Why are companies keeping AI in pilot mode instead of scaling?

According to the survey, 64% of organizations with unprepared workforces remain in pilot or planning stages. The research identifies workforce skills gaps (33%) and unclear ROI (33%) as the top two barriers. ASCM CEO Abe Eshkenazi notes that companies are using AI primarily for analysis and predictions, treating it as a 'glorified spreadsheet' rather than leveraging its potential for autonomous execution of routine transactional decisions.

What is the success rate difference between prepared and unprepared workforces?

Organizations with workforce readiness for AI report a 71% project success rate, while those without report only 28%. Of the 107 survey respondents meeting analysis criteria, 83% indicated their employees are unprepared to use AI effectively, representing a significant competency gap across the supply chain industry.

Which supply chain functions are least advanced in AI adoption?

Planning functions lead adoption with demand planning at 2.28 and supply/inventory planning at 2.12 on a 5-point scale. Execution-heavy functions trail significantly, with returns and reverse logistics ranking last at 1.59. This pattern reflects the industry's preference for using AI as an analytical tool rather than an autonomous decision-maker.

What cybersecurity risks does AI integration introduce?

The survey found that 92% of respondents expressed significant concern about cybersecurity exposure through AI-enabled suppliers and partners. However, the average organization has adopted only 2.3 of six standard cybersecurity practices. Eshkenazi notes that post-pandemic visibility initiatives connecting suppliers on shared platforms have exposed organizations to ransomware risks in tier-three and tier-four vendors with limited resources.

How should companies measure AI return on investment?

Eshkenazi argues that headcount reduction is too simplistic a measure. The better metric is response time: how quickly a company can recognize a disruption, evaluate alternatives, and act. This perspective shifts focus from labor displacement to operational agility, though the survey shows unclear ROI remains a top barrier to adoption.

Technology & Innovation

High Impact

AI Skills Shortage Keeps Supply Chain Adoption Stuck in Pilot

Oct 23, 2026

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The signal

A joint survey from the Association for Supply Chain Management and the Digital Supply Chain Institute finds that 83% of supply chain professionals report their workforce is unprepared for AI adoption, creating a critical bottleneck in digital transformation. Companies with ready workforces achieve a 71% AI project success rate, while unprepared organizations see only 28% success and tend to remain stuck in pilot or planning phases.

The research reveals that AI is being deployed narrowly for insights and analysis rather than autonomous decision-making, scoring an average adoption level of 1.94 on a 5-point scale. Two barriers tied for first place in blocking progress: lack of workforce skills (33%) and unclear return on investment (33%).

The findings highlight a structural problem where technology capabilities outpace organizational readiness, creating what ASCM leadership describes as a dangerous mismatch between powerful tools and workers who cannot critically evaluate their outputs.

#ai-adoption

#supply-chain-workforce

#pilot-programs

#ai-skills-gap

#digital-transformation

#supply-chain-technology

#workforce-readiness

#procurement-automation

#cybersecurity-risk

#supply-chain-ai

Frequently Asked Questions

What This Means for Your Supply Chain

Simulation Suggestion

strategic

What if your supply chain team gains AI-ready skills within 12 months?

Simulate increasing workforce AI readiness from current unprepared state to 50% readiness across planning and execution functions. Model the impact on demand planning accuracy, inventory optimization, and procurement automation. Estimate potential service level improvements and cost reductions assuming success rate increases from 28% to 50%.

Run this scenario

Simulation Suggestion

this month

What if you automate routine procurement decisions within guardrails?

Model a selective AI autonomy scenario where freight procurement is partially automated within pre-defined parameters (e.g., rate benchmarking, carrier selection) while high-risk decisions (customer commitments, major disruptions) remain human-controlled. Estimate impact on procurement speed, cost savings, and operational risk. Compare results against keeping AI in analysis-only mode.

Run this scenario

Simulation Suggestion

immediate

What if your tier-3 and tier-4 suppliers suffer ransomware attacks?

Model a cybersecurity disruption scenario where 15% of tier-3/tier-4 vendors go offline due to ransomware. Simulate the cascading impact on visibility, inventory allocation, and fulfillment capacity. Test how reliance on AI-enabled platforms without proper cybersecurity controls amplifies disruption duration and recovery costs.

Run this scenario

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