The Cautious Apprentice

Most gear companies have experimented with artificial intelligence (AI); few have integrated it into core operations. The typical deployment involves marketing copy, meeting transcription, and email drafting—useful but peripheral.

Where companies have pushed further, results vary. One reports that AI-assisted engineering and design is “paying off.” Another uses AI to optimize production scheduling against the competing demands of marketing forecasts, manufacturing capacity, and supply chain constraints. These aren’t trivial applications.

But skepticism persists, and it’s earned. One respondent tried using AI for ratio calculations and watched it fail. Another found AI analysis “often incorrect and inconsistent.” The technology works well enough for tasks where errors are easily caught and corrected; it’s not yet trusted where mistakes are costly.

A deeper concern runs beneath the practical objections. Several respondents worry about feeding proprietary knowledge into systems they don’t control. The gear industry runs on accumulated expertise—decades of understanding how a particular machine behaves, how a specific material cuts, what tolerances a given application actually requires. That knowledge has value precisely because it’s hard-won and closely held. Handing it to an AI feels, to some, like giving away the store.

Still, the trajectory is clear. Companies that dismissed AI entirely a year ago now describe “pilot programs” and “exciting opportunities.” The question isn’t whether AI will reshape the industry, but how quickly and in what form.