product is delivered at the right time, at the right quality, and to the right patient—every single time.
The Drug Supply Chain Security Act (DSCSA) is a major milestone in establishing traceability and accountability within the pharma value chain, enhancing transparency across various parties involved.
4. What do you feel are the biggest lessons supply chains have learnt over the past few years and how well equipped is the modern-day supply chain now to deal with ‘black swan’ events like the ones we’ve seen recently?
The key lesson is that there is no one-size-fits-all approach to supply chain management. Each supply chain is unique and the metrics we use to measure, monitor, and react must evolve with patient needs and product complexities. Organisations must prioritise flexibility and resilience, recognizing that the frameworks they use today may need to be rapidly adapted tomorrow.
During the pandemic, for example, companies that had already invested in advanced scenario planning and predictive analytics capabilities were able to adjust more quickly to sudden changes in demand and supply chain disruptions compared to those that relied on traditional models.
Sustainability in the pharma supply chain
5. Sustainability is an important item on most Chief Supply Chain Officers’ agenda. Amid government legislation and changing customer demands, is a sustainable supply chain a non-negotiable in today’s world?
Sustainability is no longer just a corporate initiative; it is a non-negotiable requirement for Chief Supply Chain Officers (CSCOs). Sustainability is intertwined with every decision made throughout the supply chain, from sourcing raw materials to carriers delivering products to patients. Governments and consumers are increasing pressure on companies to demonstrate sustainable practices and failing to do so not only risks reputational damage, but can also impact compliance and operational efficiency.
Driving digital transformation
6. How are you navigating the world of generative AI?
Generative AI is revolutionising logistics and supply chain operations by transforming how we interact with data and how we work every day.
It enables faster decision-making through synthesising vast sets of data both structured and unstructured, thus allowing companies to anticipate disruptions and optimise their supply chains in near real-time. AI can also facilitate personalised supply chain strategies, adapting to the unique needs of different therapeutic areas and modalities.
For instance, supplt chain managers are using AI-driven models to optimise cold chain logistics for temperature-sensitive therapies. This ensures the integrity of products from the point of manufacturing to the patient point of care.
7. What should CSCOs consider before starting the gen AI journey?
The first step for CSCOs is to identify and prioritise specific business cases that can benefit from generative AI.
There is a lot of hype surrounding AI. However, organisations should adopt a structured, value-driven approach to separate reality from the hype. Experimenting with pilot projects, learning quickly from failures, and scaling successful initiatives is the best way to ensure AI adoption yields measurable outcomes. It’s essential to focus on the problem AI is solving rather than implementing technology for technology’s sake.
8. What are the biggest challenges or hesitations you’re seeing companies have around AI? What should organisations look for in technology to hedge against these concerns?
One of the biggest challenges companies face when adopting AI is trust in the data. AI models are only as good as the data designers use to train them. As a result, many organisations struggle with fragmented, incomplete, or inaccurate data.
Additionally, concerns about the ethical use of AI and transparency in decision-making are common. To overcome these challenges, companies should invest in robust data governance frameworks and ensure that AI tools are designed to be explainable and accountable. Finally, AI adoption in the context of pharma and controlled environments also comes with some nuances. These require careful consideration and navigation in GxP environments.
The future of the pharma supply chain
9. How exciting a future does the pharmaceutical supply chain have?
There is no better time than now to be involved in the pharmaceutical supply chain. With years of digitization across core capabilities and transactional systems, organisations are now poised to leverage their digital assets (data) to turbocharge their supply chains to build agility, anti-fragility and resilience.
By embracing predictive insights and data-driven decision intelligence platforms, supply chains can become a true competitive advantage. They can enable faster, more efficient operations that deliver value to patients and the business alike.
We catch up with Anna Tinnin, Director of Strategic Accounts at GeakMinds, to get her take on the supply chain sector’s use of technology to circumvent disruption.
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From extreme weather events to political tensions, the world is becoming an increasingly unpredictable place. For supply chain teams, finding ways to combat the uncertainties of the modern supply chain is critical. Geakminds is a business consulting firm that focuses on using advanced analytics to help businesses make data driven decisions.
Recently, we caught up with their Director of Strategic Accounts, Anna Tinnin, to get her take on the challenges and opportunities facing the supply chain space, as well as how a data driven approach can help supply chain managers unlock the resilience and agility they need.
1. How well suited is the modern day supply chain to deal with ‘black swan’ events like the ones we’ve seen recently?
In recent years, supply chains have learned to prioritise resilience over efficiency by diversifying suppliers and increasing inventory.
There’s been a strong shift towards real time visibility using technologies like IoT and blockchain to better respond to disruptions. Accelerated digital transformation, including AI and automation, has become crucial for enhancing agility and predictive capabilities.
Companies are now more mindful of geopolitical and environmental risks when selecting suppliers and recognise the importance of strong collaboration with suppliers for effective crisis management.
While modern supply chains are better equipped with improved risk management, technology, and contingency plans, they still face vulnerabilities due to their complexity, making ongoing investment in resilience and flexibility essential to prepare for future ‘black swan’ events.
2. What types of supply chain and procurement decisions are now possible, or much easier to make, with the rise of AI and LLMs? And how quickly are things changing?
Generative and conversational AI are revolutionising supply chains by enhancing demand forecasting, inventory management, supplier risk assessment, procurement optimisation, logistics, and communication.
AI driven models now provide more accurate demand forecasts by analysing vast amounts of data, including unstructured sources like news and social media, allowing companies to optimise inventory levels. Supplier risk management has become more proactive, with AI enabling real time risk monitoring by analysing diverse data sources. In procurement, AI automates and optimises processes by analysing purchasing data, market prices, and supplier performance, making strategic sourcing decisions faster and more accurate.
Logistics and route optimization have also improved, with AI algorithms dynamically adjusting routes based on real time conditions, significantly boosting efficiency. Conversational AI, such as chatbots, streamlines supplier and customer interactions, handling complex queries and reducing the need for human intervention.
Compared to a few years ago, AI and large language models have transformed supply chain and procurement decisions, making them faster, more data driven, and predictive, leading to more resilient and responsive supply chains.
3. What are the biggest challenges you’re seeing companies have around AI? What should organisations look for in technology to hedge against these concerns?
Companies face several challenges with AI adoption, including issues with data quality, lack of expertise, ethical concerns, cost and ROI uncertainty, integration difficulties, and security risks. Poor data management can hinder AI effectiveness, so investing in systems that ensure clean, integrated data is crucial.
The need for specialised skills is also a barrier, making user friendly AI platforms and expert partnerships valuable. Ethical concerns, such as bias and transparency, require companies to prioritise AI solutions with bias detection and ethical practices. High costs and unclear ROI cause hesitation, so starting with small, measurable projects and choosing solutions that are easier to scale is a better way to go about the process. Integration with legacy systems can be challenging, so opting for AI technologies that are compatible and easy to integrate is essential.
Finally, AI raises data security and privacy concerns, making it important to select tools with robust security features and regulatory compliance. By focusing on flexibility, ethical AI practices, ease of use, and security, companies can adopt AI more confidently and effectively.
4. People are a business’ greatest asset but can also be a hurdle to overcome when it comes to innovation. How do you manage change and create buy in when approaching innovation?
Getting employees on board with innovation requires a strategic approach. Start by clearly communicating the vision behind the change, explaining not just what is changing but why it’s important for the company’s future and how it benefits them personally.
Involve employees early in the process to build ownership and reduce resistance, and provide the right training and support to help them feel confident with new skills. Address concerns transparently to build trust, and highlight quick wins to demonstrate the benefits of innovation. Fostering a culture of innovation, recognising and rewarding innovative behaviour, and leveraging key influencers within the organisation can further support the change effort.
Ongoing communication and feedback, combined with empathy and patience, help ease the transition, while linking the change to personal and professional growth opportunities ensures that employees see the value in embracing innovation.
5. How can the supply chain industry take that next step and what strategies can be put into place to push the industry forward even further?
To advance the supply chain industry, companies need to embrace several key strategies. Adopting advanced technologies such as AI, machine learning, blockchain, and IoT can significantly enhance visibility, efficiency, and decision making. Leveraging big data and analytics allows for deeper insights into operations and predictive analytics.
Focusing on sustainability by implementing environmentally responsible practices and optimising resource use is crucial for meeting regulatory requirements and reducing impact. Improving collaboration with suppliers and partners through shared platforms and real time communication can lead to more synchronised supply chains.
Utilising digital twins for real time monitoring and scenario simulation can optimise operations without disrupting the actual supply chain. Investing in workforce development ensures employees can effectively use new technologies, while robust cybersecurity measures protect data and systems from threats. Integrating automation technologies like robotics and automated storage systems enhances efficiency and reduces errors.
Adopting agile practices enables greater flexibility and responsiveness to changes, and staying informed about emerging trends such as 3D printing, autonomous vehicles, and drone delivery can offer new opportunities for transformation. By implementing these strategies, the supply chain industry can achieve greater efficiency, resilience, and sustainability, positioning itself to better navigate future challenges and opportunities.
James Fisher, Chief Strategy Officer at Qlik, explores the potential for AI to help mitigate disruptions caused by the climate crisis.
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Consumers today expect online deliveries to arrive in two days or less – especially when buying from suppliers like Amazon. In fact, research this year found that 80% of organisations reported higher customer satisfaction levels, and 70% experienced higher sales, when able to offer same-day delivery. But climate disasters and severe weather conditions, which are unfortunately becoming increasingly prevalent as we battle with climate change, pose a significant challenge for shipping and logistics companies to meet customer expectations.
While we can’t put an immediate stop to severe weather conditions, we can take steps to help minimise disruption and support the shipping and logistics industry to keep customers happy and business profitable. It all comes down to predictive analytics and automation.
Traditional ML models can’t handle today’s climate impact
Traditional machine learning models learn from existing data, and map potential outcomes based on this information. But when it comes to the type of climate impacts we are facing today, we cannot just rely on replicating previous scenarios. Past data doesn’t accommodate for all the new possibilities that could, and are more likely, to happen in the future.
Temperatures are changing, and ‘freak’ weather events are happening more than ever before. The Covid-19 pandemic offers a good parallel to this. Its impact on the modern world was unlike any health crisis previously. Therefore, using past information was not useful to map its potential trajectory to determine how to react.
When facing net-new challenges, we can’t look backwards.
The role of real-time data and automation
To navigate new or unexpected challenges, like emerging climate disasters, we need other ways to remain operational and meet customer needs. This is where real-time data and generative AI becomes vital.
With access to real-time data, like emerging weather or traffic conditions, logistics, shipping and retail businesses can build more resilient operations.
If you can apply AI to model and predict how a scenario may play out based on information that is correct up to the minute, you can make well-informed decisions that reflect the exact scenario you face. This could be changing delivery routes, shipping products from a different warehouse in an unaffected area, or even just having information early enough to let customers know ahead of time that their delivery will be delayed. Combine that with automation and AI powered agents and we can give customers warning about possible delays and offer alternatives, all can help to improve their overall experience..
Putting predictive analytics into practice
One example of how AI and predictive analytics is helping to manage supply chains and minimise disruption is Penske, the company which operates and maintains more than 422,000 logistics vehicles across the USA and Canada.
Penske worked with Qlik to develop Fleet Portal. Fleet Portal provides information and analytics related to a vehicle’s operation, as well as how it is used and maintained in near-real time. The company is also implementing AI to reduce repair time for vehicles, and in some cases, predict maintenance events before they become a problem, helping to reduce any potential delays or disruptions from broken down vehicles.
It’s clear to see how this type of sophisticated real-time data insight can help react to everything from adverse weather conditions to real climate crises like wildfires or hurricanes.
Unfortunately, today we face many climate challenges and severe weather conditions. There is a lot of pressure on logistics and shipping companies to meet customer expectations and drive business success, even in the face of these obstacles.
Understanding and harnessing data in the correct way means businesses will be better equipped to predict the potential impact of climate events in as near to real-time as possible, thus mitigating business disruption and, critically, keeping loyal and new customers happy.
Scott Robertson, Co-Founder of HaulageHub, takes a look at the role of AI in the UK freight sector’s green ambitions.
