AI Layoffs: Corporate Cost-Cutting Disguised as Technological Progress

Why AI-Fueled Layoffs Will Backfire

Right now there seem to be only two types of business headlines: Those dedicated to the eye-popping investments and valuations of the ever-expanding AI boom, and those chronicling a stream of layoff announcements. Strikingly, you'll often see the same company names appearing in both. It makes sense, I suppose. Employers in thrall to the possibilities of this powerful new technology are betting it will drive productivity -- meaning fewer humans are needed. (And the post-layoff stock bump doesn't hurt.) But ultimately, many of these cuts will likely prove unwise. In fact, they may undermine the very thing companies are so focused on: the ability to use AI to its fullest potential.

Mass Layoffs Are Scary, but Probably Not a Sign of the A.I. Apocalypse

Despite fears that Amazon and other employers are already replacing workers with bots, the A.I. transition is likely to play out differently. Amazon's announcement last month that it was cutting 14,000 corporate positions included an alarming warning for those worried that the artificial intelligence apocalypse may have arrived. A.I. is "enabling companies to innovate much faster than ever before," a senior vice president wrote in a message to employees that the company shared publicly. And to realize this potential, the executive suggested, "we're convinced that we need to be organized more leanly, with fewer layers." The announcement, combined with other layoff news from companies like Target, UPS, Microsoft and IBM, has prompted some to suggest that the economy has entered a period of A.I.-driven restructuring. But the A.I. apocalypse is probably not here just yet. While the technology may have played an indirect role in some of the downsizing, experts say the transition to an A.I.-powered workplace most likely won't entail large-scale layoffs in which employers dump humans in favor of machines. Rather, the transition is likely to be more gradual, in many cases occurring as new companies, built to exploit A.I., take market share from more established companies that are slower to embrace it. "Widespread adoption is going to happen at the new firms," said Mert Demirer, an economist at M.I.T. "It's always the case that the smaller the production process, the more the process is easier to change." Among established companies, those in the tech industry appear to be furthest along in adopting artificial intelligence. Employers like Amazon, Microsoft and Google have made a number of A.I. tools available to their white-collar employees, such as A.I. assistants that suggest lines of code, so-called agents that can generate whole sections of computer programs, and chatbots that can produce drafts of memos and reports. But employees at Amazon, where the announced job cuts affected less than 5 percent of corporate workers, say the adoption of these tools has been uneven across different teams and organizations. And thus far, the layoffs and buyouts at big tech companies do not appear to have been driven by the automation of white-collar jobs directly. "We do think that at some point A.I. tools will allow us to enhance productivity to a point that we're going to need less labor, but we're not there yet, not in any significant way," said Gil Luria, an analyst who covers Microsoft and Amazon for the investment bank D.A. Davidson. Instead, he added, the companies appear to be making the cuts partly to hold their overall profit margins steady while they spend tens of billions of dollars on A.I. infrastructure like data centers. Cutting back on employees is a way to convince shareholders that the companies are "investing in a responsible manner," Mr. Luria said. Amazon said that different companies were funding their A.I. investments in different ways, and that while some couldn't afford their investments, Amazon could. The use of A.I. tools appears to be even less intensive outside technology companies. In a recent survey by McKinsey, the consulting firm, almost 80 percent of companies reported using generative A.I., but about the same number reported that the tools had not significantly affected their earnings. A study released this summer by researchers at M.I.T. reached a similar conclusion, finding that industries other than technology and media showed "little structural change" as a result of A.I. In some cases, laying off workers is less about automating their jobs today than gambling that they won't be needed in the future. Over the past few years, many employers have engaged in "labor hoarding" -- hanging on to workers they no longer need because they may have use for them in a year or two and don't want to go through the trouble of hiring again. But given the possibility that advances in A.I. will reduce the need for workers on that timetable, these companies feel more comfortable laying them off. "The whole motive of labor hoarding is that you're going to need workers when demand picks up again," said Benjamin Friedrich, a labor economist at Northwestern University's Kellogg School of Management. "You want to be ready to go." It's unlikely, however, that big established companies will be able to substitute A.I. for large numbers of workers over the next year or two. One reason is that big companies are by their nature plodding and bureaucratic when reimagining their work processes. The McKinsey report observed that many companies' flirtation with A.I. had involved "a proliferation of disconnected micro-initiatives" that suffered from "limited coordination." But a more important reason has to do with a deeper conservatism: Established companies tend to use new technology to do what they've always done, only somewhat faster and less expensively, said Andrew McAfee, a principal research scientist at M.I.T.'s Sloan School of Management. They don't tend to rethink their entire structure. By contrast, new companies often ask how best to organize themselves when starting from scratch, without the employees or rituals that the new technology renders obsolete. Dr. McAfee, who is also a founder of Workhelix, an A.I. start-up, cited the electrification of factories that began in the late 19th century as an example. During the first few decades of electrification, he said, many factory owners simply began powering their machines with electricity rather than steam. But they didn't reorganize their processes. It was only when entrepreneurs reimagined the factory to incorporate new layouts and new processes like assembly lines that electricity brought enormous productivity gains. Something similar is likely to play out with A.I.: a long period of marginal changes at established companies before new businesses eventually change the way work is staffed and organized. In the legal profession, for example, large firms have long deployed teams of partners and several associates, billing clients for each lawyer's services at an hourly rate. But some entrepreneurs have recently started companies that rely on vastly fewer legal experts per client, supporting them with A.I. instead. "Professional services firms are still generally operating on a time- and materials-based business model, which disincentivizes using A.I. to cut hours," said Omar Haroun, chief executive of the parent company of Eudia Counsel, a so-called A.I.-native law firm. "We're actually trying to prove that one knowledge worker can do the work of 10."

