Detroit Automakers Have Already Cut Over 20,000 White-Collar Jobs in the US as Artificial Intelligence Advances
Artificial intelligence is no longer the stuff of science fiction or a topic reserved for tech conferences. It is already embedded inside the worlds largest automakers, reshuffling teams, eliminating roles, and reshaping the future of office work in real time. And the numbers that have just come to light reveal a scale few expected to see this soon.
The Big Three of the American auto industry — GM, Ford, and Stellantis — have collectively eliminated more than 20,000 salaried positions in the United States. That represents 19% of their combined white-collar workforces, calculated from peak hiring levels recorded this decade, according to public filings and employment data provided by the companies themselves.
That is not a small number.
And what makes this shift even more significant is the context behind it: the digital transformation accelerated by the rise of AI is concentrating its effects on exactly the people who always felt the safest in the job market — so-called white-collar workers, those in administrative, financial, and information technology roles.
Jim Farley, CEO of Ford, went as far as publicly stating during the Aspen Ideas Festival in July that AI will replace literally half of all white-collar workers in the US. A blunt statement, but one that is starting to find backing in the hard data coming out of Detroit.
What is happening with the American automakers is, in practice, one of the first major real-world tests of how artificial intelligence impacts the labor market at scale. And the results deserve the attention of everyone who works — or plans to work — in tech. 👇
What Is Behind This Massive Wave of Job Cuts
When a company lays off workers on a large scale, the initial read is usually financial trouble, declining sales, or a one-off restructuring. But what is happening at GM, Ford, and Stellantis goes beyond that. The reasons for headcount reduction vary from automaker to automaker, but they are broadly tied to the technological changes sweeping through the auto industry: the rise of software-defined vehicles, autonomous vehicles, fully electric cars, and more recently, the massive incorporation of artificial intelligence into corporate processes.
General Motors led the cuts by a wide margin. The automaker reduced its US salaried workforce by roughly 11,000 people between 2022 and the end of last year. Keep in mind that GM had significantly ramped up hiring before that, jumping from 48,000 white-collar workers in 2020 to 58,000 in 2022. That expansion was followed by a sharp pullback, driven both by the shutdown of its Cruise robotaxi program and by ongoing internal workforce evaluations under CEO Mary Barra.
Ford Motor and Stellantis, the parent company of the Chrysler brand, made more gradual cuts. Ford reduced its salaried workforce by about 5,300 employees since its peak employment in 2020, landing at approximately 30,700 workers in that category by the end of last year. Stellantis went from 15,000 salaried employees in 2020 to roughly 11,000 over the same period.
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In total, combined white-collar employment across the three automakers peaked at approximately 102,000 positions in 2022. By the end of last year, that number had dropped 13%, falling to 88,700 people. We are talking about a real, sustained, and structural reduction — not a short-term adjustment.
GM Ramps Up IT Layoffs With a Focus on AI
Just this past week, General Motors added another round of cuts to its track record, laying off between 500 and 600 salaried employees globally. According to sources close to the matter who spoke anonymously to CNBC, the cuts were concentrated in information technology operations in Texas and Michigan. And part of those layoffs was directly attributed to shifting workforce needs driven by the adoption of artificial intelligence.
What makes this situation particularly complex is that, even as it lets go of traditional IT professionals, GM is actively hiring for AI-related positions and encouraging its remaining employees to embrace the companys artificial intelligence platforms. It is a real-time swap: the employee who did the work the conventional way walks out the door, the tool that automates a significant chunk of that work steps in, and only those who can operate within this new model stick around.
A veteran programmer and data scientist at GM, who was laid off in this latest round, shared his perspective with CNBC anonymously. He said the company is pushing AI into day-to-day work and into everything else. He acknowledged that the technology can make a programmer far more productive and help deliver more output, but he made an important point: AI is not going to do you any good if you do not know the business. That is something that often gets lost in the conversation — the tool is powerful, but without business context, it does not solve real problems on its own.