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The UK’s haulage industry is a cornerstone of the supply chain, playing a crucial role across sectors from retail to manufacturing. Responsible for transporting 89% of all goods by land, the industry employs hundreds of thousands of people and remains vital to the UK economy. However, it faces significant challenges, particularly in addressing inefficiencies such as empty runs—when Heavy Goods Vehicles (HGVs) travel without cargo. Empty runs currently account for over 30% of all HGV miles in the UK, contributing to increased operational costs and more than five million tonnes of unnecessary CO2 emissions annually.
These inefficiencies, combined with rising fuel costs and increased interest rates, have placed immense pressure on haulage companies, many of which have struggled to stay afloat over the past year. In response, the industry is turning towards technology, especially artificial intelligence (AI), to streamline operations and promote sustainability.
AI: A Game-Changer for Efficiency and Sustainability
AI models have emerged as a promising solution to some of the longstanding issues in the haulage industry. By analysing data and making real-time decisions, AI has the potential to reduce inefficiencies, cut costs, and lower the environmental impact of logistics operations.
A digital freight marketplace, like that developed by HaulageHub, is an example of how AI is being used to transform how shippers and hauliers connect. This platform utilises AI to match loads with hauliers, particularly those with routes that would otherwise run empty. This not only maximises the use of available capacity but also reduces the number of empty miles travelled, thus cutting fuel consumption and emissions.
By continuously analysing traffic conditions, vehicle availability, and other real-time factors, AI systems can optimise routes, improve load distribution, and predict vehicle maintenance needs. This ensures trucks are operating at peak efficiency, reducing both fuel use and downtime. Moreover, platforms equipped with AI capabilities can provide detailed emissions data, allowing businesses to track and reduce their carbon footprint, which is increasingly important as the logistics industry looks to improve sustainability.
A Data-Driven Approach to Reducing Emissions
The use of AI in the haulage sector is already delivering tangible results. For instance, HaulageHub has successfully reduced the average rate of empty runs from 33% to 19%, a significant improvement that translates into both cost savings and a reduction in CO2 emissions. This highlights the broader potential for AI to create a more sustainable future for the industry as a whole.
In addition to optimising operations, AI systems also offer flexibility for hauliers of all sizes. Small-scale shippers, as well as large corporate entities, can benefit from enhanced operational efficiency, while also gaining access to tools for managing subcontracting volumes. As technology evolves, further integration of AI in logistics could revolutionise how the industry operates, from route planning to vehicle management.
The Future of AI in Freight: Beyond Efficiency
Looking to the future, the haulage industry is poised for even greater transformation. AI is not just improving operational efficiency but also opening the door to innovations such as autonomous trucks, advanced telematics, and the integration of electric and hydrogen-powered vehicles. These developments will be key to reducing the sector’s environmental impact and moving towards a zero-emission future.
Companies like HaulageHub, with a focus on AI-driven solutions, are at the forefront of these changes. Their plans for a Transport Management System in a SaaS format and expansion into telematics and tachograph management illustrate how AI can be leveraged to improve transparency and efficiency in logistics. By exploring the use of electric and hydrogen powered vehicles, the industry can further reduce its reliance on fossil fuels and accelerate the shift towards more sustainable freight transport.
The integration of AI in the UK’s freight industry is not just about addressing inefficiencies; it’s about driving the sector towards a more sustainable future. As the industry faces increasing economic pressures and growing environmental concerns, AI offers a pathway to greater efficiency, reduced emissions, and improved profitability. By embracing these innovations, the UK’s haulage industry can stay competitive and resilient, ensuring its continued role in supporting the economy while minimising its environmental impact.
Philip van der Wilt, SVP and GM EMEA at Samsara, explores the role of AI in transforming the logistics space.
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When it comes to using artificial intelligence (AI) in road transport, it no longer falls into the category of “too new to try”. Instead, it is a market-tested technology that is driving results across the supply chain, particularly the logistics sector.
In fact, advancements in AI have ushered in a new era of transformative technology, as well as speculation about how it will revolutionise the world — not least in the world of transport and logistics.
While AI’s potential might not be immediately obvious to everyone, its impact in this sector is already profound. From enhancing safety to reducing costs, AI is driving significant improvements across the board and streamlining workflows for fleet managers and drivers alike.
Driving safety forward
AI’s integration into existing technologies opens the door for significant improvements in driver safety, and dashcams are an excellent example of this. When enhanced with AI, dashcams can monitor driver behaviour in real-time, helping to prevent incidents and save lives.
For instance, AI can detect distractions such as a driver picking up their phone or signs of fatigue, automatically issuing alerts that prompt drivers to refocus or take necessary breaks. These interventions go beyond passive observation and instead, actively contribute to preventing accidents.
Wholesale food distribution giant, Sysco, reported significant results since implementing Samsara’s AI safety system, including a 40% decrease in on-road accidents within just three months. In addition, it also witnessed a 17% reduction in harsh driving events and a 15% reduction in insured costs year-on-year – and they’re not alone.
M Group Services, which equipped over 8,500 of its vehicles with dual-facing AI dashcams, saw an almost 30% reduction in incidents per million miles.
AI is facilitating never-before-seen levels of safety, and its potential for growth in this area is exponential. As more businesses integrate these technologies into their logistics functions, our roads will become safer, meaning that all drivers will reap the benefits of this new standard of road safety.
Returns on AI investment
Not only does AI save lives, it also helps to mitigate risk and reduce costs. By minimising accidents and monitoring driving behaviours, AI can save businesses money in terms of repairs, replacing damaged vehicles and hefty insurance premiums.
Moreover, by crunching much larger amounts of data than humans can, AI can spot anomalies such as excessive fuel use among particular drivers, vehicles, or routes, and identify changes that can lead to greater efficiency.
Beyond cutting costs out on the roads, AI is saving time and money in the back offices too. By automating workflows and removing the need for human intervention on more menial, time-consuming tasks, AI has become a real game changer for an industry where many are often still reliant on manual, pen-and-paper based processes.
Another impactful application of AI is predictive maintenance. By using real-time data and performance history, AI allows businesses to forecast when a vehicle is likely to need maintenance. As a result, fleet managers can get the most value for their money as AI allows them to carry out maintenance exactly when needed.
A glimpse into the future
The benefits of AI are constantly evolving and embracing this technology early on will provide significant long-term benefits to businesses. In the next five years, AI is poised to seamlessly connect all parts of the supply chain, as fleet leaders increasingly turn to AI not only to cut costs and improve safety in logistics, but ultimately to remain competitive.
Samsara’s new State of Connected Operations report found that, of the 1,500 operations leaders surveyed, more than half (51%) reported that their organisation is already using AI in some capacity. Of those leaders, 90% also said that their employees feel positive about the technology. While this is a promising start, there’s still a great deal of progress to be made to ensure fleet organisations are fully realising AI’s potential across all operations.
Trust and AI
However, with so much happening at pace, it’s crucial to make the right preparations and to stay focused on deploying AI responsibly. Issues such as privacy, data quality, and data protection are all potential obstacles to the implementation of AI, which could undermine trust if left unaddressed.
In fact, the top three barriers to implementing AI technology solutions are data quality and availability (41%), privacy and security concerns (40%) and integration with existing infrastructure (39%).
Of those already using AI, our research shows that the majority report that their organisation is currently deploying privacy and data protection measures (58%), establishing AI ethics and principles (57%) and making efforts to mitigate bias in AI (54%).
These priorities indicate that organisations are taking a measured and thoughtful approach to AI implementation, focusing on addressing legal and ethical risk before tackling logistics and rollout.
Data fuels AI
Ultimately, one thing has to be understood from the outset: AI is fuelled by data. The better the data, the better the outcomes. So investing in AI also means fleets also need to invest in digital management platforms capable of providing accurate real-time data.
For those already on the digital transformation journey, AI is opening up a world of possibilities. For those yet to start, AI will increasingly be built into applications as standard.
Jason Davis and Jason Payton, both partners at ScottMadden, discuss how supply chain leaders should lean into digital transformation, resilience, and sustainability.
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As a general management consultancy, ScottMadden seeks to provide high-quality, objective advice and support to help clients solve challenging problems. The company is renowned for the quality of its services, as well as the integrity of its relationships.
To ScottMadden, clients are at the heart of its strategy. In supply chain, the team simplifies enterprise strategy for supply chain management while identifying opportunities to reduce costs through improved category and inventory management. A recent project that showcases ScottMadden’s supply chain intent was its work with a large, midwestern investor-owned utility needed to improve its supply chain organisation’s strategy, governance, and operations.
ScottMadden
It was revealed that costs were high and the organisation could not provide the strategic direction needed for efficient planning, sourcing, and materials management across the company. This is where ScottMadden came in. ScottMadden were engaged to help articulate one clear enterprise strategy for supply chain management which senior executives could support, drive, and monitor.
Given the disruption that recent global events have caused, it has become clearer than ever before how easily supply chains can be disrupted. Through ScottMadden’s five-step approach, they can partner with companies to develop a supply chain business intelligence tool to ensure its customers have the data-driven insights needed to safeguard their supply chain.
Amidst ASCM CONNECT 2024, ScottMadden partners Jason Davis and Jason Payton reveal ScottMadden’s approach to supply chain management in the middle of technological change and digital disruption.
Would you be able to give me a brief introduction to your role and the company you work for?
ScottMadden: “We are partners with ScottMadden, a general management consulting firm with over 40 years of experience. ScottMadden delivers a broad array of consulting services ranging from strategic planning through implementation across many industries, business units, and functions. In supply chain, we have assisted our clients with improving their operating models and transforming functions in procurement, materials management, and logistics.”
Jason Payton
ASCM CONNECT 2024
What is the value of events like ASCM CONNECT 2024: North America? How important is this conference in the supply chain calendar?
ScottMadden: “ASCM CONNECT provides a valuable forum for supply chain professionals to gather and discuss challenges and solutions. One of the many benefits is the ability to learn from organisations and solution providers of all sizes and focus areas. For ScottMadden, ASCM CONNECT is a very important event and will continue to be a focus for us in the future.”
Global supply chain
Given the backdrop of the global disruption over the past few years (COVID, wars, inflation etc.), how would you sum up where the supply chain space finds itself today?
ScottMadden: “It’s well documented that today’s supply chain landscape is marked by increased complexity and uncertainty. The COVID-19 pandemic disrupted global supply chains, revealing vulnerabilities in just-in-time inventory models and overreliance on single-source suppliers, particularly in critical industries like healthcare and technology. Geopolitical tensions, such as wars and trade disputes, exacerbated these disruptions, leading to increased protectionism and the reshoring of some manufacturing activities.
“Inflation and price volatility have further complicated supply chain management by impacting the cost of raw materials, transportation, and labour. These trends have put pressure on profit margins, forcing companies to rethink pricing strategies and cost management. Additionally, climate change and other sustainability priorities have prompted businesses to seek more resilient and environmentally friendly supply chain practices, although these initiatives often come with their own hurdles.”
“Despite this environment, executives and stakeholders recognise that supply chain is a strategic lever for companies. Meeting ever-increasing customer and stakeholder demands in this challenging environment requires supply chain organisations to consider new strategies and practices. Companies are evaluating emerging solutions (e.g., generative AI, advanced analytics), implementing strategies to strengthen supplier diversity, risk management, and supplier relationships, and redesigning processes to improve visibility, agility, and resilience. These improvements will help ensure success and a promising future for supply chain.”
Sustainability
Sustainability is an important item on most Chief Supply Chain Officers’ agenda. Amid government legislation and changing customer demands, is a sustainable supply a non-negotiable in today’s world?
ScottMadden: “Regulations and increasing consumer demand for ethical and environmentally friendly products are major drivers for sustainability. Sustainability is less of an option and more of a fundamental requirement in today’s business environment.”
“Global regulations are increasingly mandating sustainable practices, with regulations targeting carbon emissions, waste management, and resource usage. Failure to comply with these regulations can lead to significant financial penalties, reputational damage, or worse.”
“Customers are increasingly prioritising sustainability in their purchasing decisions. Consideration of sustainability may be more weighted when procuring certain types of materials, services, or for end-users. For example, in the Consumer Packaged Goods industry, customers may be more sensitive to the consideration of sustainability of product ingredients. This shift includes B2B relationships, where businesses scrutinise their suppliers’ environmental and ethical standards. Sustainable supply chains are indeed becoming non-negotiable. In addition to the required compliance with regulations, this transition feeds brand loyalty and, when executed effectively, operational efficiencies.”