AI isn't replacing jobs. AI spending is

For decades now, we have been told that artificial intelligence systems will soon replace human workers. Sixty years ago, for example, Herbert Simon, who received a Nobel Prize in economics and a Turing Award in computing, predicted that "machines will be capable, within 20 years, of doing any work a man can do." More recently, we have Daniel Susskind's 2020 award-winning book with the title that says it all: A World Without Work. Are these bleak predictions finally coming true? ChatGPT turns 3 years old this month, and many think large language models will finally deliver on the promise of AI replacing human workers. LLMs can be used to write emails and reports, summarize documents, and otherwise do many of the tasks that managers are supposed to do. Other forms of generative AI can create images and videos for advertising or code for software. From Amazon to General Motors to Booz Allen Hamilton, layoffs are being announced and blamed on AI. Amazon said it would cut 14,000 corporate jobs. United Parcel Service (UPS) said it had reduced its management workforce by about 14,000 positions over the past 22 months. And Target said it would cut 1,800 corporate roles. Some academic economists have also chimed in: The St. Louis Federal Reserve found a (weak) correlation between theoretical AI exposure and actual AI adoption in 12 occupational categories. Yet we remain skeptical of the claim that AI is responsible for these layoffs. A recent MIT Media Lab study found that 95% of generative AI pilot business projects were failing. Another survey by Atlassian concluded that 96% of businesses "have not seen dramatic improvements in organizational efficiency, innovation, or work quality." Still another study found that 40% of the business people surveyed have received "AI slop" at work in the last month and that it takes nearly two hours, on average, to fix each instance of slop. In addition, they "no longer trust their AI-enabled peers, find them less creative, and find them less intelligent or capable."

