General Motors, Ford, and Stellantis have collectively eliminated more than 20,000 U.S. salaried positions from their recent peak headcounts, a 19 percent reduction in combined white-collar workforces, as the companies race to retool around artificial intelligence, software-defined vehicles, and a shifting regulatory landscape for electric cars.
GM accelerated the trend this week, laying off between 500 and 600 salaried workers globally, with the cuts concentrated in information technology operations in Texas and Michigan, CNBC reported. People familiar with the matter said the reductions were driven in part by changing workforce needs tied to AI adoption.
The numbers tell a clear story. Combined white-collar employment across the three Detroit automakers peaked at roughly 102,000 in 2022. By the end of last year, that figure had fallen 13 percent, to 88,700. GM alone shed approximately 11,000 salaried positions from 2022 through last year after expanding from 48,000 U.S. white-collar workers in 2020 to 58,000 in 2022. Ford scaled back by roughly 5,300 workers from its salaried peak in 2020 to about 30,700 last year. Stellantis dropped from 15,000 to about 11,000 over the same period.
Ford CEO Jim Farley put the matter bluntly at the Aspen Ideas Festival in July:
"Artificial intelligence is going to replace literally half of all white-collar workers in the U.S."
Farley added that "AI will leave a lot of white-collar people behind." That is a remarkable admission from the chief executive of a company that still employs tens of thousands of salaried Americans. It is also a preview of the argument corporate leadership will use to justify every round of cuts to come.
GM CEO Mary Barra offered a gentler version of the same logic during an Automotive Press Association meeting in January, addressing turnover in GM's top ranks. "Sometimes the people who got you to 'point A' aren't necessarily people who are going to get you to 'point B,'" she said. Under Barra's leadership, rolling evaluations of GM's workforce have become standard operating procedure.
An unnamed veteran programmer and data scientist for GM, speaking anonymously for fear of repercussions, told CNBC the direction is unmistakable. "They're going to push AI for everyday work and everything else," the employee said. "I've seen it firsthand. It can make you much more productive, as a programmer. It can really help you get more work done, but AI isn't going to do you any good if you don't know the business."
That last line deserves attention. The workers who understand the product, the supply chain, and the customer are not easily replaced by a chatbot. The ones who fill out spreadsheets and write routine code may be. The question is whether corporate leadership can tell the difference, or whether the headcount targets come first and the thinking comes later. GM's recent round of IT layoffs, reportedly delivered in 15-minute calls, suggests the process is not always surgical.
All three automakers declined to comment on the scope of their white-collar reductions in recent years. In past rounds of cuts, they have cited "transformations," "bold choices," cost-cutting, and making units more efficient. None of those phrases tell a laid-off IT specialist in Michigan much about where to find the next paycheck.
The salaried job losses stand in sharp contrast to overall motor vehicle manufacturing employment. U.S. Bureau of Labor Statistics data show those jobs dropped by just 0.2 percent from 2022 through last year, to 285,800 workers. In other words, the factory floor is holding relatively steady. The carnage is in the office park.
And it is not hitting every automaker equally. Toyota Motor reported a roughly 31 percent increase in its American white-collar workforce from 2020 through 2025, to approximately 47,500 people. That gap between Detroit's contraction and Toyota's expansion raises an uncomfortable question: Is the Big Three's downsizing a sign of strategic foresight, or a symptom of years of misallocated investment, including the headlong rush into electric vehicles that consumers have been slower to embrace than executives predicted?
The EV connection is hard to ignore. AP News reported that GM cut about 1,700 workers at EV-related plants in Michigan and Ohio because of slower near-term electric vehicle demand. That included roughly 1,200 jobs at an all-electric plant near Detroit and 550 at the Ultium Cells battery plant in Ohio. GM said it was "realigning EV capacity" due to slower adoption and "an evolving regulatory environment," and noted battery production pauses beginning in January 2026 at facilities in Ohio and Tennessee.
So the same companies that spent billions chasing an EV future, encouraged by federal mandates and subsidies, are now pulling back on both the factory workers who build those vehicles and the white-collar staff who designed and managed the programs. The workers pay twice: once when the company over-hired for a government-favored initiative, and again when reality forced a correction. Honda's recent first-ever annual loss under the weight of its own EV strategy shows the pattern extends well beyond Detroit.
The consulting class is already framing the next wave. Boston Consulting Group forecasts that within five years, or perhaps further out, 10 to 15 percent of U.S. jobs could be eliminated as AI spreads. Over the next two to three years, BCG projects 50 to 55 percent of American jobs will be "reshaped" by AI.
Gregory Emerson, a managing director and senior partner at BCG, wrote in a coauthored report that "this shift is already happening, and will pick up speed as AI adoption spreads." He added a warning for companies tempted to swing the axe too aggressively:
"Those who cut their workforce beyond AI's ability to replace it will see productivity drop, institutional knowledge disappear, and critical talent walk away. Those who fail to dramatically rethink work will see their competitors grow faster and more profitably."
Gad Levanon, chief economist at the Burning Glass Institute, a labor data nonprofit, identified the jobs most vulnerable: clerical positions and repetitive office roles in finance and information technology, including coding. "A lot of white collar workers will lose their jobs because AI can automate some of their tasks," Levanon said. "I think it will be a major trend in the next decade or two."
Lenny LaRocca, who leads KPMG's automotive practice in the Americas, urged caution. "They really need to think about how they adapt it and use it to generate, to be more efficient and be more profitable," he said. "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."
That is a reasonable distinction, in theory. In practice, the headcount numbers speak for themselves. More than 20,000 salaried positions are gone. Meanwhile, GM is pursuing massive profit margins from subscription fees and software services, a business model that requires fewer engineers and more algorithms.
The Detroit automakers currently have more than 2,000 open positions posted in the U.S. Nearly 400 of those involve AI. GM alone is seeking more than 250 AI-related roles. The message to the existing workforce is plain: retool yourself or find the door.
Stellantis CEO Antonio Filosa has said the company still plans to add more than 2,000 white-collar jobs in North America as part of a companywide turnaround that includes a global cost-cutting program. Whether those new hires offset the thousands already let go remains to be seen. Stellantis declined to comment on its recent reductions.
The dynamic playing out in Detroit is not unique to the auto industry, but it is especially visible there. These are companies that anchor entire regional economies. When GM cuts 500 IT workers in Texas and Michigan in a single week, the ripple moves through mortgage payments, school enrollments, and local tax rolls. GM is ramping up pickup truck production at a Michigan plant to meet strong gas-powered demand, a sign that consumer preferences and corporate strategy are not always aligned, and that the workers caught in between rarely get a say.
Several questions remain unanswered. How many of the 20,000 eliminated positions were genuinely redundant, and how many represented institutional knowledge that no AI tool can replicate? What share of GM's latest layoffs were directly caused by AI adoption versus broader cost-cutting? And will the new AI-focused hires go to Americans in Detroit and Michigan, or to contractors and remote workers elsewhere?
The automakers are not eager to answer. All three declined to discuss the reductions on the record. They have offered slogans, "transformations," "bold choices", but not accountability.
Corporate America has every right to adopt new technology and restructure for efficiency. No serious person argues otherwise. But when executives like Jim Farley predict that AI will replace "literally half" of white-collar workers, and then their companies quietly cut thousands while posting AI job listings, the people left behind deserve more than a buzzword and a 15-minute phone call.
The factory floor held steady. The office didn't. And the executives who made the promises, about EVs, about AI, about transformation, are still collecting their paychecks.