Jason Davis
Digital transformation
What should CSCOs out there do first? What needs to be considered before starting the gen AI journey?
ScottMadden: “First, ScottMadden recommends clarifying the business problem that could be solved with generative AI. All organisations have a list of improvement opportunities that can be refined into specific use cases. Supply chain organisations should evaluate and prioritise these use cases based on data availability, quality, and business context. Identifying one or two high-value use cases for a pilot is a good way to begin the generative AI journey.”
“Executing the pilot involves forming the right team, selecting the best-fit technology solution, transforming the data, and iterating the solution until the desired result is achieved. Companies can use Pilots not only to deliver on the use case but to also build components of the technology and data infrastructure needed for future pilots or use cases. The key benefit of a pilot, in addition to addressing a high-value use case, is the learning that results from the data transformation and technology configuration. These lessons can be applied to additional use cases, setting the foundation for a robust data structure and enabling the delivery of solutions at scale that build on one another.”
Tech challenges
What are the biggest challenges or hesitations you’re seeing companies have around AI? What should organisations look for in technology to hedge against these concerns?
ScottMadden: “The most common challenge related to generative AI is data security. Generative AI enables relatively easy access to many users, which creates risk for organisations.
“Selecting the best-fit technology for investment is another key challenge. In supply chain, as well as other functions, many technology solutions with AI functionality have emerged, raising questions about what to use and how to deploy, manage, and govern these solutions.
“Determining how to implement a scalable data solution is another major hurdle. The issue of data governance has existed for many years. Investing the required time and resources in data integrity and infrastructure has been a daunting task for many organisations, often resulting in deferred or unsuccessful data-related initiatives.
“As described previously, we recommend executing a pilot to address one or two high-value use cases. This approach provides solutions to important business problems and enables learning that can be applied to other improvement opportunities and used to build a scalable data-driven operating model.”
Future
How can the supply chain industry take that next step and what strategies can be implemented to push the industry forward even further?
ScottMadden: “Supply chain leaders should lean into digital transformation, resilience, and sustainability. A solid approach to digital transformation (e.g., data analytics and AI) will enable resilience, sustainability, and effectiveness. By embracing digital changes early and incrementally, supply chain organisations can ensure a ‘seat at the table’ when enterprise strategies are discussed. Similarly, considering data skills to the Supply Chain workforce will help prepare organisations for an increasingly digital future”
Are there any exciting projects that you’re currently working on or any past ones that you’re proud of that you’d like to highlight?
ScottMadden: “Some of our most recent work has involved using data analytics and AI to help shape materials management strategies, resulting in significant opportunities to drive savings and increase agility and scalability. We have been able to leverage proven inventory management methodologies to identify these opportunities more quickly and efficiently, which enables faster implementation for our clients. We have also applied related techniques to warehouse design and network optimisation. The exciting part is that we are just scratching the surface with these solutions.”
On the back of ASCM CONNECT 2024, Suyash Deo, Functional SME Data Analytics and AI at Softweb Solutions, reveals how new technology can unlock numerous opportunities and create significant value for organisations.
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GenAI is a game-changer for procurement.
It has the potential to redefine procurement’s entire operating model and significantly accelerate the function’s efficiency.
To a Chief Procurement Officer, saving both time and money is like music to their ears. However, that’s not to say that GenAI has all the answers and doesn’t come without challenges.
In this exclusive article, Suyash Deo, Functional SME Data Analytics and AI at Softweb Solutions, tells us more about how GenAI and conversational AI represent revolutionary advancements in technology, poised to transform traditional supply chain operations.
Would you be able to give me a brief introduction to your role and the company you work for?
Suyash Deo: “I serve as a Functional SME in AI and Data Analytics at Softweb Solutions. With 13 years at Softweb, I’ve managed key accounts in supply chain and manufacturing, driving their digital transformation.
“Softweb Solutions, an Avnet company, is a global system integrator headquartered in Dallas, with offices in Chicago and a development unit in India. For over two decades, we’ve been bridging technology gaps in digital supply chains through data and AI-driven strategies. We’re closely aligned with Hyperscalers like Microsoft and AWS, and enterprise platforms like Salesforce and SAP.”
Suyash Deo, Functional SME Data Analytics and AI at Softweb Solutions
ASCM CONNECT 2024
What is the value of events like ASCM CONNECT 2024: North America? How important is this conference in the supply chain calendar?
Suyash Deo: “ASCM CONNECT 2024 stands out as a premier event, offering a unique platform for professionals in the supply chain industry to collaborate and connect. While we attend many industry events, the networking opportunities at ASCM CONNECT are truly unmatched.”
What are the biggest takeaways from this year’s ASCM CONNECT for you?
Suyash Deo: “At Softweb, we had the opportunity to showcase our Generative AI framework, Needle, along with our AI agent capabilities. The response from the audience was overwhelmingly positive, particularly in seeing how AI agents can revolutionize traditional operations. Additionally, the event offered valuable networking opportunities and insights from industry experts, making it a highly enriching experience for us.”
Global supply chain
How would you describe where the supply chain space finds itself today?
Suyash Deo: “The supply chain sector has undoubtedly been among the hardest hit by recent global disruptions. These challenges have exposed vulnerabilities and push the industry to rethink its approach.
“We’re now moving away from the traditional, linear supply chains toward more interconnected, technology-driven networks. There’s a strong shift towards data-driven strategies and an ‘AI-first’ mindset, which is rapidly becoming the norm in organisations aiming to future-proof their operations. The focus has shifted to creating smarter, more resilient supply chains that are better equipped to handle the uncertainties of today’s global landscape. This evolution is what we’re now considering the ‘new normal’ for supply chains.”
Digital transformation
Where are generative and conversational AI having the biggest impact in the supply chain? What types of supply chain and procurement decisions are now possible, or much easier to make, with the rise of AI and LLMs? How does this compare to just a couple of years ago?
Suyash Deo: “At ASCM Connect, we showcased our GenAI Framework, Needle. This cutting-edge tool integrates with multiple data sources and enterprise systems through its AI agent. During the demo, we illustrated how Needle can generate a Bill of Materials (BOM) from natural chat conversations with clients. It captures key information—whether it’s an image, web link, or text—and uses that data to determine specific requirements for electronic boards and parts. Additionally, Needle can recommend alternative parts for aging inventory, create new opportunities in Salesforce, notify account managers, and validate parts availability.
“This AI-driven approach has optimised the traditional procurement process by over 40% and significantly improved customer experience. Looking back a few years, procurement involved a cumbersome chain of emails and forms, extensive data exchanges, and a high level of human dependency, all of which increased the risk of errors. Needle modernises and streamlines these processes, delivering greater efficiency and accuracy.”
What should CSCOs out there do first? What needs to be considered before starting the gen AI journey?
Suyash Deo: “GenAI technology has the potential to unlock numerous opportunities and create significant value for organisations when implemented effectively. However, we’ve noticed that many clients begin with proofs of concept (POCs). This is before then abandoning full-scale implementation due to inadequate planning.
“In our Data 360 program, we address this challenge by starting with a thorough data readiness assessment and mapping out all overlapping workflows. While we always adhere to a well-defined AI strategy, our approach ensures that it is tailored to fit each client’s existing ecosystem and use cases.”
Biggest challenges
What are the biggest challenges or hesitations you’re seeing companies have around AI? What should organisations look for in technology to hedge against these concerns?
Suyash Deo: “During our workshops, we encounter various concerns from stakeholders. This is much like the apprehensions someone might have when riding a jet ski for the first time.
“However, one common worry is, ‘We do not want to share our data with the LLM.’
To address this, we implement our Needle framework directly within the client’s cloud environment.
This setup ensures that clients maintain full control over their data sources, user interactions with the AI model, and the resources it generates.
“Additionally, we provide a comprehensive overview of the GenAI thread landscape from an enterprise perspective and explain how Needle integrates within it. We can also discuss specific cases in detail to address any further concerns.”
What are the underlying issues in how companies are currently storing and looking at their supply chain data? Why is this a problem and how can they overcome those challenges with generative AI and knowledge graphs?
Suyash Deo: “We frequently encounter this question during our workshops. As I mentioned earlier, GenAI or even traditional AI should come later in the process. The first and most critical step is building a solid data foundation.
“Many systems operate in silos, a number of applications run on local servers, and it’s not uncommon to find data managed through XLS and CSV files. This fragmented setup makes it difficult to ensure data availability for successful AI implementation.
“We always recommend focusing on strengthening the foundational data layer first. Once that’s in place, companies gain the flexibility to fully explore and leverage the true potential of AI.”
Future
Are there any exciting projects that you’re currently working on or any past ones that you’re proud of that you’d like to highlight?
Suyash Deo: “We’re involved in some exciting projects, especially in the areas of AI, data analytics, and digital transformation. Let me share two examples.
“Recently, we partnered with a leading supply chain company to develop a robust solution called POLAR. It’s a cloud-based web platform specifically designed to manage supply chain operations across different business units in the Asia-Pacific region. POLAR includes modules for planning, operations, logistics, reporting, and analytics, all customised to meet the needs of various roles within each unit.”
Challenges:
“They were facing numerous challenges managing their complex supply chain operations across diverse business units in the Asia-Pacific region. These includes Slow SAP data retrieval, which hindered real-time decision-making, forecasting future operations was also challenging due to the difficulty in analysing historical trends effectively.
Solution
“Our developed web platform designed specifically to manage supply chain operations across diverse business units in the Asia-Pacific region. Built leveraging Azure services, it offers robust features, including modules for planning, operations, logistics, reporting, and analytics.
“This resulted into greater impact in form of;
Improved Operational Efficiency: Automated processes, reducing time and effort in managing supply chain operations.
Enhanced Data Accuracy: Eliminated manual errors, resulting in more accurate reporting and decision-making.
Faster Decision-Making: Real-time SAP access and historical comparisons enabled quicker, informed decisions.
Seamless Integration: Integration with SAP and third-party systems optimized the entire supply chain.
Future Scalability: The cloud-based platform supports long-term growth and adaptability for the business.
Project FSP
“We have also built Full-Service Portal (FSP) to streamline their product service and ordering for end client.
“Portal also covered critical modules, including product listing, order processing, and BOM (Bill of Materials) management, to enhance operational efficiency across regions.
Key Features:
Product Listing and Search: A robust system for listing products with extensive search and filter options, enabling users to find products efficiently.
Quoting System: FSP introduced a quoting module that allowed users to request quotes through multiple channels, track quote progress, and place orders based on quoted products.
BOM (Bill of Materials) Management: The BOM module enabled users to create BOMs through various options, track product availability and pricing, and manage quotes and orders for BOM products seamlessly.
Results and Impact
Improved Efficiency: The system streamlined product listings, order management, and quoting processes, improving response times and customer satisfaction.
Global Reach: The platform’s capabilities supported FSP’s operations across the Americas, APAC, and EMEA, enhancing its global presence.
Enhanced Customer Experience: Customers could easily navigate through product listings, request quotes, and track orders, leading to a better user experience.
BOM Optimisation: The BOM management feature enabled more accurate tracking of product availability and pricing, reducing delays in production and order fulfilment.
“This solution helped FSP rapidly respond to market changes, ensuring greater flexibility and operational agility across its global footprint.”
Andy Coussins, Executive Vice President at Epicor, lays out the role of data and AI in developing supply chain resilience.
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Essential industries — those that make, move, and sell products — are no strangers to using technology to help them navigate supply chain disruptions, escalating costs, and skilled labour gaps. Businesses in sectors like manufacturing, retail and logistics have already embraced cloud computing and the Internet of Things (IoT) to streamline their operations and insulate them from the chill blast of economic uncertainty and supply chain disruptions.
A report by PWC, Transforming your supply chain, highlights this trend, discussing industry-wide investment in digital systems and noting that that 77% of UK digital champions have implemented solutions to gain visibility across their end-to-end supply chain.
Today, these ‘traditional industries’ are further advancing their investment in cloud and IoT technology by embracing artificial intelligence (AI) and machine learning (ML) to enhance their supply chain resilience.
AI is key to developing resilience and increasing efficiency
One of the main reasons behind the adoption of AI is its almost unlimited potential. It can help establish vital data bridges across departmental silos, automatically analyse disparate business data, and provide actionable insights to enhance operational performance.
