Only 10% of retail and manufacturing leaders trust AI to make fully independent supply chain decisions, per Relex Solutions' 2026 report. While 54% prefer AI recommendations with human final approval, confidence in AI use rose to 67% year-over-year. Adoption is strongest in inventory optimization (47%) and logistics routing (41%). Consumer demand volatility (44%) and raw material disruptions (57% among manufacturers) drive planned investments in generative, agentic, and predictive AI. Experts stress AI's role in enhancing responsiveness—not replacing judgment—in volatile conditions.
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 AI Adoption
Rather than delegating authority to AI systems, 54% of respondents prefer AI to generate recommendations while humans retain final decision-making authority. The data stems from a January 2026 survey of 514 leaders across retail, manufacturing, wholesale, and supply chain functions, conducted by Researchscape.
Growing Confidence Amid Cautious Deployment
Despite skepticism about full autonomy, 67% of respondents reported increased confidence in using AI for supply chain decision-making compared with 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.
Investment Trajectory and Drivers
Looking ahead, 71% plan to invest in generative and agentic AI, and 60% in predictive AI over the next three to five years. The chief catalyst is volatility: 44% cite consumer demand volatility as their top challenge over that horizon. Retailers especially feel downstream pressure — 30% identify adapting to sudden consumer demand shifts as a major challenge, driving demand for AI-enhanced forecasting, inventory optimization, and responsive decision-support tools.
Manufacturers face distinct pressures: 57% point to raw material procurement disruption as the most impacted area, while 34% highlight regulatory and compliance pressures as growing operational 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 deliberate adoption reflects broader industry patterns. For example, Gartner’s 2025 Hype Cycle for Supply Chain Strategy notes that AI-powered demand sensing tools have moved from the ‘Peak of Inflated Expectations’ into the ‘Slope of Enlightenment’, with early adopters reporting measurable gains in forecast accuracy (12–18% improvement) and stockout reduction (up to 22%). Similarly, Maersk’s 2025 digital transformation update confirms deployment of AI-driven port call optimization across 12 terminals — but all final berth allocation decisions remain human-reviewed.
Practically, supply chain professionals must prioritize interoperability between AI tools and legacy ERP/TMS platforms, ensure audit trails for AI-generated recommendations, and develop cross-functional upskilling programs focused on interpreting probabilistic outputs and managing exception workflows.
This article was AI-assisted and reviewed by the SCI.AI editorial team before publication.
Source: DC Velocity
