A joint report from GEP and the University of Virginia’s Darden School of Business indicates that most supply chain AI projects fail to reach full-scale implementation. While over half of surveyed supply chain professionals report some usage of AI, fewer than one in 10 have scaled their pilots into enterprise-wide operations. Additionally, 74% of organizations are stuck in the planning phase, and previous reports estimated that as many as 95% of AI investments were stalling out.

The researchers surveyed 180 senior supply chain executives across 12 industries and determined that the primary barrier is not the technology itself, but a lack of supporting business processes. Projects frequently sputter when top-down initiatives meet internal operational resistance or when companies attempt to layer AI over dysfunctional legacy systems. The report emphasizes that failing to treat AI implementation as an “operational transformation” (fundamental change to business workflows) leads many projects into a state of stagnation.

Success requires a portfolio approach, where multiple projects are managed on different timelines, and the direction of a dedicated steering committee to oversee multi-functional opportunities. The “performance elite,” as researchers labeled them, successfully combine AI specialists with frontline staff skilled in process management. The report concludes that effective stakeholder engagement and a well-prepared workforce are currently more significant competitive advantages than the models themselves.

A joint report from GEP and the University of Virginia’s Darden School of Business indicates that most supply chain AI projects fail to reach full-scale implementation. While over half of surveyed supply chain professionals report some usage of AI, fewer than one in 10 have scaled their pilots into enterprise-wide operations. Additionally, 74% of organizations are stuck in the planning phase, and previous reports estimated that as many as 95% of AI investments were stalling out.

The researchers surveyed 180 senior supply chain executives across 12 industries and determined that the primary barrier is not the technology itself, but a lack of supporting business processes. Projects frequently sputter when top-down initiatives meet internal operational resistance or when companies attempt to layer AI over dysfunctional legacy systems. The report emphasizes that failing to treat AI implementation as an “operational transformation” (fundamental change to business workflows) leads many projects into a state of stagnation.

Success requires a portfolio approach, where multiple projects are managed on different timelines, and the direction of a dedicated steering committee to oversee multi-functional opportunities. The “performance elite,” as researchers labeled them, successfully combine AI specialists with frontline staff skilled in process management. The report concludes that effective stakeholder engagement and a well-prepared workforce are currently more significant competitive advantages than the models themselves.