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Where Does Your Procurement Organization Sit on the AI Maturity Curve?

IDC’s Patrick Reymann breaks down the stages of AI maturity—and what separates leaders from laggards as agentic systems scale across procurement.

AI has arrived in procurement, but not all organizations are evolving at the same pace. In this PLaN session, Patrick Reymann, Research Director at IDC, presents a clear framework for assessing procurement’s AI maturity—and identifying the capabilities required to advance to the next level.

Patrick outlines IDC’s AI Maturity Model, highlighting the five stages organizations pass through as they move from experimentation to scaled, autonomous operations. He explains why most procurement teams remain stuck in early stages: fragmented data, siloed tools, unclear ownership, and workflows built for a pre-AI world.

This session explores what separates leaders from the rest. Mature organizations build AI-ready architecture, integrate cognitive capabilities across intake and sourcing, implement governance early, and shift human roles toward oversight, scenario evaluation, and risk management. They move from task automation to decision augmentation, and eventually to outcome automation.

Patrick provides examples of where AI is adding value today—supplier risk detection, intake intelligence, contract analytics, forecasting, autonomous sourcing—and where the next wave of gains will emerge as agentic systems mature.

 

This is an essential session for any procurement, IT, or transformation executive looking to evaluate AI-readiness, benchmark their roadmap, or understand the organizational investments required to stay competitive.

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Procurement AI Adoption Index 2025 - 26: From Pilots to Procurement Autonomy
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