AI is moving from experimentation to operational decision support across supply chain planning, and is being used to counter supply chain volatility, according to the State of Supply Chain 2026: Volatility, Trade-Offs & the Rise of AI report from RELEX Solutions.

“Most companies today have accepted that volatility is now an expected part of their operations,” explains Max Forsius, Product Director, AI Innovations at RELEX Solutions, and 44% of leaders cite consumer demand volatility as a top challenge over the next three years, according to the report.

“The challenge is that many supply chain decisions are still made in disconnected ways, even though forecasting, replenishment, allocation, and execution all directly affect one another,” Forsius continues. “AI helps organizations connect those decisions so they can adjust plans continuously as demand, inventory levels, supplier constraints, and operating conditions change.”

In fact, 67% of retail and manufacturing leaders say their confidence in using AI for supply chain decision-making has increased compared with last year. Based on this sentiment, organizations are increasing future investment in AI capabilities, with 71% planning to invest in generative and agentic AI and 60% in predictive AI over the next three to five years, according to the report.

Forsius says AI helps organizations evaluate trade-offs much faster and with greater precision, allowing companies to react more effectively while maintaining service levels, controlling costs, and keeping inventory better aligned with actual demand.

Forsius points out that most organizations are not aiming for fully autonomous supply chains, however. Instead, they are building systems where AI generates recommendations, and humans remain accountable for the final decision. The report found that 54% prefer AI to make recommendations while humans finalize decisions, and only 10% trust AI to make fully independent supply chain decisions.

The Bottom Line

AI adoption is strongest in areas tied to inventory planning, forecasting, replenishment, allocation, and broader supply chain coordination, says Forsius, and the report findings show 47% of organizations are already using or planning AI-driven inventory and supply optimization initiatives. “These are high-frequency decisions that directly impact product availability, working capital, and operational efficiency, making them some of the most valuable and measurable applications for AI.”

The clearest financial impact of AI comes from improving the precision of core supply chain planning decisions, according to Forsius. “Rather than trying to automate everything, the most strategic companies are focusing on areas where incremental improvements can drive meaningful gains in efficiency, availability, and profitability.”

Forsius continues, “Inventory is one of the clearest examples. Traditionally, many companies relied on excess inventory as a buffer against uncertainty. Now, AI is helping organizations align supply more closely with actual demand so they can improve availability without carrying unnecessary stock. That lowers working capital requirements, reduces waste and markdown risk, and improves margins at the same time.”

Forsius concludes that even small improvements in forecast accuracy, replenishment, or allocation can scale quickly across thousands of products and locations, creating measurable gains in availability, efficiency, and inventory performance.