A Relex Solutions study finds only 10% of retail and manufacturing leaders trust AI to make fully independent supply chain decisions; 54% prefer AI recommendations with human finalization. Confidence in AI use rose to 67%, with 47% adopting AI for inventory optimization and 41% for logistics routing. Retailers prioritize demand volatility response (44%), while manufacturers focus on raw material procurement disruption (57%). Seventy-one percent plan generative and agentic AI investments within five years. Experts emphasize AI's role as decision support-not autonomous action-in volatile, regulated environments.
According to www.dcvelocity.com, only 10% of retail and manufacturing leaders say they would trust AI to make fully independent supply chain decisions — a finding from Relex Solutions’ “State of Supply Chain 2026: Volatility, Trade-Offs & the Rise of AI” report.
Human-in-the-Loop Dominates Decision-Making
Instead of full autonomy, 54% of respondents prefer AI to generate recommendations while humans retain final decision authority. The report draws on a January 2026 survey of 514 leaders across retail, manufacturing, wholesale, and supply chain functions, conducted by Researchscape.
Growing Confidence, Strategic Investment
Despite caution around delegation, confidence is rising: 67% reported increased confidence in using AI for supply chain decision-making compared to the prior year. Operational adoption is accelerating — 47% are using or planning AI-driven inventory and supply optimization, and 41% are applying AI to logistics and routing.
Forward-looking investment plans reflect long-term commitment: 71% plan to invest in generative and agentic AI, and 60% in predictive AI over the next three to five years.
Drivers of AI Adoption by Sector
- Retail: 44% cite consumer demand volatility as their top challenge over the next three years; 30% identify adapting to sudden demand shifts as a major operational hurdle — driving adoption of AI-driven forecasting and decision-support tools to protect margins and product availability.
- Manufacturing: 57% point to raw material procurement disruption as the most impacted area; 34% highlight regulatory and compliance pressures as growing concerns.
“AI is becoming part of everyday supply chain decision-making. As volatility persists, companies are investing in AI-driven forecasting, optimization, and decision support to respond faster and operate with greater confidence, even when conditions change quickly.” — Madhav Durbha, group vice president of manufacturing industry strategy at Relex Solutions
This cautious yet pragmatic stance reflects broader industry patterns. Major players like Maersk and Amazon have deployed AI for predictive container allocation and dynamic warehouse slotting — always with human oversight layers. Gartner’s 2025 Hype Cycle notes that supply chain agentic AI remains in the ‘Innovation Trigger’ phase, with no vendor offering production-grade autonomous execution without audit trails or override controls. For practitioners, this means AI integration must prioritize explainability, real-time data governance, and role-based validation workflows — not just algorithmic accuracy. Teams building AI-augmented planning systems should treat model outputs as high-fidelity inputs, not binding directives, especially where regulatory compliance (e.g., CSDDD, CBAM) or margin-sensitive stockout/overstock trade-offs are involved.
This article was AI-assisted and published after review and verification by the SCI.AI editorial team.
Source: DC Velocity
