Overcoming the Knowledge Gaps that Hold Back AI Advancements in Manufacturing

For many in the manufacturing industry, artificial intelligence has long been treated as a solution in search of a problem. But as the technology matures, the real barrier to scaling AI has shifted from a technical challenge to a cultural one: the failure within organizations to communicate, document, and share what their teams are learning. That internal challenge now poses a serious disadvantage, as external pressures from labor shortages, rising costs, and digital acceleration make finding new operational efficiencies more urgent than ever.

Douglas Kent, Executive Vice President at the Association for Supply Chain Management and a former senior leader at PwC and Avnet, has built his career at the intersection of strategy and operations. A recognized global speaker and co-Author of the new book Sustainable Supply Chain Orchestration, he believes that unlocking AI's potential requires changing the focus from the technology itself to the stories organizations tell about it.

"If you want AI to scale, track your hypothesis, trace the result, and tell the story. Inside the company and even on a stage. People are desperate to hear real use cases," says Kent. But you can't tell those stories without first building trust. Instead of demanding blind faith in algorithms, Kent insists the focus should be on developing a functional framework for human oversight.

• Finding balance: "You can’t pretend AI is infallible. It will deliver insights and it will also hallucinate," he says. "The real skill is knowing when the model can run on its own and when the human loop needs to step in to guide, confirm, or correct the result." Getting that balance right is the only way AI moves beyond a pilot and becomes a repeatable capability.

When that trust isn't scaled through shared stories, progress stalls. Kent notes that cultural differences between industries can dictate the pace of adoption; risk-averse sectors like aerospace and defense are slower to trust automated outputs than CPG companies, for example. In that gap of acceptance, learnings can get lost. Pilot programs often remain isolated and their results are not shared, preventing other teams from following a proven growth strategy or learning from peers who have scaled AI successfully.

• A story untold: For Kent, this failure comes down to a single, overlooked discipline. "The biggest thing companies miss out on is storytelling. We sit in these islands of isolation and don’t tell the rest of the organization what we tried, what failed, and what actually worked." That failure to share becomes a growing challenge as external pressures demand a more systemic approach. "Digital doesn’t mean doing the same wrong things faster. It means rethinking what you do, how you do it, and making sure you’re sharing the story of what the technology actually proved."

• Connected advantage: What makes AI transformative in manufacturing is not the novelty of self-diagnosing machines or automated scheduling, it's the connection it creates which allows the supply chain to respond as one system rather than a series of handoffs. "The value shows up when AI connects planning and manufacturing into one continuous flow. Once those pieces move together, the whole operation can respond more fluidly to disruptions and protect itself from cost pressure and tariff volatility," explains Kent. With cost structures shifting and demand patterns becoming harder to predict, that integrated view is becoming more essential than ever.

Technology can accelerate progress, but people determine whether that progress lasts. For AI to scale, teams need the skills to oversee the human loop, evaluate results, and turn their experiences into stories the rest of the organization can use. Kent's final point is that the talent gap often matters more than the technical one. "We have to keep pace between talent and technology," he concludes. "If the talent isn’t there to know how to use it effectively, then you get in the situation where the ROI goes upside down."