With almost constant supply-chain disruptions, the need for adaptive planning is crucial, says Andrew Bell, chief product officer at Kinaxis.

Disruptions vary in degree and in impact, but the one thing they have in common is they seem to be continuous these days. Or, as Bell says, “It’s not a single event. They're happening all the time.”

Supply-chain planning in particular needs to be more than aware of events; it must be nimble enough to continuously adapt to changing conditions.

As for the role of artificial intelligence in supply chain, Bell says it’s imperative to know what the desired outcome is, and what AI can do. “Where do I need to make better decisions? What does a better decision look like for me, my company, my situation? How do I use these tools to achieve those outcomes?”

Of course, AI has been used for some time in the predictive space, most obviously in machine learning for demand forecasting. Use of generative and agentic AI is still in its infancy. “Then you've got the second phase of democratization of access,” Bell says. “Now, people who might not be experts in how to use the various tools can access them because of the new interface of generative, agentic AI. And we have this notion of horizontally orchestrating the workflow by building agents that go across multiple functions in supply chain, as opposed to just driving productivity in one.”

Traditionally, the planner collected and analyzed a lot of data, then applied their own judgment, Bell says, but AI is changing that. “Now, the planner's role is about setting the guardrails, policies, direction and objectives, setting the framework that will drive the decision to be made. Then AI does the heavy lifting, looking at the data, leveraging the tools and capabilities at its disposal to make recommendations to the planner based on those policies and objectives the planner has set.”