Artificial intelligence is transitioning from experimental to operational decision support in supply chain planning. Retail and manufacturing leaders report that 67% of them have growing confidence in using AI for supply chain decision-making compared to the previous year. RELEX Solutions’ "State of Supply Chain 2026: Volatility, Trade-Offs & the Rise of AI" report reveals that 54% of respondents prefer AI to make recommendations while humans finalize decisions, with only 10% trusting AI to make supply chain decisions completely independently. From a supply chain perspective, human-in-the-loop architecture ensures that regulatory frameworks such as the AI Act and NIST AI RMF are reflected in supply chain decision-making, with auditability and explainability becoming central to corporate procurement criteria.
In the same report, 47% of respondents are using or planning to use AI-driven inventory and supply optimization, while 41% are applying AI to logistics and routing. The report is based on a survey of 514 retail, manufacturing, wholesale, and supply chain leaders conducted by Researchscape in January 2026. From a supply chain perspective, adding an AI layer to multi-echelon inventory optimization (MEIO) engines in the inventory optimization domain combines safety stock calculations with service level curve optimization. On the routing side, VRP (Vehicle Routing Problem) solvers process traffic, weather, and delivery window signals in real time, increasing last-mile efficiency.
RELEX, which operates an AI-driven supply chain management technology platform, notes that organizations are increasing future investment in their AI capabilities. 71% of leaders plan to invest in generative and agentic AI over the next three to five years, while 60% are considering investing in predictive AI. These investments are occurring in an environment where 44% of leaders identify consumer demand volatility as their top challenge over the next three years, reinforcing the need for smarter and more responsive planning systems. From a supply chain perspective, different layers such as generative AI for scenario explanation, agentic AI for autonomous purchase order generation, and predictive AI for demand forecasting are interconnected in a composable architecture. API-first approaches enable evaluation together with AI plug-ins for platforms such as SAP IBP, Oracle Fusion SCM, Blue Yonder, and o9 Solutions.
The report also shows that retail leaders are increasingly turning to AI-driven forecasting, inventory optimization, and decision support tools, enabling rapid response to changes in consumer behavior while preserving margins and availability. AI is increasingly being applied to link demand signals to purchasing and production decisions, helping manufacturers improve forecast accuracy, reduce supplier risk, and maintain flexibility in the face of ongoing material, regulatory, and geopolitical disruptions. From a supply chain perspective, combining demand sensing and demand shaping techniques with machine learning models enables Point of Sale (POS) data to flow upstream in hourly cycles. In the supplier risk monitoring domain, knowledge graph-based solutions that provide tier-N visibility automatically convert geopolitical and regulatory signals into events. Ultimately, the RELEX report clearly documents that artificial intelligence is moving beyond experimentation and into the center of operational decision-making processes in supply chain management.
Key Takeaways:
1. 67% of leaders report growing confidence in AI compared to the previous year.
2. 54% prefer the recommendation-approval model; only 10% trust fully autonomous decisions.
3. 47% are deploying AI in inventory and supply optimization; 41% in logistics and routing.
4. 71% plan to invest in generative and agentic AI; 60% in predictive AI over 3-5 years.
5. 44% identify consumer demand volatility as their top challenge.
