GM, Ford and Stellantis have shed more than 20,000 U.S. salaried positions. That’s 19 percent of their combined white-collar workforces from recent peaks this decade. The cuts didn’t arrive overnight. They built over years of shifting demands. Yet artificial intelligence now stands ready to speed the process.
Public filings and company employment data paint a clear picture. White-collar headcount across the Detroit Three topped roughly 102,000 in 2022. By the end of last year that number stood at 88,700. CNBC first detailed the scale on May 15. The reasons vary. Legacy costs. Slow electric-vehicle adoption. The pivot to software-defined vehicles. And now AI tools that handle tasks once reserved for engineers, programmers and analysts.
GM led the decline. The company cut about 11,000 salaried roles from its 2022 peak of 58,000. Some exits came from the wind-down of its Cruise robotaxi unit. Others followed repeated workforce reviews under CEO Mary Barra. This month alone GM eliminated 500 to 600 information-technology jobs globally, many in Texas and Michigan. The move targeted positions the company no longer needs. At the same time GM listed more than 250 AI-related openings in the United States. “GM is transforming its Information Technology organization to better position the company for the future,” the automaker said in a statement. “As part of that work, we have made the difficult decision to eliminate certain roles globally.”
Ford trimmed roughly 5,300 salaried positions from its 2020 high, landing near 30,700 last year. Stellantis reduced its U.S. white-collar count from 15,000 in 2020 to about 11,000. The company nevertheless plans to add more than 2,000 such jobs in North America as part of a turnaround effort. Across the three automakers more than 2,000 U.S. roles remain open. Nearly 400 involve AI directly.
The numbers tell only part of the story. Executives have grown blunt about what lies ahead. Ford CEO Jim Farley delivered the starkest assessment last July at the Aspen Ideas Festival. “Artificial intelligence is going to replace literally half of all white-collar workers in the U.S.,” he said. He added that AI “will leave a lot of white-collar people behind.” The comment, reported by The Wall Street Journal, marked a shift. CEOs once hesitated to link job losses directly to new technology. No longer.
Barra struck a similar note on talent needs. “Sometimes the people who got you to ‘point A’ aren’t necessarily people who are going to get you to ‘point B,’” she told the Automotive Press Association in January. The line captured the tension inside these companies. Skills that powered traditional auto design and manufacturing don’t always translate to an era of software-defined cars and generative design tools.
One laid-off GM programmer and data scientist watched the change up close. Speaking anonymously to CNBC, the veteran said the company intends to push AI into everyday tasks. “They’re going to push AI for everyday work and everything else. I’ve seen it firsthand. It can make you much more productive, as a programmer. It can really help you get more work done.” Then came the caveat. “But AI isn’t going to do you any good if you don’t know the business.”
Industry consultants echo that caution. Gregory Emerson, a managing director at BCG, warned that companies cutting too deeply risk losing institutional knowledge. Productivity could suffer. Critical talent might walk. Lenny LaRocca, who leads KPMG’s automotive practice in the Americas, sees the effort as broader than headcount reduction. “I don’t know necessarily if it’s just to reduce headcounts. I think the focus is more on how do they do their job better and how to be more innovative and move quicker.”
Gad Levanon, chief economist at the Burning Glass Institute, expects AI to automate repetitive office work in finance, information technology and clerical functions. Some losses will be offset by demand in autonomous systems, cybersecurity and software-defined vehicles. Yet the net direction looks clear. BCG forecasts that 10 to 15 percent of U.S. jobs could disappear because of AI within five years. Another 50 to 55 percent will be reshaped over the next two to three years.
Not every automaker follows the same path. Toyota expanded its U.S. white-collar workforce by 31 percent from 2020 through 2025, reaching roughly 47,500 people. The broader U.S. motor vehicle manufacturing sector, which includes both salaried and hourly workers, saw white-collar jobs fall only 0.2 percent to 285,800. The Detroit Three’s steeper declines reflect their legacy burdens and heavier exposure to the transition away from internal-combustion engines.
GM has turned to AI in vehicle design itself. The company uses the technology to generate sketches, optimize structures and accelerate engineering decisions. Bryan Styles, GM’s director of design innovation and technology operations, told the Detroit Free Press that AI raises expectations for speed and output. Designers must deliver more with greater efficiency. The company insists no design jobs have been cut solely because of these tools. Still, last October GM eliminated more than 200 computer-aided design positions at its Warren technical center to sharpen focus on core architecture work.
The pattern repeats across functions. Legacy IT maintenance roles shrink. Positions that once required manual coding or routine analysis give way to oversight of AI systems. Engineers who once spent days iterating on vehicle components now review outputs generated in minutes. The productivity gains look real. The headcount implications worry both workers and some executives.
Competitive pressure adds urgency. Chinese automakers produce vehicles at lower cost without the same overhead. U.S. policymakers debate bans on connected Chinese cars over security concerns. Legacy Detroit players must move faster or lose ground. AI offers one route to that speed. It also forces uncomfortable choices about which employees stay and which skills matter most.
Industry analysts note the shift from traditional engineering and administrative roles toward data science, machine learning and software integration. The Detroit Three continue to recruit aggressively in those fields even as they trim elsewhere. The result is a smaller but, they hope, more capable workforce. Whether that bet pays off will shape not only their bottom lines but the future composition of auto-industry employment.
Farley’s prediction hangs over the sector. Half of all white-collar jobs replaced. The claim sounds extreme to some. Others see it as a blunt acknowledgment of trends already visible in design studios, IT departments and finance teams. The Detroit Three have already traveled far down this road. AI promises to determine how much farther they go. And how many more offices empty along the way.
Detroit’s White-Collar Reckoning: 20,000 Salaried Jobs Gone as AI Accelerates Auto Industry Overhaul first appeared on Web and IT News.