AI Isn't Replacing Jobs. AI Spending Is

For decades now, we have been told that artificial intelligence systems will soon replace human workers. Sixty years ago, for example, Herbert Simon, who received a Nobel Prize in economics and a Turing Award in computing, predicted that "machines will be capable, within 20 years, of doing any work a man can do." More recently, we have Daniel Susskind's 2020 award-winning book with the title that says it all: A World Without Work. Are these bleak predictions finally coming true? ChatGPT turns 3 years old this month, and many think large language models will finally deliver on the promise of AI replacing human workers. LLMs can be used to write emails and reports, summarize documents, and otherwise do many of the tasks that managers are supposed to do. Other forms of generative AI can create images and videos for advertising or code for software. From Amazon to General Motors to Booz Allen Hamilton, layoffs are being announced and blamed on AI. Amazon said it would cut 14,000 corporate jobs. United Parcel Service (UPS) said it had reduced its management workforce by about 14,000 positions over the past 22 months. And Target said it would cut 1,800 corporate roles. Some academic economists have also chimed in: The St. Louis Federal Reserve found a (weak) correlation between theoretical AI exposure and actual AI adoption in 12 occupational categories. Yet we remain skeptical of the claim that AI is responsible for these layoffs. A recent MIT Media Lab study found that 95% of generative AI pilot business projects were failing. Another survey by Atlassian concluded that 96% of businesses "have not seen dramatic improvements in organizational efficiency, innovation, or work quality." Still another study found that 40% of the business people surveyed have received "AI slop" at work in the last month and that it takes nearly two hours, on average, to fix each instance of slop. In addition, they "no longer trust their AI-enabled peers, find them less creative, and find them less intelligent or capable." If AI isn't doing much, it's unlikely to be responsible for the layoffs. Some have pointed to the rapid hiring in the tech sector during and after the pandemic when the U.S. Federal Reserve set interest rates near zero, reports the BBC's Danielle Kaye. The resulting "hiring set these firms up for eventual workforce reductions, experts said -- a dynamic separate from the generative AI boom over the last three years," Kaye wrote. Others have pointed to fears that an impending recession may be starting due to higher tariffs, fewer foreign-worker visas, the government shutdown, a backlash against DEI and clean energy spending, ballooning federal government debt, and the presence of federal troops in U.S. cities. For layoffs in the tech sector, a likely culprit is the financial stress that companies are experiencing because of their huge spending on AI infrastructure. Companies that are spending a lot with no significant increases in revenue can try to sustain profitability by cutting costs. Amazon increased its total CapEx from $54 billion in 2023 to $84 billion in 2024, and an estimated $118 billion in 2025. Meta is securing a $27 billion credit line to fund its data centers. Oracle plans to borrow $25 billion annually over the next few years to fulfill its AI contracts. "We're running out of simple ways to secure more funding, so cost-cutting will follow," Pratik Ratadiya, head of product at AI startup Narravance, wrote on X. "I maintain that companies have overspent on LLMs before establishing a sustainable financial model for these expenses." We've seen this act before. When companies are financially stressed, a relatively easy solution is to lay off workers and ask those who are not laid off to work harder and be thankful that they still have jobs. AI is just a convenient excuse for this cost-cutting. Last week, when Amazon slashed 14,000 corporate jobs and hinted that more cuts could be coming, a top executive noted the current generation of AI is "enabling companies to innovate much faster than ever before." Shortly thereafter, another Amazon rep anonymously admitted to NBC News that "AI is not the reason behind the vast majority of reductions." On an investor call, Amazon CEO Andy Jassy admitted that the layoffs were "not even really AI driven." We have been following the slow growth in revenues for generative AI over the last few years, and the revenues are neither big enough to support the number of layoffs attributed to AI, nor to justify the capital expenditures on AI cloud infrastructure. Those expenditures may be approaching $1 trillion for 2025, while AI revenue -- which would be used to pay for the use of AI infrastructure to run the software -- will not exceed $30 billion this year. Are we to believe that such a small amount of revenue is driving economy-wide layoffs? Investors can't decide whether to cheer or fear these investments. The revenue is minuscule for AI-platform companies like OpenAI that are buyers, but is magnificent for companies like Nvidia that are sellers. Nvidia's market capitalization recently topped $5 trillion, while OpenAI admits that it will have $115 billion in cumulative losses by 2029. (Based on Sam Altman's history of overly optimistic predictions, we suspect the losses will be even larger.) The lack of transparency doesn't help. OpenAI, Anthropic, and other AI creators are not public companies that are required to release audited figures each quarter. And most Big Tech companies do not separate AI from other revenues. (Microsoft is the only one.) Thus, we are flying in the dark. Meanwhile, college graduates are having trouble finding jobs, and many young people are convinced by the end-of-work narrative that there is no point in preparing for jobs. Ironically, surrendering to this narrative makes them even less employable. The wild exaggerations from LLM promoters certainly help them raise funds for their quixotic quest for artificial general intelligence. But it brings us no closer to that goal, all while diverting valuable physical, financial, and human resources from more promising pursuits. By Gary N. Smith and Jeffrey Funk This article originally appeared in Inc.'s sister publication, Fast Company. Fast Company is the world's leading business media brand, with an editorial focus on innovation in technology, leadership, world changing ideas, creativity, and design. Written for and about the most progressive business leaders, Fast Company inspires readers to think expansively, lead with purpose, embrace change, and shape the future of business. The early-rate deadline for the 2026 Inc. Regionals Awards is Friday, November 14, at 11:59 p.m. PT. Apply now.

