As AI continues to dominate conference stages and boardroom discussions, the pressure to use it is everywhere. As this technology becomes further embedded in enterprise strategy, many organisations are still grappling with how to apply it in a way that delivers real, measurable value.
Rather than focusing on AI for the sake of innovation, the question now is how to align new tools with real business problems. That means looking beyond dashboards and pilots to deploy AI where it can simplify decision-making and improve processes.
At Beroe, this principle is central to how AI solutions are developed, deployed, and scaled. As the company behind the world’s leading procurement intelligence platform, Beroe provides real-time market data, cost analysis, and supplier risk assessments, empowering thousands of organisations globally to streamline operations and mitigate risks. Its latest advances in autonomous negotiation, supplier discovery, and predictive analytics show what it means to align AI with business objectives.
Speaking with Prerna Dhawan, Chief Product Officer at Beroe, during this year’s DPW New York conference, the discussion explored how procurement leaders can move beyond hype and start unlocking the full potential of AI.
Misalignment with business needs
There are plenty of real-world examples of how AI can improve efficiency within a business, from automating manual tasks like invoice processing to identifying new suppliers based on complex sourcing criteria. Accessing this technology is easier than ever with a wide range of tools available to procurement professionals. It can be tempting to jump on the bandwagon and integrate AI across every area of an organisation, but success requires a more nuanced approach.
The key is to ask the right questions, Dhawan explains: “We talk about all the latest and greatest technology out there, but what does it mean in practical terms? We need to ask, ‘How can I apply it today in the work I am doing as a head of product or as a procurement professional?’”
The allure of generative AI is especially strong, but business leaders should ask whether that’s the right solution for their needs. As with any decision, it’s important to consider the business problem. “It starts with a little bit of knowledge about what you’re looking for,” says Dhawan. “What are some of your biggest challenges, and which of those challenges could AI technology solve?”
Matching the right tool to the job
Once an organisation has identified a specific problem, it’s possible to find the AI solution that fits. While generative AI gets a lot of attention, other AI technologies and machine learning based systems might be more appropriate.
In some cases, prescriptive, rule-based, or predictive AI could be a better choice to solve a problem without the need for a large language model. For example, forecasting commodity prices doesn’t require generative AI, just strong, contextual machine learning.
“We are looking at AI across two dimensions,” says Dhawan. “Firstly, what is our offering to customers, in terms of procurement intelligence and autonomous negotiation technology. Second, we are looking at AI internally. Let’s say in product development, how do we use the latest AI solutions to accelerate our product development cycles so we can release new modules and capabilities more quickly.”
Regardless of the type of tool chosen, it should cover a high-impact use case. Integrating AI to solve a problem that only surfaces for a small group of people a couple of times a year won’t have a great return on investment. Instead, look for regularly occurring problems that, if fixed, could have a huge impact on productivity or quality.
Reducing the cognitive load
We’re already bombarded by information, and the use of AI to add to this doesn’t make sense. “I don’t need another dashboard in my life,” says Dhawan.
When implemented correctly, AI can make data more accessible while reducing cognitive load for users. The result is increased productivity and faster decision-making.
“I think the power of AI is to simplify access to data. This is why ChatGPT has been a success: it democratises access to information. That’s what our B2B technology world is waiting for. It gives me something simple that allows me to talk to my data. Then I can focus on what insights I need to make a decision or take action.”
For most B2B users, the key is intelligent simplification. Look for ways to simplify access to data through agent AI tools and conversational interfaces. This brings the focus back to action rather than dashboards.
Inside Beroe
While many procurement teams are still exploring AI’s potential, Beroe has already embedded it across both its platform and internal operations. The company, founded in 2006, provides procurement intelligence to thousands of organisations worldwide. Its platform delivers the critical data that professionals need to make informed sourcing decisions, from commodity prices and risk indicators to ESG scores and supplier intelligence.
