Manufacturers risk losing critical know-how as AI takes over

MIT Technology Review reports that manufacturers are under pressure to capture and transfer the practical knowledge that keeps factories running. The article calls this blend of experience and recorded data "industrial intelligence." For business operators, the risk is that crucial know-how may disappear as older workers retire and as AI systems take on more decision-making.

Why it matters

Every manufacturer has its own way of doing things, shaped by the people who run the lines and fix the problems. According to MIT Technology Review, some of this knowledge is written down, but much of it lives in the heads of experienced operators. When a veteran prepares to restart a line after a changeover, they know the settings, how specific materials behave, what happened on the previous shift, and which "minor issues" can halt production if missed.

As AI and automation become more common, that kind of tacit knowledge is at risk. AI systems can optimize for efficiency and consistency, but they need accurate, comprehensive data. If the only record is someone's memory, that knowledge is not available to the system or to the next generation of workers. The result can be lower productivity, higher error rates, and slower recovery from disruptions.

Most operator knowledge is undocumented

The MIT Technology Review story highlights how much of industrial intelligence is undocumented. Experienced staff know which machine parameters matter most, how to adjust for subtle differences in materials, and which warning signs predict trouble. These details often go unrecorded, even as factories bring in new digital tools and AI-driven systems.

This is a data problem as much as a training problem. AI models need structured, accurate records. But when process adjustments or workarounds are passed along informally, they never make it into the system. When a key operator leaves, their knowledge can leave with them. According to the article, this is now a strategic concern for manufacturers investing in AI and automation. Companies are starting to treat operator knowledge as an asset that needs to be documented, updated, and made accessible, just like any other part of the production process.

What this means if you run a business

If you operate a manufacturing business, the risk is losing the practical expertise that keeps production on track. As more companies adopt AI-driven process control, the gap between documented procedures and real-world know-how becomes a cost issue. When key people leave or retire, undocumented fixes and adjustments may vanish. This can lead to expensive downtime or failed automation projects.

For business owners, investing in AI or automation means building systems for capturing and updating the expertise of your workforce. That could mean structured interviews with experienced operators, regular updates to process documentation, or digital tools that make it easy to record adjustments and observations. As the MIT Technology Review article suggests, treating industrial intelligence as a managed asset is now a competitive necessity.

Some companies are starting to act on this by building new documentation processes and digital knowledge bases. Others are still relying on informal handovers. The difference will show up in how well automation projects deliver results and how quickly factories recover from disruptions.