By Sasha Pailet Koff
There’s a great deal of excitement around the role of agentic AI in supply chain operations, and rightfully so.
Agentic systems do more than automate tasks. They initiate action, learn continuously, and take actions based on goals and real-time context. This represents a fundamentally different paradigm from traditional robotic process automation (RPA), which executes predefined rules within a structured workflow. We need both.
RPA remains essential for stability, repeatability, and efficiency. Agentic capabilities, however, open the door to adaptive decision-making, cross-functional orchestration, and unlocking value in complex and dynamic environments where rules aren’t enough.
But with this shift comes responsibility. If we are introducing autonomous digital actors into our supply chain ecosystems, agents that negotiate, classify, plan, detect exceptions, or trigger actions in the physical world, then we must also introduce modern governance, oversight, and accountability frameworks to manage them.
This means asking important questions:
Just as we would never deploy a new physical workflow without process controls, checks, and clearly defined responsibilities, we cannot deploy digital actors without governance and resilience plans.
In other words, agentic AI isn’t just a technology investment. It’s an operating model investment. Organizations that understand this will move faster, be more resilience, and build supply chains capable of learning and adapting in real time. Those that don’t may find themselves with powerful tools and unintended consequences.
The future of supply chain is intelligent, autonomous, and interconnected. We must ensure this new world is built with clarity, accountability, and security at its core.
Sasha Pailet Koff is Managing Director of the Cyber Readiness Institute (CRI) and is Founder and President of consultancy, So Help Me Understand. She is Co-Chair Emeritus of the Digital Supply Chain Institute (DSCI). This blog originally appeared on Sasha’s LinkedIn page.
