Agentic artificial intelligence is enhancing operations of warehouse management systems, says Todd Kolber, partner-general manager at Logistics Reply.

Existing WMS architecture is insufficient, in Kolber’s view. Planners are looking months, even years out, operations are tasked with meeting those forecasts, and management is the “traffic cop” that’s supposed to make everything work.

“The problem that a warehouse management system has is that it can't see the whole,” Kolber says. “It's answering a need for a given task and fulfilling orders, but it's not really providing what is the total optimal outcome for a process or facility. There's still a lot to be desired today.” 

Either management or a solution needs to be much more aware at an “umbrella level” of all resources, functions and technologies in the entire facility, he says. “The key word is orchestrate – orchestrate what happens in that facility.” 

A lot of data and activity “happens” in real time, making it impossible for any human or team to make the right decision on the best action to take, Kolber says. “It’s going to be critical that AI and agentic AI systems play a major role in bringing all that data together, analyzing it, looking at historical trends and patterns, then making decisions based on all that information in real time and providing the optimal answer. And, more importantly, when things happen that we're not expecting — when a large order … drops, a machine starts performing at a lower speed than historically it does, or an area of the warehouse goes down — humans can't react fast enough to recover.

“AI can analyze all that data in real time, solve things in such a way that you can still meet the goals of that day, and do it at optimal cost,” Kolber says.