General Motors tracks executive AI usage in internal competition

General Motors (GM) is fostering an internal competition among its senior leadership focused on the adoption and utilization of artificial intelligence (AI). Paul Jacobson, the company's Chief Financial Officer, revealed that top executives, who report directly to CEO Mary Barra, are comparing monthly AI usage data across different business functions and departments.

"There is a healthy competition among all of Mary’s senior executives. We publish the usage for each function and business unit every month," Jacobson stated at the JPMorgan U.S. All Stars conference in London. He described the initiative as a "company-wide, well-intentioned, healthy competition." A spokesperson for GM confirmed the existence of this "friendly rivalry" among executives.

GM has been accelerating AI applications across various divisions in recent years. The company has previously indicated that AI tools can offer suggestions for vehicle design and assist in identifying supply chain risks. Sterling Anderson, Chief Product Officer, has stated that his team aims to expedite the entire process from car design to mass production.

AI has become a focal point for Detroit automakers, especially as Chinese automotive companies expand their global market share with more affordable electric vehicles offering longer ranges. Jacobson also acknowledged this competitive pressure, noting that the United States is becoming a "haven" for manufacturers shifting production away from intense competition in the Chinese market.

Jacobson emphasized that GM's AI strategy is still in its early stages, with the company continuously exploring how the technology can transform its operations. He anticipates future applications in vehicle features, product quality, and manufacturing processes, warning that companies failing to improve efficiency through AI will "fall further and further behind." Within the finance department, Jacobson hopes AI will empower analysts with foresight, shifting their focus from analyzing past performance to forecasting future trends.