Before these most recent IT layoffs, the most significant reductions at GM were tied to the shutdown of its Cruise robotaxi program, which the company decided to wind down at the end of 2024, and to recurring organizational efficiency reviews. Mary Barra, GM CEO, commented during an Automotive Press Association meeting in January that sometimes the people who got you to a certain point are not necessarily the same ones who are going to take you to the next stage.
Why White-Collar Workers Are at the Center of This Story
For decades, the automation debate revolved around factory-floor workers. Automated assembly lines, industrial robots, mechanical arms replacing manual operators — that was the prevailing image whenever the conversation turned to technology eliminating jobs in the auto industry. Office professionals, the ones with college degrees, management badges, and reserved offices, were considered the most protected group. Their roles involved judgment, creativity, interpersonal skills, and contextual decision-making — traits that machines, for a long time, simply could not replicate.
But the latest generation of artificial intelligence has changed exactly that. It did not come to tighten bolts faster. It came to read contracts, interpret balance sheets, answer emails, prioritize tasks, generate code documentation, and suggest data-driven strategies. In other words, it came to do exactly what white-collar professionals do — and at a scale no human can match.
Gad Levanon, chief economist at the Burning Glass Institute, a nonprofit focused on labor market data, reinforces this view. According to him, the jobs at greatest risk of being replaced by AI are administrative positions and repetitive office functions, like those found in finance and information technology, including programming. Levanon believes many white-collar workers will lose their jobs because AI can automate a significant portion of their tasks, though he acknowledges that some losses will be offset by new roles in strategic areas like autonomous vehicles, cybersecurity, and software-defined vehicles. In his view, this will be a dominant trend over the next decade or two.
This is a point that deserves special attention because it flips a logic that many people still hold onto. Tech professionals, analysts, corporate lawyers, accountants, and project managers tend to feel they are on the safe side of automation — that they are the ones implementing the tools, not the ones being displaced by them. But what the data from the Big Three shows is exactly the opposite. Job cuts are hitting hardest in precisely these categories, and the trend is set to deepen as AI tools become cheaper, more accessible, and more tightly integrated into corporate workflows.
Not Everyone Is Cutting — And Automakers Are Still Hiring
It is important to put the decline in salaried employment at the Big Three in context. It does not necessarily represent what is happening across the entire American auto industry. According to the US Bureau of Labor Statistics, jobs in motor vehicle manufacturing fell only 0.2% between 2022 and last year, totaling 285,800 workers — a number that includes both salaried and hourly employees.
And not every automaker is downsizing. Toyota Motor, for example, saw a roughly 31% increase in its US white-collar workforce between 2020 and 2025, reaching about 47,500 people. That contrast shows that mass layoffs are not a universal industry playbook but rather a strategic choice the American automakers are making in response to specific competitive pressures.
On top of that, GM, Ford, and Stellantis themselves are still hiring for certain roles. Antonio Filosa, CEO of Stellantis who is leading a global turnaround plan with a cost-cutting program, said the company still plans to add more than 2,000 white-collar positions in North America. And together, the three automakers currently have over 2,000 open positions in the United States, according to their career websites.
Of that total, nearly 400 involve artificial intelligence, with GM alone seeking more than 250 AI-related positions. That data point is quite telling: the companies are not simply laying people off and closing positions. They are swapping out profiles — traditional roles go away and positions requiring skills in AI, machine learning, automation, and advanced data analytics come in. 🤖
Expert Warnings About Strategy and Caution
While the numbers speak for themselves, there is a growing debate about how automakers should manage this transition. Lenny LaRocca, leader of the automotive practice at consulting firm KPMG in the Americas, raises an important point. According to him, automakers need to be careful about how they execute their AI strategies alongside their workforce.
