Artificial intelligence (AI) is moving from experimentation to operational decision support across supply chain planning, but only 10% of retail and manufacturing leaders say they would trust AI to make fully independent supply chain decisions, according to a study from tech vendor Relex Solutions.
Instead of allowing AI to make those decisions itself, 54% said they prefer AI to make recommendations while humans finalize decisions. That data comes from “State of Supply Chain 2026: Volatility, Trade-Offs & the Rise of AI,” a report based on a January 2026 survey of 514 retail, manufacturing, wholesale and supply chain leaders conducted by Researchscape.
Despite that skepticism, 67% of respondents to the survey said their confidence in using AI for supply chain decision-making has increased compared with last year. For example, 47% are using or planning AI-driven inventory and supply optimization and 41% are applying AI to logistics and routing.
Meanwhile, many organizations are planning for a future with more AI, with 71% planning to invest in generative and agentic AI and 60% in predictive AI over the next three to five years.
The chief reason behind those investments is that 44% of leaders cite consumer demand volatility as a top challenge over the next three years, reinforcing the need for more intelligent, responsive planning systems.
Retailers continue to feel the downstream effects of demand uncertainty, as 30% cite adapting to sudden consumer demand shifts as a major challenge, reinforcing the need for stronger demand visibility and more responsive planning processes. To address this volatility, retail leaders are increasingly turning to AI-driven forecasting, inventory optimization, and decision-support tools that allow them to respond quickly to changes in consumer behavior while protecting margins and availability.
Manufacturers cited different reasons for investing in AI, with 57% saying raw material procurement disruption is the most impacted area of their supply chain, while 34% citing regulatory and compliance pressures as a growing operational concern.
"AI is becoming part of everyday supply chain decision-making," Madhav Durbha, group vice president of manufacturing industry strategy at Relex Solutions, said in a release. "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."
Facts Only
Actors: Retail leaders, manufacturing leaders, Relex Solutions (tech vendor)
Events: AI being used for operational decision support, survey conducted by Researchscape, increase in confidence in using AI for supply chain decision-making, planning for future investments in AI
Dates: January 2026 (survey)
Locations: Not specified
Institutions: Relex Solutions, Researchscape
Executive Summary
Full Take
In analyzing the article, it is important to recognize that while AI is becoming increasingly integrated into supply chain decision-making, there remains a significant level of skepticism regarding its ability to make fully independent decisions. This hesitancy may be due to concerns about the transparency and accountability of AI systems, as well as a desire to maintain human oversight in critical decision-making processes. However, the increase in confidence in using AI for supply chain decision-making suggests that businesses are recognizing the potential benefits of these technologies, particularly in responding quickly to changes in consumer behavior and managing volatility in demand and raw material procurement.
Patterns detected: None
Root Cause: The integration of AI into supply chain decision-making is driven by a desire to increase efficiency, reduce costs, and improve responsiveness in the face of increasing volatility and complexity. However, this shift also raises questions about the role of humans in decision-making processes and the potential risks associated with reliance on AI systems.
Implications: The growing use of AI in supply chain decision-making has significant implications for both businesses and consumers. On one hand, it offers the potential to improve efficiency and responsiveness, potentially leading to lower costs and improved customer service. On the other hand, it raises questions about accountability, transparency, and the potential for unintended consequences or bias in AI systems.
Bridge Questions: What are the long-term implications of increased reliance on AI in supply chain decision-making? How can businesses ensure that they are using AI ethically and responsibly? What role should humans play in overseeing and guiding AI systems, and how can we ensure that they are making informed decisions based on data from these systems?
Sentinel — Human
This article is likely written by a human journalist. The writing style, argumentative structure, and personal touch indicate a human writer.