Understanding Why Agentic AI Initiatives Stall The Top 3 Pitfalls Behind Failed Agentic AI Initiatives in Procurement

A MUST-READ FOR PROCUREMENT PROFESSIONALS

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Understanding Why Agentic AI Initiatives Stall

Agentic AI promises autonomy and speed in procurement. But for many organizations, those ambitions stall before delivering real value.

So where do agentic AI initiatives really break down?

Poor data quality contributes to 80% of AI project failures, shows new research by Procurement Leaders, sponsored by GEP. At least 67% of companies say legacy systems are holding back AI adoption.

This research report examines the three most common hurdles that prevent procurement teams from moving from experimentation to execution and outlines how data quality, technology foundations, and internal readiness allow agentic AI to scale.

If you’re planning for agentic AI and looking to avoid costly missteps, this paper is essential reading.

Why Read This Paper

Fragmented Data Foundations

Why disconnected, inconsistent data undermines well-intentioned AI initiatives

Technology That Can’t Keep Up

How legacy systems and weak integration limit agentic AI’s ability to act in real time

Internal Readiness Gaps

What skills, roles and change are required to support agentic execution

What It Takes To Scale Agentic AI in Procurement — Download Now

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