Bringing it to life: Beroe’s approach to AI-enabled procurement

In the penultimate chapter of Beroe’s Future Vision report, “Artificial Intelligence: Real Decisions”, we explore embedding intelligence into the very fabric of how procurement teams work. It isn’t about flashy features, temporary fixes, or experimental pilots; it’s about building AI that can deliver ongoing real value. 

Rather than treating it as a bolt-on tool, solutions should be designed to use AI as an operating layer grounded in trusted data, trained on procurement-specific knowledge, and delivered directly into existing workflows. From conversational interfaces to embedded dashboards and dynamic content formats, intelligence has to be accessible, actionable, and intuitive. Architectures must be built around human-machine collaboration, with a Human-in-the-Loop model that ensures transparency, trust, and continuous learning.  

 With every AI capability mapped to a real-world use case, ensuring that the technology serves enhanced decision-making, procurement teams can be faster, smarter, and more effective. 

Beroe’s approach to AI-enabled procurement 

While many AI initiatives stall at the proof-of-concept stage, Beroe has taken a fundamentally different approach by designing intelligence not as a feature, but as an operating layer across the procurement function. 

Our philosophy is simple, AI works best when it’s grounded in trusted data, trained on domain-specific knowledge and delivered in ways that align with how and where procurement teams already work. 

Here’s how we do it: 

A trusted, fit-for-purpose data foundation 

Beroe brings together proprietary intelligence, curated external sources, and contextual enrichment to ensure that the data feeding AI models is complete, consistent, and tailored for procurement. This ensures that AI recommendations are built on facts, not assumptions.  

Domain-trained AI models purpose-built for procurement 

One-size-does-not-fit-all. Beroe’s AI capabilities are trained on procurement-specific data and tuned to procurement- specific decisions. This results in more relevant, explainable, and action-ready outputs. These models are not retrofitted from general-purpose AI. They are natively designed to support sourcing, supplier management, category strategy, and risk mitigation. 

Seamless, embedded delivery into procurement workflows 

Intelligence doesn’t drive action unless it reaches the right person, at the right time, in the right format. That’s why Beroe delivers AI outputs through a conversational interface, Abi, that answers natural-language queries with contextual insight, integrated widgets, and dashboards within platforms like Slack and Microsoft Teams, and dynamic content formats, including executive briefings, supplier snapshots, and audio digests. The result is that procurement professionals don’t need to adapt to the technology; the technology adapts to them. 

Human + machine collaboration by design 

Beroe’s architecture is built around human-in-the-loop intelligence. Intelligence-driven procurement isn’t about replacing analysts; it’s about amplifying them. AI performs the heavy lifting of data ingestion, filtering, and recommendation while human experts provide validation, nuance, and override authority. Meanwhile, feedback loops 

continuously improve model accuracy and relevance. This hybrid model ensures trust, accountability and continuous learning – both for humans and machines.  

Practical use case deployment, not AI for AI’s sake 

Every capability in Beroe’s AI stack is mapped to a clear procurement use case, with measurable outcomes:  

This ensures that AI is always in service of decision-making – not a layer of complexity. 

Beroe’s approach to AI is grounded, focused and results-driven, and equips procurement professionals with the tools they need to make faster, smarter, and more strategic decisions without compromising control, clarity, or confidence. 

“Artificial Intelligence: Real Decisions” explores how leading procurement teams are using AI today to strengthen decision-making across key domains spanning insight generation and risk forecasting to supplier engagement and strategic sourcing.