For LaRocca, the focus should be on how to use AI to become more efficient, more profitable, and more innovative, and not necessarily on simply reducing headcount. It is a distinction that might seem subtle, but in practice it determines whether a company will maintain its capacity for innovation and institutional knowledge over time, or whether it will end up hollowing out its foundations while trying to save money in the short term.
Gregory Emerson, managing director and senior partner at the Boston Consulting Group, reinforces that perspective with forward-looking data. According to BCG projections, within five years — or maybe a bit further out — between 10% and 15% of US jobs could be eliminated as AI proliferates. At the same time, between 50% and 55% of American jobs are expected to be reshaped by artificial intelligence within the next two to three years.
Emersons message goes beyond the numbers and touches on a fundamental strategic point. He warns that companies that cut their workforce beyond AIs actual ability to replace it will see productivity drop, institutional knowledge vanish, and their best talent walk out the door. On the other hand, those that fail to radically rethink how work gets done will watch their competitors grow faster and more profitably.
This shift, according to the report co-authored by Emerson, is already underway — and it will accelerate as AI adoption spreads across more sectors and more companies.
What Detroit Reveals About the Future of Work With AI
Detroit has always been a barometer of the American job market. When the automakers struggle, the impact ripples across the entire supply chain, from parts suppliers to service providers, from small local businesses to pension funds. And when they adopt a new technology at scale, it tends to signal what is coming for other industries.
What is happening now with GM, Ford, and Stellantis is not a phenomenon isolated to the auto industry. It is a pilot run for what is likely to repeat in banking, insurance, consulting, law firms, tech companies, and any organization that still relies heavily on repeatable cognitive work to function.
The difference between this moment and previous waves of automation is the speed and breadth of the impact. In earlier industrial revolutions, there was time for displaced workers to reskill, for new types of jobs to emerge, and for society to adjust its educational and economic structures. This time, the pace of artificial intelligence adoption is far outstripping the ability of people and institutions to adapt. The automakers have eliminated over 20,000 positions in a relatively short window, and the AI systems taking over those functions are already operating, already delivering results, and already being expanded.
That puts a concrete question on the table for any professional following this space: which skills are still genuinely irreplaceable within the current corporate landscape? The most honest answer, based on what is being observed at major companies, points to capabilities like leading through uncertainty, managing complex relationships, original creation with an emotional component, and decision-making in scenarios without enough data. Anything that can be described as a process is likely to become a target for automation.
GM, Ford, and Stellantis declined to comment specifically on the reductions in their white-collar ranks in recent years. In previous statements, the automakers cited terms like transformations, bold choices, cost-cutting, and strengthening business units as justifications for the adjustments. Those are corporate phrases that, translated into the real world, mean that artificial intelligence is taking over the role that thousands of human professionals once filled — and that there is no turning back. 🚗💨
The Numbers in Perspective
To grasp the true scale of what is being discussed, it helps to lay the data side by side:
- GM: reduced its US salaried workforce by approximately 11,000 people between 2022 and the end of last year, after expanding from 48,000 to 58,000 between 2020 and 2022. This week, it laid off an additional 500 to 600 people, primarily in IT.
- Ford: eliminated about 5,300 salaried positions since its 2020 peak, landing at approximately 30,700 employees in that category.
- Stellantis: went from 15,000 salaried employees in 2020 to roughly 11,000, a reduction of about 4,000 positions focused on its American operations.
Meanwhile, the three automakers together have over 2,000 open positions — nearly 400 of them directly tied to artificial intelligence. What these numbers reveal, when viewed together, is that we are looking at a deep structural shift. AI is being used as a lever to redefine the ideal size of corporate teams, and that redefinition is hitting first — and hardest — the very professionals who historically held the most stable and best-compensated positions within these organizations.
The signal coming from Detroit is clear: the transformation has already begun, and anyone who is not prepared to adapt runs the risk of being left behind in a job market that is changing faster than any previous forecast managed to anticipate.
