Only 10% of retail and manufacturing leaders trust AI to make fully independent supply chain decisions, per Relex Solutions’ 2026 report based on a survey of 514 leaders. Instead, 54% prefer AI recommendations with human final approval. Confidence in AI rose to 67%, with 47% using AI for inventory optimization and 41% for logistics routing. Key drivers include consumer demand volatility (44%) and raw material disruptions (57% among manufacturers). Investment plans show 71% targeting generative and agentic AI within 3–5 years.
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. The study draws on a January 2026 survey of 514 retail, manufacturing, wholesale, and supply chain leaders, conducted by Researchscape.
Human-in-the-Loop Dominates Decision-Making
Rather than delegating authority, 54% of respondents prefer AI to generate recommendations while humans retain final decision rights. This reflects a strong preference for human oversight despite growing operational integration of AI tools. Confidence in AI for supply chain decision-making has risen significantly: 67% report increased confidence compared with last year.
Current AI Adoption by Function
Adoption is accelerating across high-impact areas:
- 47% are using or planning AI-driven inventory and supply optimization
- 41% are applying AI to logistics and routing
Investment plans further signal institutional commitment: 71% plan to invest in generative and agentic AI, and 60% in predictive AI, over the next three to five years.
Drivers Vary by Sector
Demand volatility is the top catalyst for AI investment across sectors: 44% of leaders cite consumer demand volatility as a top challenge over the next three years. Retailers feel this acutely — 30% identify adapting to sudden consumer demand shifts as a major challenge, driving adoption of AI-driven forecasting and decision-support tools to balance margins and product availability.
Manufacturers face distinct pressures: 57% say raw material procurement disruption is the most impacted area of their supply chain, while 34% cite regulatory and compliance pressures as a growing concern.
“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
Broader Industry Context
This cautious yet pragmatic stance aligns with wider industry patterns. PMMI’s 2026 report on AI in packaging — based on interviews with CPG firms, OEMs, and machinery vendors — confirms similar adoption trajectories: AI use is shifting from isolated pilots to broader deployment, particularly in predictive maintenance, machine vision, and regulatory compliance. However, persistent barriers remain, including data hallucinations, accountability for AI-generated errors, cybersecurity, and gaps in operational readiness. Notably, smaller firms increasingly favor software-as-a-service (SaaS) models to offload implementation risk — a trend observed across logistics technology providers like Manhattan Associates and Blue Yonder, whose recent earnings calls highlight SaaS-driven AI module uptake.
For supply chain professionals, this means AI integration must prioritize interoperability with legacy systems, transparent model explainability, and role-specific training — especially for planners and procurement teams who rely on real-time scenario modeling. Human judgment remains non-negotiable for exception handling, ethical trade-offs (e.g., sustainability vs. cost), and stakeholder alignment — reinforcing that AI’s highest value lies not in autonomy, but in augmenting speed, accuracy, and consistency of human-led decisions.
信息来源：DC Velocity
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