Not only can AI automate processes, but it can also replace the need for human interventions. Therefore, this streamlines complex processes even further. It can spot trends, carry out mundane and repetitive tasks, flag inconsistencies, make connections, and deliver insights that would be beyond the capability of even the most eagle-eyed employees.
But there’s a problem. AI relies heavily on access to quality data. Inaccurate, untimely data inevitably leads to poor insights. That’s why a holistic, data-first, ERP business strategy is key to success.
Modern ERP system designers are purposefully incorporating AI into their products. This AI-powered software enables quick analysis of large volumes of data, converting a system of record into an organised system of actions.
By automating certain manual processes from the shop floor that could take hours to complete, it frees up employees to focus on other important areas of the business.
The importance of having a clear understanding of operations before adopting AI
Businesses can only achieve this if they clearly understand what’s going on both inside and outside of their operations. This means knowing what data they already have access to, where silos exist, and how to strengthen the critical partnerships needed to facilitate seamless and secure data exchange.
According to Epicor’s 2024 Agility Index, conducted by independent analysts Nucleus Research, 58% of organisations have already integrated generative AI into their digital supply chain operations.
Underlining just how much progress had been made, the research found that businesses had applied AI across various functions within their software applications including product descriptions, customer chatbots, natural language querying, reporting, and in-application assistance.
In fact, almost two-thirds (63%) of high-growth organisations have integrated generative AI into their respective supply chain operations through their ERP and supply chain management software applications.
These findings point to one obvious conclusion; businesses are increasingly turning to AI, ML and other technologies as part of a strategic move to enhance operational efficiency and customer engagement.
A practical approach to adoption
Of course, the rewards for such strategic decision-making don’t happen overnight. Nor can such results be achieved successfully without taking a measured and practical approach to the adoption of AI. So, what’s the best approach?
The message from those that have already begun their AI journey is that an effective data supply chain strategy can only work through a connected ecosystem of partner communities. Not only that, it must also seek to remove data silos by integrating key functions such as finance, design, testing, and manufacturing.
For it is only once organisations close the gaps between the shop floor, the boardroom, and different departments, that insights can start to flow more freely. Key to that, of course, is to ensure open communication across all departments and between management layers — as well as trusted strategic digital transformation partners.
After all, as ERP specialists they know the industry and can alleviate any anxiety about AI-powered data integrations, cybersecurity, or adaptability. What’s more, they are best placed not only to help businesses capitalise on an AI-led approach but ensure that it’s aligned with the long-term strategic direction of a business.
Theresa Macdonald, Business Development Manager at Element Logic, explores five trends changing the face of warehouse automation in 2024.
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The past few years have been transformational for logistics and supply chain operations, with warehouses at the epicentre of this change. Economic volatility, global political shifts, and the lingering effects of COVID-19 have made the landscape increasingly complex, further intensified by constantly evolving consumer behaviours.
Instead of waiting for an elusive return to “normalcy,” now is the time for businesses to proactively future-proof their warehouse operations. Here’s a closer look at four technology trends that are not only navigating but also shaping this unpredictable future.
1. The rise of warehouse automation and robotics
Technological advancements are rapidly transforming the logistics sector, with automation emerging as a key driver of competitive advantage.
Automation significantly enhances storage density, reduces overhead costs, and extends operational hours, meeting the demands of rising order fulfilments. Take Automated Storage and Retrieval Systems (ASRS), for example. These advanced systems use goods-to-person technology to optimise space, improve order-picking accuracy, and cut labour costs. By seamlessly integrating with Warehouse Management Systems (WMS) and data-driven Warehouse Control Systems (WCS), ASRS provides continuous improvements through real-time feedback.
In addition, robotic piece-picking technologies, powered by machine learning and AI – achieve high picking rates while virtually eliminating human errors and reducing labour demands. Autonomous Mobile Robots (AMRs) further boost efficiency by navigating warehouse spaces with sensors and vision systems to manage tasks that are hazardous or impractical for humans.
Although the initial investment in automation technology can be steep, the return on investment usually manifests within 1-2 years, enabling around-the-clock operations and optimal asset utilisation.
2. Data-driven decision making
Harnessing real-time data through sophisticated AI and machine learning software unlocks vital insights that drive process efficiency, inventory management, and customer behaviour understanding.
Translating these insights into actionable strategies boosts performance. For instance, data-driven software streamlines capacity planning by alerting managers to potential constraints, ensuring timely resource redistribution. Digital twin simulations can stress-test various scenarios in a virtual model of the warehouse, offering enhanced planning capabilities.
Predictive maintenance further mitigates risk by flagging potential equipment issues before they escalate, preventing costly operational disruptions.
In transportation, analytics-driven software enhances supply chain efficiency, making logistics more resilient. Engaging staff through gamified tasks acknowledges their efforts and boosts morale, creating an efficient and enjoyable work environment.
3. Accessible automation for smaller businesses
Contrary to widespread belief, warehouse automation isn’t just for large enterprises. Smaller businesses can also benefit, particularly through models like Automation-as-a-Service (AaaS), which offer a cost-effective, low-risk entry into enhanced automated operations.
Small companies can leverage automation technologies to scale sustainably without the burden of operational complexities. AaaS ensures positive cash flow, allowing funds to be directed toward innovation and growth.
Warehouse automation solutions are highly adaptable, fitting into diverse spaces and scaling according to needs. Easily reconfigurable, these technologies meet the dynamic requirements of smaller businesses and third-party logistics providers (3PLs).
4. The growth of Micro Fulfilment Centres
Heightened consumer expectations for same-day or next-day delivery are compelling businesses to rethink their distribution models.
Micro fulfilment centres (MFCs) are emerging as a formidable solution, especially among European grocery retailers. These localised, small-scale warehouses expedite deliveries, enhance inventory control, and streamline returns. Strategically located close to consumers — in retail stores, nearby buildings, or dedicated ‘dark’ warehouses — MFCs reduce last-mile delivery times, cut transportation costs, and lower emissions.
Although manual labour in MFCs can limit efficiency and stock volume, investing in flexible, modular automated systems can significantly enhance both storage density and operational efficacy.
5. Embracing smart warehousing
The future of warehousing holds immense promise. Staying abreast with emerging trends and technological innovations is crucial for businesses aiming to excel in this ever-changing commercial landscape.
The key is to embrace change and stay ahead of the curve, creating a resilient and adaptive warehousing strategy. By recognising and acting upon these trends, businesses are well-positioned to navigate future uncertainties, ensuring both operational resilience and sustained growth.
Holly Clarke, Product Manager, Inventory AI, at Peak, examines the role of AI in creating stock transparency for supply chain managers.
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For as long as commerce has existed, from ancient merchants to today’s multinational conglomerates, knowing the optimal amount of stock to hold across complex networks of warehouses and stores has been a persistent challenge. Now, in an increasingly digital age, supply chain managers are having to adapt even quicker.
Research last year predicted inventory distortion – the combined cost of loss of sales from out-of-stocks and excess stock – would cost retailers $1.77 trillion in 2023. With so much value at stake, failure to adapt to modern day challenges would be catastrophic for businesses and consumers alike. The seamless adoption of new solutions is critical to business development.
For supply chain managers untuned to the world of AI, how can the technology optimise their processes? And what advantages can they expect?
Same problem, far greater variance
Economic downturns, geopolitical tensions, extreme weather events and changing consumer habits have always played their part in global challenges faced by supply chain managers. What’s more, a reliance on historically manual processes and spreadsheets has made it incredibly challenging to gauge what optimal inventory levels look like and how best to balance costs.
Today, unprecedented modern events have laid bare supply chains’ vulnerabilities, meaning solutions need to be found at pace. Not only caused by political or economic levers, even superstars impact global supply chains. Last year, Google search data showed a notable spike in the search term ‘metallic cowboy boots’ as Beyoncé’s Renaissance world tour kicked off and fans grappled to purchase their own show outfits. If you also consider vastly changing customer needs driven by economic uncertainty, supply chain managers are dealing with a host of obstacles; demand can change at the flick of a switch.
Disruption and uncertainty can always be expected, but striving for near-perfect inventory levels – including more SKUs and faster delivery – is almost impossible without AI.
Overstock vs out of stock: A balancing act
The key challenge for any supply chain manager is finding the balance between holding too much stock (especially when demand is low) and too little (especially when demand is high).
The former means they risk obsolescence, needing more warehouse space to house additional stock and potentially wasting vast amounts of products that go past their ‘sellability’. It can result in the business having to shift that stock at discounted rates and puts pressure on nailing every single sale. The latter of course means a host of missed sales opportunities, not only impacting revenue and operational costs but also brand reputation. The consequences can be critical to a business.
Forward-thinking companies are looking to AI to optimise their inventories. The more they can optimise, the less sales lost and the less capital tied up in excess stock. For example, by using AI, they can assess inventory levels in real time and instantly make decisions to balance factors like product availability and life cycles with operational costs, a process that used to take days or even weeks.
And for the early adopters, the proof is already in the pudding. Using AI, McKinsey research showed these adopters lowered their logistics costs by 15% and improved service levels by 65% “compared with slower moving competitors”. But if the results are attractive, why are more companies not jumping aboard the AI train?
Optimising team processes
It’s the unfortunate truth that supply chain teams are struggling for resource. In fact, a recent survey found that 76% of supply chain and logistics leaders are experiencing significant shortages in their supply chain workforce.
Part of this is due to recruitment challenges, which plague the industry. Enticing tech companies and roles attract talented tech workers. Supply chain is missing out on key talent. Organisations need to shine a light on these supply chain roles and companies to ensure there is a healthy flow of talent into the sector.
On top of recruitment challenges, to combat these pesky supply chain resource shortages, organisations need to optimise their team processes. But, what does this look like?
When AI is introduced into the fray, teams can regain time in both the short- and long-term, giving them much-needed time back to plan and strategise. AI-powered insights also elevate this strategic planning, empowering supply chain teams with a quantity and quality of data they might not have accessed previously.
An approach fit for the modern world
You can never truly predict future customer demand. But if you know how much variance there usually is between forecasted demand and the true level, you can implement a supply chain strategy and inventory level best suited to deal with this fluctuation.
It’s not an exaggeration to say that without using AI in the coming years, companies could be losing millions in margin compared to their AI-powered competitors. But if they can start to embed AI into their supply chain operations now, they can form a flexible and modern approach to tackle a problem as old as commerce.
Holly Clarke is Product Manager for Inventory AI at Peak, a UK-based artificial intelligence company building unique AI solutions for companies of all sizes in every market and vertical.
Companies across industries are increasingly under scrutiny for alleged greenwashing. It’s estimated that 40% of businesses’ green claims could be…
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Companies across industries are increasingly under scrutiny for alleged greenwashing. It’s estimated that 40% of businesses’ green claims could be classed as unsubstantiated or misleading. In Britain alone, 70% of British consumers dismiss green claims as false or deceptive.
While enterprises are most commonly the target of greenwashing claims, we’re seeing that even the most iconic events are finding themselves in the hot seat. The 2024 Olympics is currently facing criticism for inflating its sustainability efforts.
The consequences of greenwashing can have far-reaching impacts on an organisation, including loss of customer trust, declining sales, and even litigation. Beyond these direct impacts, companies are now facing the threat of severed business relationships, deterring investors, and limiting potential partnerships due to the risk of reputational damage by association.
Commenters have deemed the new Sustainability Disclosure Requirements, introduced by The Financial Conduct Authority (FCA) earlier this year, to be the “most significant single piece of UK sustainable finance regulation to date.” It mandates that all regulated firms stop greenwashing or making climate-friendly false claims. As a result, smart businesses are re-evaluating how they track ESG activities to ensure their claims are truthful, transparent, and compliant with FCA requirements.
Responding to the New Regulatory Landscape through Contracts
Contracts are foundational to commerce governing every dollar in and out of an enterprise. They act as a single source of truth for business relationships to ensure that the company and its suppliers are following ESG regulations and delivering on promises like net zero pledges. According to a recent survey that studied what defines trust in business relationships and what companies can do to build the necessary trust to achieve their goals, 70% of executives said they view contract language as an effective tool to enforce ESG standards and commitments. These contract clauses are wide-ranging and could include provisions aimed at promoting biodiversity, net-zero targets, and the prevention of land contamination.
