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.
- AI in Supply Chain
- Risk & Resilience
