The Best Manufacturers Build AI with Workers, Not for Them
Summary. Manufacturers are pushing ahead with AI, but workers often feel unprepared, uncertain, and distrustful. Research shows a clear gap between executive optimism and frontline experience, driven by unclear roles, weak training, and poor performance measures. The most effective companies close this gap in three ways. First, they reduce uncertainty by involving workers in mapping how roles will evolve. Second, they train people in the flow of real work, not in abstract settings. Third, they measure success based on how humans and AI perform together on the job. These practices build trust, improve outcomes, and accelerate adoption. Factories that treat AI as a collaborative tool, not a replacement, are better positioned to adapt and compete.
Executives are optimistic about AI’s potential to transform manufacturing. Workers, on the other hand, are more skeptical. In a seven-week internal unpublished study of video diaries from 85 frontline workers across six industries in Australia, the UK and the United States, we asked workers to describe how emerging technologies, including AI, are being introduced into their jobs, what training they receive, and how they see their future. Across industries, distrust ran deep, of both the tools and the organizations deploying them. More than three-quarters of participants said they were dissatisfied with their training. Many were uncertain about how their roles would change or whether they would have a place in the future factory.
But some manufacturers are getting this right. They are closing the gap between executive optimism and workers’ lived experience. Their approach—and our internal research—point to three key principles that shape how the smartest manufacturers approach this kind of working environment. They reduce uncertainty about how roles will shift with input from the shop floor. They train people in the context of real work. And they measure performance based on how humans and AI operate together, not on training hours logged.
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