A few months ago, I took note of how prevalent the topic of artificial intelligence (AI) has become in just about any conversation one might have about the future of the industry. Those conversations aren’t going away—I’ve had them with my customers recently, and I bet you have, too.

I don’t claim to be an expert on the subject—far from it, in fact. But I’m paying attention, and I’m considering the possible impacts that AI and other burgeoning technologies may have on manufacturing at large. There are plenty of angles to consider. And that brings us to today’s tip:

Keep your eyes open when it comes to technological change.

I’ve always been an advocate for embracing the right technologies to elevate operations on the shop floor. Manufacturing, as a whole, has come a long way by doing so. Shop floors everywhere are broadly cleaner, safer and more efficient than they’ve ever been, in part due to technological progress.

Here I’ll emphasize: the right technologies have helped us accomplish these things. And leveraging the right technologies for your operations involves thorough vetting, evaluation and, of course, eventual adoption. And whether or not something like AI is a real solution to real problems is still being borne out. For example, I was struck by this recent headline from IndustryWeek: “IIoT Means Nothing and No One Uses Generative AI.”

The report is an analysis of a recent technology survey of manufacturers across different industries. IIoT—meaning the Industrial Internet of Things, aka the end-to-end connectivity of critical factory equipment—may “mean nothing,” according to the survey, but manufacturers are capturing and analyzing data on critical metrics. “Sixty percent said they capture data to analyze processes like throughput and volume,” the report notes. “Fifty-three percent measure productivity, information like cycle times, changeover times, uptime and downtime.” This kind of analysis can lead to some powerful insights manufacturers can use to make a difference.

How about AI?

“Three-quarters of respondents said they did not use AI in their businesses. We asked the remaining 25% to elaborate. Only two respondents cited a manufacturing-specific use case. The rest were business applications with nothing to do with manufacturing operations, such as pricing engines, document writing, corporate communications, and sales and marketing applications.”

Again, terminology may be a complicating factor here. Experts cited in the piece say applications like machine learning—which can automatically predict maintenance needs, tweak process conditions, and other functions—should be included under the AI umbrella.

But most people hear AI and think of generative applications like ChatGPT and OpenAI. Meanwhile, programs such as these are simply not being used for manufacturing-specific functions right now—probably for good reason. In recent weeks, you might have heard about Google’s new AI feature providing patently false answers to simple search queries. That kind of margin for error is simply unacceptable on a manufacturing floor, where safety and quality are at stake every day. The technology may yet evolve to a more reliable form, but we’re not there yet.

The point of all this, then, is simply that manufacturing leaders need to stay on top of these kinds of technological trends, even if we’re not putting them to use immediately. There may be plenty of talk about the possibilities regarding AI and manufacturing, and those possibilities are worth our careful consideration—even if some of them may never become fully realized.

Again: It’s about the right technologies for the right applications. And it’s up to all of us to continue paying attention.

John Ryba is technical services manager for Quanex.

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