All those corporate layoffs? Don't blame AI.

Over the last few months, a number of well-known companies have announced layoffs of tens of thousands of workers. UPS said it is getting rid of 48,000 employees. Amazon is shedding 30,000. Intel is firing 24,000. IBM, Target, Nestle, Accenture and Ford are terminating many thousands more. The list goes on. And the culprit? According to many media reports, it's artificial intelligence. The "AI Destruction of Millions of Jobs Begins," says Yahoo Finance. "Tens of Thousands of White-Collar Jobs Are Disappearing as AI Starts to Bite," reports The Wall Street Journal. "A.I. Might Take Your Job," warns The New York Times. "The Nation's Largest Employers Are Putting Their Workers On Notice," says The Washington Post. Automation will kill jobs! Robots are destroying the world! The end is nigh! These stories get clicks. But the truth is, AI isn't the reason behind most of these job cutbacks. In fact, AI -- at least so far -- has not been working as well as hoped. A recent survey published by KPMG of more than 48,000 business people around the world found that only 46 percent trusted their AI systems. A similar poll of developers -- and these are the people who would know -- revealed that only one-third trusted the output of their AI-driven development tools, a number that has been declining from the technology's earlier years. "Almost right" is a phrase often heard. Many news outlets have recently reported on the "workslop" generated by AI chatbots. This includes blurry logos, nonsensical texts, generic or unpolished writing and poor coding that has forced companies to hire more freelancers to correct the end product that AI got wrong, with many finding it much easier for a human worker to just do the job themselves. "In April 2024, it seemed like agentic AI was going to be the next big thing," writes Steven Newman, an AI expert. "The ensuing 16 months have brought enormous progress on many fronts, but very little progress on real-world agency." According to a recent New York Times report, a whopping 80 percent of big companies who invested in AI projects this year said they saw "no significant bottom-line impact" with as many as 42 percent abandoning their efforts. At the same time, an MIT study found that 95 percent of AI pilot programs "failed to deliver a measurable profit-and-loss impact" and only about 5 percent of these pilots are achieving rapid revenue acceleration. "The 95 percent failure rate for enterprise AI solutions represents the clearest manifestation of the GenAI Divide," writes Zvi Mowshowitz, a former hedge fund manager and long-time AI commentator. "Organizations stuck on the wrong side continue investing in static tools that can't adapt to their workflows, while those crossing the divide focus on learning-capable systems." There are lots of surveys saying how many small businesses are adopting AI. But according to one of my clients, the HR firm Paychex, AI is not replacing workers; hiring has remained steady over the past year. And I think I know why -- I couldn't even create a simple image using any one of three popular AI chatbots. I need more employees to fix these problems! This is not to say that AI isn't having an impact. Bots are now doing the lion's share of coding at big tech firms, which is why they're shedding developers. Other AI systems are automating customer service and helping workers be more productive by creating policies, writing emails and analyzing spreadsheets. As the technology emerges from its 1.0 phase, when there's a reliable infrastructure and the inevitable bubble bursts that cleans out the bad ideas and the companies that never deserved to get their funding in the first place, what's left will be the applications and agents and hardware -- drones, robots, sensors -- that will truly use AI to do work in place of humans. But I don't know anyone who is replacing their employees with AI any time soon. Which brings me back to jobs. If it's not AI, then what's really behind all of these layoffs? That's simple: good old-fashioned corporate mismanagement. Just ask Andy Jassey. "The announcement (about layoffs) that we made a few days ago was not really financially driven and it's not even really AI driven, not right now," said Jassey, Amazon's CEO. "You end up with a lot more people than what you had before, and you end up with a lot more layers. Sometimes without realizing it, you can weaken the ownership of the people that you have who are doing the actual work and who own most of the two-way door decisions." Or listen to Target's Michael Fiddelke. "The complexity we've created over time has been holding us back," said Target's current COO and soon to be CEO. "Too many layers and overlapping work have slowed decisions, making it harder to bring ideas to life." What Jassey and Fiddelke are actually saying: We screwed up. We over-hired. We changed our minds. We hired the wrong people. Our forecasts were wrong. We didn't anticipate a slowing economy, higher costs, rising tariffs, supply chain disruptions, consumer behavior, interest rate hikes and any number of other factors that caused these wrong decisions. When companies make mistakes and hire too many people, or the wrong people, they wait for the right time to cut the fat. This usually occurs when there's a financial downturn or a recession because that's easy to blame. In this case, it's the AI bubble. It's a much easier story to tell your shareholders and the public that management's actions are the result of smart technology investments instead of dumb, strategic mistakes. And the news outlets back up their claims for clicks. So the enticing, terrifying story of AI taking away jobs isn't really accurate, for the most part. The real reason for these layoffs is the same boring reason as before: fixing poor decisions. Gene Marks is founder of The Marks Group, a small-business consulting firm.