Despite the rise in demand for more standardised ESG clauses, only 30% of organisations are actively embedding ESG language into their contracts. When business leaders begin to develop ESG contract language, they often find they have limited visibility into existing contracts and the current requirements for global suppliers. Add on the challenge of traditional contract management systems that consist of manually stored PDF documents, and you’ve now created a black hole with no clear path forward. Contract mismanagement can mean these ESG clauses are not properly tracked or enforced. This results in potential legal risk and reputational damage that could harm an organisation’s bottom line.
The Role of AI in Formulating ESG Clauses
AI has enabled organisations to overcome these challenges by providing visibility into existing contracts, promoting standardisation, and ensuring accountability.
Contract data presents one of the most valuable untapped assets in the enterprise and a prime resource to fuel innovation with AI. While contract intelligence equips companies with the visibility, automation, and insights to efficiently track and report on ESG obligations, AI enhances efficiency to empower customers to unlock the full potential of their commercial agreements – for example, determining whether ESG obligations are included and adhered to. Essentially, AI-powered contracting serves as a partner for legal teams, alleviating the burden of managing large volumes of contracts. This is critical because it helps avoid compliance threats, reputational risk, financial penalties, and sanctions, or even the inability to quickly respond to regulatory changes.
ESG Regulations and Supply Chain Compliance
AI-powered contract intelligence is empowering organisations to more accurately monitor ESG compliance within supply chains. Take, for example, the war in Ukraine.
At the time of Russia’s invasion, government regulations around the world halted any business conducted with Russian-based companies. Supply chains around the world needed to respond immediately. However, not everyone had the infrastructure in place to quickly identify at-risk suppliers. The result was a month-long supply chain disruption.
By harnessing AI-powered contract intelligence, businesses are able to understand their risk profile concerning sanctions and implement changes that would ensure compliance.
This is just one example of how AI-powered contract intelligence can enable enterprises to thrive despite macroeconomic challenges. The same holds true for organisations looking to track their supplier’s environmental impacts or even identify areas where there’s an opportunity to reduce their carbon footprint.
By connecting millions of contracts and infusing their data into core enterprise systems, enterprises can create rich pools of AI-powered insights to inform better decision-making around ESG commitments and complex regulations.
The Future of Company Contracts and ESG Practices
In the eye of public opinion, ESG commitments are not optional. Gone are the days when ESG commitments were a ‘nice-to-have;’ they’re now an absolute imperative for any organisation that conducts business.
Businesses will need to digitally transform their contracting systems to ensure they adhere to FCA greenwashing regulations, as well as to avoid the loss of shareholder, investor, and customer trust.
Investment in AI will play an increasingly important role in guaranteeing standardisation and visibility. This ensures that organisations throughout the supply chain adhere to the ESG clauses in their contracts. This, in turn, will combat the challenges that prevent organisations from meeting their sustainability goals.
By deploying the right software, businesses can not only address these specific challenges, but also increase revenue, reduce costs, and mitigate risks – outcomes that are vital in the current business environment. It’s all about structuring and connecting contract data across the enterprise to deliver speed and scale, and applying AI to ensure the intent of every business relationship is correctly captured and fully realised.
Chantal Bisson-Krol, VP AI & ML Solutions at Kinaxis, lays out five ways to successfully augment your supply chain with artificial intelligence.
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Supply chains have never needed more help – from geopolitical conflicts to extreme weather, the challenges facing supply chains across every industry are becoming much more pronounced. As with almost every other industry, AI technology could be perfectly poised to support supply chain professionals to overcome these challenges – but how?
AI technology isn’t simply a plug-and-play solution, however. To get the most out of AI, supply chain professionals need to abide by a few guiding principles.
1. AI should augment humans
First thing’s first: the achievements of AI in the past couple of years are nothing short of incredible, which is why it’s easy to forget the things that machines cannot provide, which I call the three C’s: context, collaboration and conscience. Models cannot derive meaning from context, critical in so many areas of the supply chain, nor can they work together to solve problems, including addressing issues like sustainability or human rights in supply chains.
This is why AI should augment humans. The most powerful combination is for humans and AI to work together, a belief reflected in a Workday survey of decision-makers, 93% of whom believe in the importance of keeping the human in the loop when AI is making significant decisions.
2. AI needs to fuse with heuristics and optimisation
AI can model problems at scale to produce more precise recommendations, such as greater demand forecast accuracy or better predictions of on-time delivery. Precision is also a benefit of optimisation, a field of AI familiar to many in supply chains for its ability to make the best use of resources within constraints to specific objectives, such as cost minimisation. Scale, though, can be a challenge: optimising a supply network can involve 200 million interdependent variables, slowing down even the fastest optimisation solver. Instead, some turn to heuristics, a problem-solving model that utilises a practical solution, or best practice, to produce a quick and feasible course of action good enough for the situation.
A fusion of the heuristics and AI can “warm start” an optimisation model, creatively combining the strengths of each approach to achieve an equilibrium of speed, precision and cost-effectiveness. Supply chain professionals should keep their hands on the wheel and remember that the most elegant solution is one that uses the right model for the right problem at the right time, no more, no less.
3. Concurrency and AI can transform supply chain management
Supply chains connect many functions across a company and beyond, which is why optimising one link doesn’t optimise the entire chain. For example, AI can greatly increase the accuracy of forecasts, but we want more than highly-efficient silos. The power of AI on its own is not enough.
The real breakthrough is not from AI but with concurrency, which integrates AI in the workflow to align decision-making across the supply chain for faster response. We want AI for its ability to predict with greater precision, speed, and elegance, and we need concurrency to connect supply chains for better, faster response, no matter what the conditions are. The bottom line is that AI embedded in concurrency leverages predictions while absorbing the volatility we cannot predict from the inevitable disruptions our supply chains will always face.
4. Democratise the power of AI
For AI to realise its potential, everyone must be able to use it. We will always need experts to explore new ways to apply AI, but empowering supply chain practitioners to adopt it themselves is crucial to realising its true power within the supply chain industry. For this reason, the best solutions are the ones which don’t require technical proficiency in AI or data science in order to use in your day-to-day role.
If solutions are designed for someone with supply chain context and business knowledge, they can “consume” the results of a model without knowing how to build it. Democratising AI in this way ensures its use, so choose to work with a provider who allows you to start from where you are and evolve.
5. Build Trust in Your AI
Many AI solutions come in a black box that even data scientists struggle to unpack. This is bad for visibility, but it can also be bad for adoption; supply chain professionals are ultimately responsible for their forecasts and, if they can’t explain how an AI platform is helping them to make their forecasts, they might think twice before trusting it. In fact, researchers have found that humans are more forgiving of what they perceive to be error on the part of fellow humans than they are from machines, a trait that can lead to them to develop “algorithm aversion.”
One approach to overcoming this aversion is state-of-the-art techniques that make black box AI models more understandable. For example, explainability techniques such as feature attribution methods can be used in demand sensing to help a planner see how adding a signal like weather affects predictions. Creating AI solutions that we can understand goes hand in hand with democratisation and, ultimately, will help improve adoption across the supply chain industry.
It’s clear that AI is transformative for the supply chain, and it’s fascinating to envision an industry augmented by this exciting technology. As we ramp up our use of AI, though, we need to remember that the trick to getting the most out of it is by adopting a human-centred approach. When AI is embedded across the end-to-end supply chain, expertly fusing the best techniques available, we can reimagine what is possible in our supply chains.
Andrea Morgan Vandome, Chief Innovation Officer at Blue Yonder, explores the trends shaping the future of the supply chain industry in 2024.
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Blue Yonder’s2024 Supply Chain Executive Survey reveals the many shared challenges and trends that continue to impact businesses worldwide. Once again, supply chain disruptions, rising costs and sustainability pressures proved top of mind for many. Unsurprisingly, the combined impact of all these issues has served to hit the bottom line, with almost half (46%) of global organisations confirming that profit margins are down.
To address these challenges and regain a degree of control, supply chain leaders are turning to innovative technology solutions to elevate end-to-end capabilities and make their supply chains more resilient, sustainable and agile.
Let’s take a look at what they are doing, and why.
The top twin challenges: disruptions and rising costs
Dealing with disruptions remains the number-one challenge facing today’s supply chain teams. In addition to raw material shortages (48%), delivery lags from suppliers (47%), labour shortages (44%) and transportation capacity restrictions (41%), senior executives cited issues resulting from extreme weather conditions, shipping route changes and geopolitical unrest.
Asked to evaluate how these disruptions had impacted their business, senior decision makers identified a number of negative outcomes including delays for customers (42%), production stoppages (42%), regulatory compliance issues (39%), reputational or financial damage (38%) and an inability to meet customer demand (38%).
In addition to managing frequent disruptions, supply chain organisations also confirm that soaring cost inflation is putting profitability under pressure. Globally, rising transportation costs (38%) and raw material costs (34%) were identified as the two most significant issues generating supply chain stress.
These combined challenges have had a significant commercial impact, with almost half (46%) of organisations globally reporting a decline in profit margins. Firms operating in the US appear particularly hit by these ongoing supply chain vulnerabilities, with 60% reporting decreased margins.
In response, many firms are doubling down on sustainability initiatives in a bid to reduce waste and excess and, by doing so, gain greater control of their cost base.
Sustainability: a strategic investment
Maximising sustainability across the supply chain is now a key focus for supply chain firms, with nearly half (44%) increasing their investment in sustainability initiatives last year.
Reducing waste and excess – including production, inventory and raw materials – was the top sustainability goal for 57% of senior executives. Meanwhile, 55% said their primary focus was increasing transportation efficiency, optimising fuel usage, redesigning network and transportation routes and creating greener fleets.
In addition to the pursuit of initiatives that boost efficiency and reduce the consumption of resources, and thereby lower operational costs, supply chain organisations are also looking to improve supplier sustainability (46%), enhance the returns process (34%), and innovate product design for enhanced reuse/circularity (34%).
To accelerate these sustainability initiatives, and optimise supply chain decision-making at scale, more and more organisations are increasing their investment in AI technologies. The reason – so they can improve supply chain efficiencies (53%), reduce disruptions (37%) and increase profitability (29%).
AI and supply chains: navigating uncertainty with enhanced insight and agility
The survey shows the extent to which supply chain organisations are already harnessing AI technologies to drive efficiencies, augment decision-making, and speed up how they pivot in the face of unexpected or disruptive events.
Over half of supply chain organisations have deployed AI and ML solutions to improve the performance of supply chain activities such as planning (56%), transportation (53%) and order management (50%). Furthermore, 80% currently have generative AI initiatives underway, having either fully (12%) or partially (33%) completed these implementations or are running pilot programmes (35%).
Asked to evaluate the success of their generative AI programmes to date, 91% of firms stated these technologies are having a measurably positive impact when it comes to optimising supply chain processes and enabling improved decision-making.
So much so, that 86% of all survey respondents confirm they plan to increase their investments in AI, ML and generative AI in the coming year. The top motivations for these investments include boosting supply chain visibility (43%), driving automation (40%), optimising supply chain planning (35%), elevating supplier and partner collaboration (27%) and improving last mile delivery (25%).
Reimagining the future: digitalising the supply chain
Persistent and ongoing challenges are spurring organisations to digitally transform their supply chains so they can synchronise decision making in near real time and leverage data to drive smarter end-to-end resource planning and utilisation.
Changing how organisations execute their sustainability strategies, manage unexpected events and empower their personnel with insights – such as disruption predictions and course-correction recommendations – supply chain decision-makers are increasingly relying on AI technologies to power their organisation’s future success.
Looking ahead, supply chain executives have clear strategic investment objectives in their sights. In the coming year their top functional areas for targeted advanced technology adoption include transport management systems (49%), advanced warehouse management systems (41%), sales and operations planning (37%) and integrated demand and supply planning capabilities (34%).
Supply chains need to be ready for disruption, but is AI the right tool to help them remain agile in the face of the unknown?
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The modern value chain is vast, complex, and can contain thousands of suppliers.
These supply chains have evolved over the past decade, setting aside simpler, more linear structures in favour of complex ecosystems spread across multiple continents. Putting a single product in a customer’s hands can rely on the movement of goods across disparate geographies, between hundreds of companies, along vulnerable trade routes.
Recent geopolitical and climate-related disruptions are driving a return to simpler, more regional supply chain models. However, organisations are nevertheless still managing highly complex, fast moving supply chains in an increasingly complicated and dangerous world. From the US-China trade war and COVID-19 pandemic, to the ongoing Houthi attacks in the Red Sea and increasingly common extreme weather events, supply chains face a landscape where disruption has become the norm rather than the exception.
