Top 5% of supply chain ai initiatives achieve breakthrough gains

CLARK, N.J., May 20, 2026 /PRNewswire/ -- A small elite group of companies has cracked the code on scaling AI in supply chain operations, delivering triple-digit productivity gains, faster response times and lower error rates, according to new joint research from GEP and the University of Virginia's Darden School of Business.

The GEP–UVA Darden study, based on surveys and interviews with senior executives at nearly 200 large enterprises, finds that while AI experimentation is nearly universal, only about 5% of supply chain AI initiatives have successfully moved beyond experimentation to enterprise-wide scale.

The research reveals a stark 'scaling gap': while 5% of initiatives have successfully industrialized, the vast majority remain stalled. Specifically, 22% are caught in the pilot phase, and 74% are either stuck in planning or have no formal roadmap for execution, leaving a significant divide between AI potential and operational reality.

The barrier is not budget, AI and agentic capabilities. It is management discipline.

"Most companies aren't failing at AI because of the technology," said Michael DuVall, Global Head of Strategy at GEP and co-author of the study. "They're failing because they're automating broken processes. The companies seeing outsized gains redesign how work gets done, put real governance in place, and hold AI to clear business outcomes before scaling."

What the 5% Elite Performers Do Differently

The organizations behind the top 5% of initiatives that have moved beyond pilots to operational scale, share several measurable characteristics:

1. Formal governance: Companies that scaled AI are significantly more likely to operate with a dedicated AI steering committee that ties funding directly to enterprise value delivery.
2. Portfolio discipline: Rather than approving isolated experiments, successful companies manage AI initiatives as a structured portfolio — progressing use cases deliberately from evaluation to pilot to scale.
3. Auditability and transparency: AI scalers document system logic through digital audit trails at materially higher rates than their peers, reinforcing trust, compliance and accuracy.
4. Workforce alignment: Organizations that have scaled AI are two to three times more likely to modernize elements of their talent strategy, redefining roles and aligning incentives to AI-enabled operating models.

In one documented example cited in the research, a standardized purchase requisition validation process enabled approximately 80% of transactions to auto-clear and drove triple-digit productivity improvements within weeks of deployment.

The GEP–UVA Darden research initiative was designed to combine frontline supply chain practice with academic rigor, examining not just where AI is being deployed, but why some organizations are able to industrialize it while others stall.

The full report, Why Operational Discipline Determines Agentic AI Success, is available HERE.

To learn more, visit www.gep.com/quantumintelligence.