“We provide all data that procurement needs for decision making, whether it’s cost data, risk data, ESG data or price data,” says Dhawan. “Our reimagination of the future is not just giving access to more data but creating that layer of recommendations that help you make decisions at speed and scale.”
One of the clearest examples of this in action is Beroe’s new ‘autonomous negotiations’ platform resulting from its recent acquisition of negotiation technology business, nnamu. Delivering a significant evolution in the procurement technology landscape the platform enhances the foundational elements of AI and game theory with Beroe’s industry-leading market intelligence and, according to Dhawan, it’s being deployed successfully in live sourcing scenarios.
“This is a technology that is being used for multilateral negotiations,” Dhawan explained. “It’s no longer just a POC or prototype, it’s live and being used at scale.” These new tools reflect Beroe’s core mission: to help procurement professionals minimise surprises and maximise margins.
Crucially, Beroe isn’t waiting for perfect data to apply these technologies. Instead, the company is using AI to work with what’s available — cleansing, interpreting, and extracting value from both structured and unstructured sources.
“You can use AI for cleansing data – even paper contracts,” Dhawan says. “Historically, we thought data had to be structured. But now, with vision models and image analytics, that’s no longer the case.”
Rather than striving for 100% accuracy before taking action, Beroe embraces a more agile mindset that balances speed and precision.
Is mindset holding procurement back?
The technology is ready. The use cases are proven. So why do so many procurement teams still hesitate to embrace AI? “There’s this subconscious fear that I think is a barrier to adoption,” she said. “And to some extent, it’s to do with our friends in Hollywood.”
There’s the myth that AI is a job-threatening black box, especially in industries where trust and experience are the backbone of good decision-making. For procurement, where professional judgement and business context are critical, the idea of handing over tasks to AI can feel risky.
But Dhawan believes this fear is misplaced. At Beroe, AI isn’t replacing procurement professionals, it’s augmenting them. Whether it’s surfacing new suppliers, automating elements of negotiation, or flagging risks earlier in the sourcing cycle, the aim is to enhance human decision-making. She says: “I think with the new kinds of AI technology that’s available to us, it is an opportunity for us in B2B tech to embrace more human-centred design with higher focus on UX.”
Looking ahead
Looking ahead to 2026 and beyond, Dhawan sees procurement evolving into a more personalised and responsive function – one where AI plays a critical role in both strategy and execution.
“We see hyper-personalisation coming, both in supplier relationships and internal stakeholder engagement,” she explains. “AI will be at the centre of that.”
Rather than one-size-fits-all sourcing strategies, AI will enable procurement teams to tailor their approaches to specific business units, categories, or even individual suppliers. This means smarter segmentation, more relevant insights, and stronger commercial outcomes.
Another key shift is the growing ability to connect macro events, such as geopolitical shocks or regulatory changes, with micro actions inside the business. AI can help procurement teams identify these signals earlier, respond faster, and still align with long-term goals such as cost efficiency or sustainability.
“It’s about balancing your fire-fighting reactions to market events with your long term goals and strategy,” says Dhawan. “Procurement needs visibility and flexibility at the same time.”
Beroe is already moving in this direction. Alongside its growing AI capabilities, the company is refining how it delivers intelligence, building agents and recommendation layers that not only inform decisions, but also help teams take action on them. Whether that means automating routine negotiations or proactively flagging supply risks, Beroe is evolving to meet the needs of a procurement function that’s more dynamic than ever.
As Dhawan points out, the goal isn’t to overwhelm teams with more tools, it’s to make their lives easier. “It’s about reducing complexity and giving procurement professionals confidence in what to do next,” she concludes.
For many procurement leaders, AI still feels like a long-term ambition. But the solutions are already here, and through companies like Beroe, they’re already in use. The challenge now is not whether AI can deliver value. It’s whether teams are ready to adopt the mindset and cultural shift that will allow them to unlock that value.
- AI in Procurement