Can AI deliver supply chain resilience and agility?
Many supply chains have undergone radical transformations driven by the intersection of AI, machine learning, and increasingly cheap computing resources. “The culmination of those three things have revolutionised how we look at supply chain processes, all the way from demand forecasting to understanding at a granular level what customer needs are,” said Parvez Musani, SVP of End-to-End Fulfilment as Walmart in an interview with PYMNTS. “The integration of AI, ML, and vast computing power, coupled with an abundance of data, has transformed our approach to demand forecasting, inventory flow, and cost optimisation.”
AI’s ability to analyse vast data sets makes the technology ideally suited to generating the kinds of insights supply chain managers need based on broad market data. Not only that, but the technology’s ability to examine large amounts of unstructured information makes it very good at flagging risks before they develop into full-fledged disruptions.
Accurately forecasting demand is critical for retailers like Walmart. By effectively managing inventory levels, supply chain and logistics managers can minimise the likelihood of stockouts or overstocking. AI algorithms’ ability to rapidly comb through weather events, local news, historical sales data, market trends, and other contextual effects in real time allows the technology to generate accurate demand forecasts. Both Walmart and Amazon use AI tools to estimate and predict product demand in order to maintain the right inventory levels.
Food retailers across the UK are flocking to AI for its potential to reduce food waste, strengthen supply chains, and future proof their businesses.
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Throughout the UK’s food retail sector, organisations are turning to artificial intelligence (AI) as a way to meet the industry’s toughest challenges.
Supermarkets are embracing AI as a way to gain better visibility into their operations, supply chains, and customers. AI is ostensibly helping them create efficiencies, improve their quality of service and, most importantly, save money. The technology is even providing a glimpse into the changing diets of their customers. AI advocates believe the technology has the potential to transform multiple areas of the UK’s food retail sector—already the country’s biggest industrial sector. It employs 7.7m people with a total estimated Gross Value Added (GVA) of over £240bn.
AI for efficiency, cost-reduction, and customer experience
The first UK retailer to go “all in” on the technology is Sainsbury’s, which announced a five-year partnership with Microsoft last month. The partnership will see the food retailer use AI and machine learning capabilities to accelerate its strategy to become the UK’s “leading AI-enabled grocer.”
Reportedly, Sainsbury’s wants the tie-up to improve its store operations. With AI tools in the hands of its employees and managers, Sainbury’s expects to operate its stores with greater efficiency and provide shoppers with more efficient, higher quality service.
It plans to use generative AI to make its online shopping experience more interactive. Customers could potentially receive recommendations from an AI-powered personal-shopper-style chatbot, or recommendations for ingredients that pair well with ones already in their cart. Whatever it looks like, the goal is to improve customers’ search experience to make shopping more “efficient and engaging.”
Sainsbury’s also wants to “empower” its in-store staff by providing them with real-time data and insights for key processes, including smarter shelf replenishment processes. AI tools will use data from cameras and stock information. It will then guide staff members to the shelves that need replenishing. This process will allegedly save valuable time and ensure sales opportunities aren’t missed due to missing stock. On the back end, Sainsbury’s plans to also integrate existing data with Microsoft 365 collaboration tools, generative AI and machine learning capabilities.
While added capabilities and customer experience is likely a part of Sainsbury’s two-footed leap into AI, the primary driver is most probably the company’s need to cut costs. Sainsbury’s is undergoing an ambitious cost-cutting initiative, which will see as much as £1 billion slashed from its expenditures over the next three years. For organisations looking to reduce labour costs, AI is quickly emerging as the number one justification for layoffs.
A-Eyes everywhere
Another retailer, Morrisons, has partnered with Focal Systems, a Seattle-based AI company, to use cameras for monitoring shelf availability in its supermarkets.
Focal Systems’ technology, trained on over two billion labelled images from more than 200,000 cameras can stock movement and spoiled produce hourly. It feeds this data to applications that identify restocking needs. If an item is out of stock but available in the backroom, the system lists it for restocking; if not, it orders more products.
More controversially, the cameras are also being paired with facial recognition technology to increase security surrounding alcohol isles. Focal Systems stresses in their literature that no identifiable customer or employee data is retained.
AI that lets you read the future
UK supermarket Waitrose and US AI firm Blue Yonder recently announced that they would extend their collaboration with Waitrose’s implementation of Blue Yonder’s AI-enabled forecasting solutions. The new move marks the first significant introduction of AI into Waitrose’s forecasting. The company hopes it can use the technology to improve stock availability across its stores.
Rather than relying on historical sales data and human intuition, the AI forecasting capability – part of Blue Yonder Demand Planning – reportedly focuses on customer behaviour, analysing “‘why’ customers bought what they did rather than just ‘what’ they bought.”
“Whether we are planning for a major sporting final or the first cold snap of the winter, there can be multiple factors affecting what our customers buy,” said Alison Maffin, Waitrose Supply Chain Director. She added that the ability for the Blue Yonder solution to learn from previous experience and help Waitrose predict demand shifts more accurately will help Waitrose be “confident we have the stock our customers want.” She notes that the AI-enabled forecasting will also allow Waitrose to “produce a much more accurate forecast” for the company’s suppliers and logistics partners, as well as resulting in less wastage.
Bug salad?
The Co-op is leveraging AI for a more forward-looking purpose. The company recently released a report detailing their predictions for the ways food could change in the UK over the coming decades. Their data predicts that meals eaten in the UK in the next 30 years could include cricket salads, lab-grown steaks and azolla burgers.
The report used generative AI imagery that paints a not-wholly unappetising picture of bug salads and futuristic meat cubes.
Partnering with experts from FixOurFood and the University of York, the Co-Op’s report predicted that the nation’s food tastes could change radically by 2054. British classics, including the traditional Sunday roast, could allegedly look radically different. Or, they say, replaced entirely by more “adventurous options.”
New research shows 81% of companies investing in supply chain technologies saw the benefits within 24 months.
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Supply chain leaders have traditionally been slower off the mark than other business stakeholders when it comes to technological adoption. However, when it comes to artificial intelligence and automation, few areas of the business see more consistently positive effects as the supply chain.
Supply chain leaders are what Noha Tohamy, distinguished VP analyst in Gartner’s supply chain practice, calls “fast followers”. As other functions in the enterprise see success, supply chains are set to follow suit rapidly.
Supply chain investment into AI, automation, etc. gathers momentum
Generative AI investment has been embraced by the supply chain sector with particular enthusiasm. A Gartner survey found that top performing supply chain organisations are investing in artificial intelligence and machine learning in order to optimise their processes at more than twice the rate of their lower performing peers.
Ken Chadwick, another VP Analyst in Gartner’s supply chain practice, noted that, rather than efficiency or cost saving, “enhancing productivity is the key factor that will drive future success” for supply chains. The key to unlocking that productivity lies in “leveraging intangible assets,” he explains. “We see this divide especially in the digital domain where the best organisations are far ahead in optimising their supply chain data with AI/ML applications to unlock value.”
However, investment into digital transformation and actually reaping the rewards of that investment are two very different things. Data gathered by McKinsey suggests that 70% of digital transformation projects fail to meet their stated goals.
Simply investing into AI, machine learning, and automation will not automatically create value in the supply chain. Thankfully, this is a lesson that supply chain leaders seem to have learned.
According to their report, technology investments are increasing organisations’ ability to deliver on their supply chain commitments. This, they found, “resulted in accelerating profitability, revenue growth, competitive differentiation, and supply chain efficiency.” Perhaps most interestingly, the benefits of investment into technologies like AI and ML were observed very quickly.
Last year, 97% of organisations surveyed by Cleo invested into “supply chain technologies.” Cleo’s research lacks specifics on which technologies exactly were invested into the most. It also fails to denote which ones saw the most impactful return. However, holistically, 81% of companies observed that their supply chain investment delivered business improvement in less than 24 months. An impressive 35% said they felt the benefits within a year.
This year, more than half of the enterprises surveyed are planning to invest $1 million or more into further supply chain technology adoption.
At a time when disruptions are more the norm than the exception in the supply chain, organisations are prizing resilience more highly. “By leveraging technology to build greater resilience to supply chain disruptions, a company is better able to take control of its supply chain commitments and deliver on their promises – resulting in stronger relationships and trust with their ecosystem,” says Tushar Patel, CMO at Cleo. He added that, in order to uphold their commitments, supply chain operators “need to consistently invest in their supply chain technology, otherwise they stand to take a hit to their relationships – impacting their bottom line.”
Supply chain visibility is at a low ebb, prompting leaders to explore machine learning as a way to regain critical insight into future threats.
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Supply chain managers in 2024 are faced with an increasingly thorny environment. From shipping disruptions in the Red Sea and Panama (and now in Baltimore), to a rise in extreme weather events, disruption seems less like the exception than the rule.
This ongoing disruption has highlighted the need for businesses to develop coping strategies. Increasingly, supply chain managers are looking to adopt technologies that let them predict and outmanoeuvre these disruptions. Agility and resilience are cardinal virtues for supply chains in 2024, almost as much as cost containment.
However, despite the goal being clear, many companies struggle to increase the resilience and agility of their supply chains. According to a recent article in the Harvard Business Review, a lack of accurate forecasting is to blame. As authors Narendra Agrawal et al posit, “how can inventory and production decisions be made effectively when demand forecasts are widely off?”
Machine learning and demand forecasting
Machine learning and artificial intelligence (AI) have tremendous potential to increase supply chain visibility.
The growth of IoT devices and oversight platforms is also generating a wealth of unstructured data across the supply chain. This makes machine learning an especially useful tool for tracking and predicting trends or disruptive events. Essentially, the technology is very good at finding complex patterns and relationships within historical data. As a result, machine learning can significantly enhance accuracy when predicting demand.
To use a simple example, let’s imagine a snack company. Using machine learning algorithms, this company could analyse historical and broader contextual data to pick up a pattern where sales of certain snacks tend to spike during specific seasons. During allergy seasons, the demand for grain-free snack foods might increase. Likewise, promotional events, like Veganuary, could cut demand for some products and drastically increase demand for others. Likewise, sourcing disruptions like a crop failure due to extreme weather conditions can be taken into account.
From a high level, these aren’t decisions that are beyond the scope of an experienced human supply chain professional to notice. However, it’s the ability for a machine learning algorithm to not only pull these insights from vast oceans of seemingly disconnected data, but to translate them into strategic recommendations for action (based on previous successes and failures) that makes the technology truly transformative. It’s doing what (not all) humans can do at speed and scale and, theoretically, with less propensity for error.
By continuously learning from these data points and recognizing the complex relationships between them, machine learning algorithms can generate highly accurate demand forecasts. As a result, companies can ensure they are stocking the right levels of inventory and ordering the right products at the right times.
Pressures on supply chain organisational processes are increasing. AI might be part of the solution with low and no-touch planning solutions.
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Supply chain teams in 2024 are under an increasing amount of pressure from multiple, often conflicting, directions.
Continued focus on sustainability and other ESG criteria is clashing with rising logistics costs, shipping delays, and pressure to cut costs. At the same time, the skills shortage continues to reduce employee headcounts while workloads are on the rise.
As a result, supply chain management capabilities across many organisations are starting to show signs of the strain.
“Existing planning capabilities have been unable to meet the demands of a more complex, multi-tiered, more nuanced world,” note KPMG analysts in a recent report. As a result, they argue that “few companies” with large, complex supply chains have enough visibility into the consequences of their actions. Without the ability to “run effective scenario analysis to determine the financial consequences of important decisions,” supply chain leaders are increasingly working in the dark.
Low and no-touch supply chain planning enabled by AI
AI-powered apps are increasingly being used to automate both sales and operational planning and integrated business planning. These applications KPMG notes, could be the answer to the question of how to bridge the “gap between supply chain planning and execution.”
Low-touch planning can streamline processes and harness advanced analytics to tackle complex issues with minimal human input, taking “large swaths of manual work out of the end-to-end planning process.”
AI’s ability to analyse large, disorganised data sets at scale is pivotal here. The technology is especially good at spotting anomalies and patterns that could indicate future disruptions, and offering potential solutions quickly.
