Companies are no longer rushing to bolt AI onto their supply chains just to say they did it. They’re starting to take a step back, asking how technology can actually serve the business, not the other way around.

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That shift was the focus of a recent conversation with Chuck Reynolds and Matt Stanfield, Managing Directors at L.E.K. Consulting, who advise clients across manufacturing, logistics, and retail. Both say the smartest companies aren’t asking what tool to buy. They’re asking why they need it.

Don’t focus on the buzzwords

According to Reynolds, the mistake many leaders make is listening to vendors before understanding their own friction points.

“Don’t approach it by listening to the vendors and say this is a new, amazing way to work,” he said. “Start with the business objective, such as agility, sustainability, or higher service. Then ask where the friction is.”

That means most companies shouldn’t be talking about generative AI until they’ve cleaned up their data and optimized their processes. “We’ve had clients say, ‘We want AI,’ but they don’t have the basics in place,” Stanfield added. “Sometimes the answer is a 1980s process fix before you buy 2020s software.”

AI is changing the work itself

Once the groundwork is there, the harder challenge becomes adoption.

“What people don’t talk enough about is how AI changes the unit of work,” Reynolds said. “You’re not running linear processes anymore. You’re managing autonomous agents, handling exceptions, and teaching the system what a good plan looks like.”

“Trust is key. If people don’t trust what the algorithm’s doing, they’ll override it. The leaders who win are the ones who train their teams to work with AI, not around it.”

Stanfield agreed, noting that this requires a completely new operating model. “Trust is key,” he said. “If people don’t trust what the algorithm’s doing, they’ll override it. The leaders who win are the ones who train their teams to work with AI, not around it.”

Smarter systems mean smaller footprints

AI’s biggest physical impact may come from efficiency.

“When you have AI optimizing capacity, you need less space,” Stanfield said. “Predictive maintenance means higher uptime, better inventory placement, and fewer warehouses.”

Reynolds calls this “the smaller supply chain,” one built around smarter utilization rather than bigger networks. “The digital changes the physical,” he said. “That’s what people aren’t realizing yet.”

Redefining the supply chain leader

Both executives believe the Chief Supply Chain Officer role is in need of a major reset.

“The CSCO can’t just be a cost steward anymore,” Reynolds said. “It’s a growth role now, one that connects to sales, marketing, and technology.”

For those starting out, Stanfield’s advice is simple: “Learn Python, understand data, and get some experience in a factory. That’s how you’ll be ready for what comes next.”