Supply Chain AI Gap: 83% of Leaders Face Workforce Unpreparedness Challenge

While 91% of organizations plan to use AI to augment human workers, 83% say their employees are unprepared to use AI effectively, according to The People Paradox in Supply Chain AI Integration, released by the Association for Supply Chain Management (ASCM) and the Digital Supply Chain Institute (DSCI).

“AI adoption in supply chain is more about people than it is technology,” says ASCM CEO Abe Eshkenazi. “The organizations making real progress treat workforce readiness as part of the technology investment, not an afterthought. They learn by doing, bring managers into the process early, and build trust one function at a time.”

“Leaders have accepted AI in principle. What most organizations haven’t built yet is the capacity to execute it in practice,” says Marko Kovacevic, managing director of DSCI. “With tariff shifts, demand shocks and geopolitical disruption, the advantage will go to companies that can sense and re-plan fastest. That makes AI readiness a management challenge first and a technology challenge second.”

Key takeaways:

·       The research finds that the biggest obstacles to scaling AI are not executive skepticism or a lack of buy-in. Instead, organizations face four business hurdles: an unready workforce, an inability to trust AI to act autonomously, cybersecurity concerns, and persistent difficulty proving return on investment.

• 83% of respondents say their employees are unprepared to use AI effectively, and only 14% say their organizations are fully prepared for an AI-augmented future. Just 7% expect AI to directly replace workers, while 51% expect it to shift people toward higher-value decision-making and 40% expect new roles to emerge.
• Across 13 core supply chain functions, average AI adoption scores just 1.94 on a five-point scale ranging from no use (1) to fully autonomous execution (5). Planning leads, with demand planning at 2.28 and supply and inventory planning at 2.12, while execution-heavy functions trail. Reverse logistics ranks lowest at 1.59.
• 82% of C-suite leaders actively lead, implement or scale AI initiatives, but direct leadership drops to 12% at the director level. Half of directors, 51% of managers, and 70% of staff say they are aware of AI initiatives without being actively involved.
• 17% of organizations with an AI-ready workforce have put AI to work across an average of six supply chain functions and report a 71% project success rate. Among unprepared organizations, 64% remain stuck in pilot or planning stages, with a 28% success rate.
• The most cited barriers are a tie between a lack of workforce skills and resources (33%) and an unclear business case or return on investment (33%), followed by poor data quality (25%).
• 92% of leaders express significant concern about cybersecurity risks introduced through AI-enabled suppliers and trade partners, yet organizations have implemented an average of just 2.3 of six standard security practices. Only 28% maintain AI-specific incident response plans, and 24% use system segmentation to contain breaches.
• 91% demand transparency into how AI models generate predictions and recommendations, while 43% express concern about algorithmic bias in supplier selection or inventory allocation.
• More than half of leaders (55%) describe their AI deployments as “somewhat successful,” reflecting isolated wins rather than broad operational change. Over the next two years, leaders expect the biggest payoffs to come from faster decision-making through shorter planning cycles (46%), lower overall supply chain costs (42%) and higher process automation rates (40%).