Successfully implementing a no-touch supply chain planning model requires a combination of detailed analytics, transparent tracking via an application or dashboard, granular and trustworthy data, and standardised procedures across the supply chain. The process also requires a degree of trust and cultural transformation. Experienced teams may initially resist relinquishing many activities traditionally seen as core to supply chain management to digital tools.
McKinsey advises that the best way to manage this shift is to implement a “two-speed IT architecture.” The first is a fast-paced ‘test-and-learn’ environment suitable for rapid prototyping and iterative development. The company then buillds this on top of their existing technology stack.
Users can then develop rapidly, test, and refine new approaches before implementing them in the existing stack. Once new solutions are proven effective, they are migrated to the main technology stack.
If successfully implemented, a low or no-touch method can help supply chains manage industry pain points, optimise processes, and create lasting resilience.
Supply chains that successfully deploy digital technologies like machine learning and generative AI will be better positioned to succeed in our uncertain climate.
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Whenever the global supply chain sector appears to have weathered the latest headwind, another one starts blowing. From shipping disruptions in Panama and the Red Sea to unpredictable consumer behaviour and extreme weather events, supply chains are increasingly under threat.
Far from being an unlucky string of coincidences, the disruptions affecting supply chains today are largely part of larger trends—none of which are harbingers of a more forgiving supply chain outlook in the years ahead. Geopolitical tensions, stoked by economic downturns and growing dissatisfaction with the conditions of modern capitalism are increasing.
Countries and populations in the more vulnerable Global South are alrady feeling the effects of the climate crisis, often with lethal consequences. In the years to come, drought, crop failure, biodiversity collapse, and growing food insecurity threaten to place supply chains under even greater pressure. This is not to mention the increasing scrutiny supply chain operators will face as environmental regulations tighten.
Throughout 2024 and beyond, the supply chains that survive and potentially even thrive will be the ones that can adapt to disruption with agility, turning catastrophe into opportunity as challenges facing them mount.
A new kind of digital transformation
Increasingly digital transformation is the tool being used by supply chain leaders, not just to gain competitive advantage, but to survive in an increasingly hostile world. Additionally, the nature of these digital solutions is shifting, from specialised, standalone systems towards integrated end-to-end solutions.
Diego Pantoja-Navajas, Vice President of New Products at AWS Business Applications observes that “traditional approaches, once the backbone of supply chain management, are now giving way to more integrated and technologically advanced solutions.”
He notes that this shift is “not just a trend but a necessary evolution” now that supply chain leaders face the growing pain points of climate change, geopolitical dynamics, macroeconomic issues, and changing customer behaviour.
What is a digital supply chain?
Digital supply chains represent sets of processes supported by advanced digital technologies like artificial intelligence (AI) and data analytics. These processes, in conjunction with digital tools help businesses make smarter sourcing decisions, predict demand, manage logistics, and handle the relationships between each step in the chain.
Organisationally, traditional supply chains are linear, moving raw materials from one step to another until it reaches the end user or consumer. By contrast, it’s easier to visualise digital supply chains as networks. Unlike traditional supply chains, which are plagued by visibility issues, digital supply chains make it easier to obtain real-time visibility into the performance of each step along the chain.
Digital supply chains increase agility and resistance to disruption
Digital supply chains, enabled by new technologies like generative AI, will allow for much greater visibility into supply chain operations. Not only this, Pantoja-Navajas explains, but it will facilitate the “simulation of supply chain scenarios that illustrate the impact of different supply chain decisions.”
If “environmental, economic, and geopolitical issues, instability can happen at any time and anywhere” then the ability to move with greater speed and agility is critical. Pantoja-Navajas adds: “organisations that utilise a digital supply chain are more likely to increase their resiliency against these disruptions – regardless of when they occur.” Generative AI’s ability to run “hundreds of thousands” of scenarios will make digitally testing supply chains for risk-exposure a much more productive activity.
He concludes that “organisations can use the digital supply chain to make the right decision and then use the physical supply chain to act on that knowledge with speed and certainty.”
Generative artificial intelligence is helping General Mills transition its supply chain model from episodic to dynamic and “always-on”.
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Cereal manufacturer General Mills is embracing generative artificial intelligence (AI) at multiple levels throughout its organisation. In addition to rolling out generative AI chatbots in the form of MillsChat in February, the company is leaning into using the technology to transform its supply chain and procurement functions.
The company has been an especially enthusiastic adopter of the technology. In many ways, this isn’t very surprising. General Mills and companies like it are reliant on far-flung agricultural supply chains. First, the years-long war in Ukraine has destabilised one of the world’s biggest bread baskets. The war is conspiring with the consistently worsening effects of the climate crisis to make life especially challenging.
As a result, General Mills is throwing itself headfirst into an AI-centric transformation, pursuing efficiencies and added visibility.
From episodic to dynamic procurement
By combining enhanced data sets within General Mills’ procurement function, Paul Gallagher, General Mills’ chief supply chain officer said in a recent episode of The GartnerSupply Chain Podcastthat a pilot program managed to realise more than 30% waste reduction in areas where the data has been implemented. As a result, the program is being rolled out across more areas of General Mills’ procurement and supply chain process.
“Historically, we would have rotated through cycles of category should-cost productivity models with potentially missing or delaying savings,” said Gallagher. “Our new reality is that we see this always-on approach driving incremental value, and the ability to react faster [when] we get supplier disruptions or market dynamics change.”
The technology—an AI solution called ELF developed partially by controversial data analytics company Palantir—was initially deployed in General Mills’ U.S. human foods business. The division experimenting with ELF reportedly handles approximately 3,000 orders each day. Over the course of the six month trial, ELF made roughly 400 suggestions to the human foods team. According to Gahhagher, 70% of these suggestions were accepted automatically. The resulting efficiency and productivity gains are, he claims, leading to daily benefits worth tens of thousands of dollars.
“What we’re seeing is that we’re moving from a world where people make those decisions supported by machines to one where the machines make most of the decisions that are guided by people,” Gallagher enthuses. He adds that “this intelligent execution at scale is where we’re seeing the benefits come through to our supply chain.”
Generative AI taking a bite out of the world’s biggest FMCG supply chains
General Mills isn’t the only organisation turning to generative AI in the hope of radically enhancing their supply chain.
Last year, Mars announced plans to explore a wide variety of generative AI applications. “Artificial intelligence has enormous potential to help companies become more efficient and productive and to work at unprecedented scales and speed,’’ a company spokesperson said in an interview with CGT. Mars is already using AI to predict whether cats and dogs could develop chronic kidney disease. It’s also using the technology to help sequence pet genomes to provide individualised nutrition and care. And, of course, AI is helping unlock efficiencies in Mars’ manufacturing operations through digital twin technology.
Colgate-Palmolive is using generative AI as a way to generate internal e-learning documents and automate marketing content creation. Nestle is just one of several large FMCG companies leveraging a generative AI platform called Tastewise. Along with Mars and Campbell’s, among others, it’s using the platform to provide consumer feedback insights and generate recommendations on everything from procurement to product development.
The combination of machine learning with advanced analytics and AI are giving supply chain leaders the ability to proactively anticipate and mitigate disruption.
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The pressures mounting on large, complex global supply chains are immense. From geopolitical conflicts and economic downturn to the intensification of the climate crisis, disruptions are not only becoming more severe, but more common.
Increasingly, supply chain operators appear to be on the back foot.
Manufacturers with complex global supply chains should expect a months-long disruption at least once every 3.7 years, due to “more profound shocks such as financial crises, terrorism, extreme weather, and, yes, pandemics,” McKinsey analysts find.
At the same time, problems securing labour, a global chip shortage, and the rising complexity of the supply chain management process are conspiring to hamper executives’ efforts to meet these challenges. Furthermore, increasing levels of globalisation are creating challenges in monitoring supply networks in real time, obtaining delivery data, and generating actionable insights.
AI and machine learning to cut through the noise
Digital tools look more and more like the solution to supply chain operator’s increasingly reactive approach to an increasingly hostile landscape.
Artificial intelligence (AI) and machine learning have the ability to analyse, organise, and generate insights from complex data sets. These capabilities make the technology especially appealing to supply chain operators. As a result, a recent IBM report found that 46% of supply
chain executives anticipate AI cloud applications will be “their greatest areas of investment in digital operations over the next three years.”
Bob Stoffel, former Senior Vice President, Engineering, Strategy and Supply Chain at UPS, said, “When we talk about supply chain visibility, it does not simply mean visibility into your own supply chain. It means visibility among partners, which enables collaborative decision making closer to the customer.”
This deeper and broader visibility is key to making more effective decisions within the supply chain. Some analysts believe that AI and machine learning will be key to enabling supply chains to transition from a reactive approach to a proactive one.
The AI-powered proactive supply chain
Adopting a proactive approach to supply chain management requires the ability to anticipate and mitigate disruptions, delays, and bottlenecks before they impact the organisation.
AI applications like predictive modelling and real-time monitoring, can help companies optimise their supply chains and gain valuable insights into their own operation, as well as those in their supplier ecosystem and the market at large. This visibility is critical to the task of identifying potential risks or opportunities ahead of time.
By shifting from a reactive stance to a more proactive outlook, organisations can implement more strategic measures to optimise business processes, enhance efficiency, and improve the overall resilience of supply chains.
Proactive supply chains not only ensure uninterrupted operations but also empower organisations to anticipate market fluctuations, customer demands, and emerging market trends. As a result, they are significantly better positioned with regard to their competition and ability to meet customer demands.
Widespread investment into generative AI raises new questions about the technology’s potential to benefit global supply chains.
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Generative artificial intelligence (AI) leapt to prominence last year. The widespread usage of popular large language model powered chatbots (like ChatGPT) and image generators (ie Midjourney) sparked excitement, controversy, and huge capital investment. Since then, adoption has been widespread and investment has been significant.
However, an array of people and organisations have leveled criticism at generative AI and its applications. The problems raised with the technology range from it being simply inefficient and unappealing to downright unethical. If the supply chain sector is to make the most of its investment into the technology, it needs to avoid making the mistakes already befalling other sectors, where generative AI is actively eroding value—usually for a high price tag.
Generative AI’s big year
Funding for generative AI quadrupled in 2023, and as of February 36 generative AI startups had attained unicorn status. Investment in generative AI startups skyrocketed, from $4.3 billion in 2022 to $21.8 billion last year.
Generative AI’s ability to create (the appearance of) new content, such as numerical data, images, text, audio or video has generated a great deal of investment, excitement, and media attention (in addition to a truly shocking amount of pornography). However, finding ways for the technology to make the leap from curiosity to useful (and, more importantly, profitable) business tool is still an ongoing search.
Clickbait, waffle, and 24/7 content farms
Several companies are providing generative AI tools as a way to supposedly enhance the experience they provide. For example, Ebay has started giving the option for sellers to use AI to automatically generate item listings. However, users have criticised the service for surrounding basic information with overly flowery, poorly phrased “waffle.”
Similarly, AI leveraged to churn out news articles and blog posts as part of a new wave of automated content farms has also faced criticism for flooding the internet with “low quality” articles and “clickbait.” The problem is escalating rapidly, as well, with a recent study conducted by researchers at the Amazon Web Services (AWS) AI Lab finding that a “shocking amount of the web” is already made up of poor-quality AI-generated and translated content.
In short, critics of the technology believe generative AI fails to bring any real value to the areas where it is being deployed. The fact that 40% of supply chain organisations are already investing in generative AI begs the question: what are they planning to use it for? Will it add value to the business?
More pertinently, are there applications for generative AI that actually can add value to the business? Or, is this tech adoption for its own sake going to hurt the organisations that embrace it like it hurt all those kids who wanted a nice weekend out at a Willy Wonka themed experience in Glasgow?
What can generative AI actually do for the supply chain?
The main issue with the more widely known generative AI platforms like ChatGPT is that their outputs are only as good as the data used to train them. Most chatbot AIs currently available to the public are generalists, trained on huge amounts of (stolen) data.
However, if trained on the right, thoroughly vetted data, generative AI can be a useful tool for analysing large, unstructured sets of information. It can rapidly classify and categorise information based on an array of visual, numerical or textual data formats. Then, it can take those large volumes of data and summarise them, extracting key insights and trends. The technology could also potentially assist in quickly pulling relevant information from those datasets in order to provide instant responses by voice or text, which might be useful in allowing workers with a lower level of technical skill to perform higher level tasks.
