Are you ready to order critical parts and products from a manufacturer the same way you order a cheeseburger from a fast-food restaurant? Leaders at industrial distributors soon could have to answer that question.

And while much of the recent talk surrounding automation and artificial intelligence (AI) has focused on applications such as ChatGPT and GPT-4 — the latter covered in a previous MDM QuickTake — other broader AI-backed applications may soon become widespread in distribution.

That’s according to MDM CEO Tom Gale and Indian River Consulting Group’s Mike Marks, whose latest QuickTake podcast covers the many problems that AI engines can solve for industrial distributors.

“There’s no way this genie is going to go back in the bottle at this point,” Marks says.

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But there are ways distributors can take advantage of existing AI engines — and their own accumulated company data — to operate more efficiently and competitively. In fact, many distributors already have access to AI engines, Marks says. They’re just not using them.

“You take one of these models for free, you get somebody knows what to use it,” Marks says. “They suck all your data in. And then what it does is, it starts to generate recommendations and input so you make better decisions.”

Think of it as “Do you want fries with that?” but if fries were specific product needs or service trends your company should keep an eye on. The process can begin with something as simple as creating customer classifications, Marks says.

“If customer classes haven’t ordered anything in 30 days, then it sends an email from the sales manager to the sales rep saying, ‘What happened to Acme Screen Door and Missile Supply?” and copy the sales manager,” he says. “Because the system generated that message. And the whole point is that, with all the noise in there, how does the salesperson notice something’s happening?”

Distributors might be hesitant to utilize AI because it is a seismic change to an industry that, historically, doesn’t act on change quickly. As an example, Marks said companies implementing AI for the first time might be discouraged when the AI points out inefficiencies in the way they do business.

“All of a sudden this guy who has been doing it says, ‘You mean, I’ve been doing it wrong for 20 years?’ And then everybody goes into denial,” Marks says. “So, that’s where they get stuck. Most distributors are using a fraction of what they already own.”