Machine learning helps GM pick the best places to put new EV fast chargers

Enlarge / A 2024 Chevrolet Silverado EV WT at a pull-through charging stall located at a flagship Pilot and Flying J travel center, as part of the new coast-to-coast fast charging network. (credit: General Motors)

It’s understandable if you’re starting to experience AI fatigue; it feels like every week, there’s another announcement of some company boasting about how an LLM chatbot will revolutionize everything—usually followed in short succession by news reports of how terribly wrong it’s all gone. But it turns out that not every use of AI by an automaker is a public relations disaster. As it happens, General Motors has been using machine learning to help guide business decisions regarding where to install new DC fast chargers for electric vehicles.

GM’s transformation into an EV-heavy company has not gone entirely smoothly thus far, but in 2022, it revealed that, together with the Pilot company, it was planning on deploying a network of 2,000 DC fast chargers at Flying J and Pilot travel centers around the US. But how to decide which locations?

“I think that the overarching theme is we’re really looking for opportunities to simplify the lives of our customers, our employees, our dealers, and our suppliers,” explained Jon Francis, GM’s chief data and analytics officer. “And we see the positive effects of AI at scale, whether that’s in the manufacturing part of the business engineering, supply chain, customer experience—it really runs through threads through all of those.