It can also quickly analyse and modify strategies, plans and resource allocations based on real-time data—much faster, with a much broader pool of information than a human.
Generative AI could also automatically generate content in various forms that enables supply chain managers to automate vendor negotiations according to a preexisting script and set of parameters.
However, it all depends on the quality of the model being used and the quality of the data. Without adequate oversight, direction, and scrutiny, generative AI will erode more value from the supply chain than it creates.
Advanced data analytics are a necessary tool in the fight to predict and avoid increasingly common supply chain disruptions by the climate crisis.
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Extreme weather events are disrupting global supply chains, and the problem is only going to get worse. If organisations are going to build climate-adaptive supply chain models, supply chain leaders need to harness the potential of big data analytics to create the adaptability, flexibility, and resilience required in the face of increasingly hostile and deadly environmental conditions.
Extreme weather drives food insecurity and puts pressure on supply chains
In August of last year, severe flooding killed 29 people and caused “tens of billions” of dollars worth of economic damage in the northern Chinese province of Hebei. In addition to the loss of human life, the floods severely impacted regional food production chains. A single extreme weather event impacted more than 2.5 million acres of farmland.
Extreme weather events like this are becoming an increasingly common side effect of our collapsing climate. In 2023 alone, climate disasters directly claimed the lives of more than 12,000 people. Every year, the climate crisis will cause more intense, severe, and long-lasting extreme weather events such as hurricanes, floods, droughts, freezes, and wildfires.
Extreme weather events are going to continue severely disrupting global supply chains. The consequences of the resulting food insecurity, loss of access to critical supplies, and social unrest as the result of economic stagnation will be appalling.
Even countries with relatively low food insecurity like the UK could see civil unrest in a relatively short amount of time due to the effects of worsening weather.
If supply chains fail, so does everything else
A 2023 study found that “food shortages stemming from extreme weather events could potentially lead to civil unrest in the UK within 50 years.” In particular, supply chain disruptions leading to shortages of staple carbohydrates like wheat, bread, pasta and cereal “appear to be the most likely triggers of such unrest.”
If these extreme weather events, combined with rising sea levels, disrupt supply chains over the coming decade, the effects will be severe. A report released by sustainability focused consulting company Ramboll argues that “disruptions in the supply chain interrupt manufacturing, production, and delivery of goods, raising costs of materials and prices of products and hurting corporate revenues. With climate change posing such imminent risks of disruptions, supply chains must begin preparing to become resilient and climate adaptive.”
Climate-adaptive supply chains built on data
Visibility is the first step towards building a more resilient supply chain. Data is the most useful tool that professionals have at their disposal in order to achieve it.
“In the current environmental climate, with extreme weather becoming the norm, organisations must become more agile to beat the disruption and avoid lasting impacts; data insights are key to this,” argues Renaud Houri, EVP of International Markets at project44. He stresses that, “as if the economic crisis was not enough to worry businesses, the spike in extreme wet weather is heightening pressures for supply chains and retailers alike and now it is fight or flight.”
Supply chain mapping, in conjunction with using data analytics to monitor changing weather patterns and macroeconomic trends, can create meaningful visibility for supply chain operators.
“With better visibility comes better planning, and predictive insights are the first line of defence for delay mitigation,” Houri says. He also advocates for the application of AI and artificial intelligence to transform data into insights for the future.
“Intelligent tracking data can be used to proactively detect issues before they happen. Delay and exception risks across all carriers are identified using machine learning, pre-empting negative delivery experiences. Associated changes to staffing demand can also be predicted and addressed,” he explains. “In layman’s terms, this means businesses have a holistic view of their operations to make better, faster decisions in the face of weather disruption, therefore resulting in superior on-time deliveries.”
If supply chains intend to weather the coming storm of disruption, they need to leverage their data into a holistic understanding of their operations and use cutting edge technology to stay ahead of one unfolding disaster after another.
Automation has the potential to help solve some of the most pressing challenges facing the supply chain sector in 2024.
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Ever since the COVID-19 pandemic threw global supply chains into chaos, it seems as though supply chain leaders have been fighting to find a way back to normality.
However, if the last four years have demonstrated anything, it’s that the stability, speed, and predictability of pre-2020 supply chains are a thing of the past. Resilience, efficiency, adaptability are the new cardinal virtues of an industry fighting on multiple fronts—against economic unrest, geopolitical conflict, and the climate crisis.
Supply chains are experiencing serious pain points as they try to stay afloat while restructuring to be more agile and resilient. Many are turning to automation as a potential solution to some of the most common problems affecting supply chain organisations.
Among different types of automation, supply chain managers are increasingly turning to robotic process automation (RPA) for its ability to alleviate supply chain pain points.
“RPA serves as a driving force for process improvement and task automation, covering everything from order processing to inventory management. The adoption of RPA software in the supply chain marks a significant shift towards improved visibility, precision, and speed,” says Alina Filatova, Head of BA Department at Innowise. “These elements are essential for attaining excellence in logistics. This integration acts as a vital link, bridging the gap between conventional logistics methods and the growing needs of today’s supply chain landscape.”
Siloed data and legacy systems
Despite ongoing digital transformation efforts, many of today’s supply chains are mired with siloed organisational structures and legacy technology. Vital aspects of organisational procedure all too often rely on emailing spreadsheets and PDFs back and forth. Relying on these methods to track and utilise often critical information creates silos, inefficiencies, and reduces the potential for collaboration.
On top of that, ERP systems can lack the flexibility to support more agile, fast moving businesses. This results in wasted labour as supply chain professionals spend time moving documents around, inputting data across multiple digital platforms, and otherwise performing repetitive, error-prone tasks.
By using an RPA tool to automate data entry, simple communications between supply chain staff and other stakeholder, and standardise information across all platforms, supply chain operators can dramatically increase efficiency and reduce errors.
For instance, an RPA tool can handle the whole process of updating customers about their order status faster than a human. It can automate multiple tasks involved in processing, checking, and tracking orders by pulling data from different systems. It can then monitor those orders based on predetermined sets of rules, and provide customers with real-time updates.
This has the potential to reduce the amount of manual work being performed, increases the accuracy of orders, and gives better visibility across multiple otherwise siloed and legacy elements of the supply chain tech stack.
Automation can increase efficiency and reduce human error at a time of unprecedented disruption for the supply chain sector.
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More than anything, the global supply chain industry craves consistency, predictability, and security. In a recent survey of supply chain leaders, Gartner found that just 9% of respondents expected to achieve revenue gains due to uncertainty, and 63% of respondents expected a loss of revenue due to exposure to uncertainty.
In a climate defined by disruption and uncertainty, automation could provide the resilience that supply chains need to overcome challenging market conditions.
A market defined by disruption and rising costs,
Supply chains face a complex and challenging geopolitical and economic outlook. Additionally, long-overdue labour organising efforts in markets traditionally hostile to unions like the US are starting to gain traction.
“Over the last three to six years, the workforce that you want to employ in your logistics facility has just become much, much more expensive. I don’t see any end to that trend, and it results in a significant problem for those of us who need to run large logistics operations. And not only is the labour rate increasing, the number of people who want to do logistics work is decreasing,” he said.
Increasingly, supply chain leaders are turning to automation to combat the economic pressures and uncertainty they face.
Automation grows in the supply chain
Supply chain automation has the potential to improve operational efficiency by reducing human error and speeding up clumsy manual processes. Automation in the supply chain can encompass several technologies, including digital process automation, robotic process automation, artificial intelligence, and machine learning.
While most supply chains have developed pockets of digitalisation over the last decade or more, it’s not uncommon for these areas of the supply chain to be siloed from one another. One of the key benefits of automating supply chain processes is the connective tissue that automation solutions create between different areas of the supply chain.
Supply chains are going to continue to implement new digital tools, so having an automation layer in place will be highly beneficial in ensuring those layers can seamlessly interconnect.
Currently, many supply chains are not integrated and optimised for a fully digital workflow. Even those that are frequently struggle with a lack of digitalisation in their supplier ecosystem.
Essential processes still frequently rely on humans extracting, inputting, and sharing data via spreadsheets, PDFs and emails. Without automation and AI-powered tools, many ERP systems lack the ability to automatically incorporate data from disparate and legacy formats. This means that manual data entry is still a significant part of the supply chain professional’s job.
The upshot is that, not only are supply chain professionals often performing repetitive, easily automated tasks by hand, but these are the kinds of tasks that most easily lend themselves to human error, often with costly results. “Supply chain automation is a transformative force. It’s revolutionising the way businesses operate, offering numerous benefits, including enhanced efficiency, cost savings, improved customer service, and a positive impact on sustainability,” notes a spokesperson for GEP.
Extreme weather and biodiversity disruption threaten our global food supply. Our ability to analyse and predict events may provide protection for our supply chains.
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Extreme weather events are 2024’s biggest supply chain risk. A report by Everstream Analytics found that climate crisis-related disruptions like hurricanes and extreme heat were the top threat predicted to disrupt supply chains this year.
It’s an obvious and natural progression, seeing as 2023 saw more extreme weather-related disruptions than any year before. Heavy rains and flooding impacted California, Nevada and Utah early last year. As a result, shipments in areas where transportation systems were disrupted dipped by 20% to 30%.
Currently, shipping moving through the Panama Canal has been cut in half by a drought. Historic lack of rainfall has lowered water levels at critical points along the waterway. As a result, ship captains stuck in weeks-long lines are being forced to choose whether to sail around the tip of either South America or Africa, or to pay as much ad $4 million to jump the queue.
Eating into supply chains and food supplies
These delays and extreme weather disruption are especially disruptive to food and agricultural supply chains. Given the perishable, delicate nature of crops and globally plummeting biodiversity, the climate crisis poses unprecedented risks and disruptions to global supply chains,” says David Nickell, Vice President Sustainability & Business Solutions at dsm-firmenich Animal Nutrition & Health. He adds, however, that “this holds doubly true for the agriculture and food sectors.”
Climate change is already affecting food security at the global, regional, and local level. Changes in climate can severely disrupt food production and reduce access to food. Not only this, but the changing climate can also affect food quality and nutritional content. The United States EPA noted in a recent report that food insecurity likely to be exacerbated by extreme weather events. The report also notes: “spikes in food prices after extreme events are expected to be more frequent in the future.” Lastly, they add that “increasing temperatures can contribute to spoilage and contamination.”
An over-globalised food supply chain
These disruptions highlight the cracks already appearing in an over-globalised, delicate food supply chain. The EPA observes that even a single climate-related disturbance to food distribution and transport could significantly disrupt not only the safety and quality of food, but also food access. “For example, the food transportation system in the United States frequently moves large volumes of grain by water. In the case of an extreme weather event affecting a waterway, there are few, if any, alternate pathways for transport,” they note.
Around the world, extreme weather is disrupting our ability to maintain existing supply chains. Nickell adds that the problem will only be exacerbated as supply chain managers are forced to “look for new methods to address the challenges of changing environmental conditions, evolving consumer buying behaviours and increasing demand for animal protein, which is expected to grow 60% to 70% by 2050, driven by population growth and greater affluence in developing economies.”
Hungry for climate data
One of the biggest challenges is that food supply chains can’t just be maintained in the face of climate disruption. At the same time, these systems must be decarbonised to avoid further devastation of the environment.
For companies throughout the food value chain, the majority of their environmental impact stems from Scope 3 emissions. These are emissions tied to farming, ranching, land clearance, and other activities further up the supply chain. These, Nickell adds, are the most complex part of the carbon footprint of food production.
A potential solution, he argues, is better data. “Data-based technologies and advanced Life Cycle Assessment platforms have become pivotal tools to enable scalable measurement and reduction of emissions, enhancing transparency and trust, building supply chain resilience, and driving positive, sustainable outcomes,” he notes.
One application for this technology, he continues, is in the animal protein supply chain. Here, “the ability to capture and analyse granular, feed and farm-level data at scale is fundamental,” Nickel says. “To be useful for measurement and for improving sustainability, that data must cover a product’s full life cycle from farm to fork, be easily shareable, scalable and tailored to various needs, whether at the product or company level.”
Lastly, he adds: “By leveraging the latest, leading technologies and data-driven solutions… the food industry can work towards reducing its environmental impact and meeting the growing demand for sustainable food in a scalable and credible manner.”
