Our new article series, “The Path to AI-First Procurement: Closing the Gap Between AI Ambition and Execution,” based on new research from Ardent Partners and sponsored by Ivalua, continues today with a look at how procurement’s AI journey is being constrained less by a lack of interest in AI than by the tactical workloads, fragmented processes, legacy systems, and data challenges consuming organizational capacity. The path to AI-first procurement therefore begins with reducing that operational burden, thereby creating capacity for higher-value work and enabling greater speed, intelligence, and strategic impact.
The Foundation Problem
When I look at procurement’s readiness for AI, the data foundations reveal just how significant the operational challenge remains. Only 11% of organizations report having a unified procurement data model across the source-to-pay process. Another 41% describe their data as integrated, but still rely on manual reconciliation across systems. Just as concerning, 40% continue to operate with fragmented data, where sourcing, contracts, supplier information, and transactional activity remain disconnected. For another 8%, much of their procurement intelligence remains trapped in unstructured documents, PDFs, and emails.
The AI planning horizon also remains relatively short. Nearly half of organizations report that they have no formally defined AI investment horizon today. Among those that do, the average planning horizon is approximately 1.8 years. To me, that suggests that while procurement’s AI momentum is real, much of the market is still navigating without a fully developed operational blueprint.
The prioritization of AI in technology selection reinforces that commitment. Nearly three quarters of organizations are prioritizing AI capabilities when evaluating procurement technology, signaling that leaders understand the importance of intelligent capabilities even as the underlying foundations remain uneven.
What concerns me is the gap between that ambition and the operational environment in which AI must function. Most procurement organizations are still operating with significant constraints around data visibility, consistency, and accessibility. AI can accelerate analysis and execution, but intelligent systems depend on connected data, integrated workflows, and reliable operational continuity. When those foundations are fragmented, scaling AI reliably becomes much harder.
I believe procurement has largely settled the question of whether AI belongs in the function. The harder question now is whether the foundation beneath it is ready to support the scale and intelligence that leaders expect.
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