Agentic AI in the global supply chain

Executive Summary

In the fast-paced world of supply chain management, every second matters. Delays, inefficiencies, and disconnected data can have significant financial and operational consequences. The COO’s focus is on maintaining a robust, sustainable supply chain, from the design of the product right through to its delivery and operation at a customer location. This broad perspective can result in more efficient operations and greater flexibility, productivity, and sustainability because decision-making is based on data, and resources are used more strategically. Lately, however, the supply chain has given COOs more than their fair share of headaches, especially when it comes to anticipating and mitigating disruptions: pandemics, trade wars and tariffs, social unrest, and even extreme weather. That is why the introduction of agentic AI—intelligent, sometimes autonomous agents that can understand natural language, bridge information gaps, integrate across systems, and even take action—represents a huge opportunity and even a business imperative for operational improvements for manufacturers and their supply chain partners. There’s a major difference between generative AI and agentic AI. While generative AI is excellent for creating content, making predictions or answering questions, agentic AI goes even further. It doesn’t just generate insights—it has the ability to act upon them. AI agents can collaborate, make decisions, and initiate actions across different business functions. In other words, agentic AI moves AI from suggestion to execution.