Why AI-fueled layoffs like Amazon will backfire

Companies are simultaneously announcing record AI investments and widespread layoffs, often for the same organizations. While AI is cited as a driver for these cuts, many initiatives show no return on investment. Layoffs, especially large ones, can undermine innovation and employee morale, potentially hindering the very AI adoption they aim to facilitate. Right now there seem to be only two types of business headlines: Those dedicated to the eye-popping investments and valuations of the ever-expanding AI boom, and those chronicling a stream of layoff announcements. Strikingly, you'll often see the same company names appearing in both. It makes sense, I suppose. Employers in thrall to the possibilities of this powerful new technology are betting it will drive productivity -- meaning fewer humans are needed. (And the post-layoff stock bump doesn't hurt.) But ultimately, many of these cuts will likely prove unwise. In fact, they may undermine the very thing companies are so focused on: the ability to use AI to its fullest potential. If the current downsizing is indeed a mistake, it's one a lot of employers are making: Last month, US companies made more job cuts than they have in any October for the last two decades. Meanwhile, many of the companies involved look healthier than ever. Amazon.com Inc., which has announced plans to shed as many as 30,000 corporate jobs, is enjoying record-high share prices, while Microsoft, which is undertaking its biggest layoffs in two years, recently reported a 12% increase in profit. So if not hardship, what is driving these layoffs? In at least some cases, AI is certainly a factor. Accenture PLC, for example, announced a cut of 11,000 workers in September, declaring that these employees "could not be retrained for an AI-driven workforce." And with AI fever sweeping corporate America, expect the technology to inspire more cuts soon. They may actually be an economic necessity: Geoffrey Hinton, the Nobel Prize-winning godfather of AI, claims the scale of capital investments made in AI is so large that the only way they can pay off is via massive job destruction. One problem: However promising AI tools appear, they don't always pay off for the businesses that use them. This isn't an argument that, as some prominent AI critics allege, that the technology is useless - I'm a ChatGPT convert myself. But a Massachusetts Institute of Technology survey of 300 publicly announced corporate AI initiatives found that the executives overseeing them reported that 95% had "zero" return on investment. When you think about it, that's not so surprising. These tools aren't just drop-ins that seamlessly replace workers. Most companies don't know how to exploit their full potential -- it's not clear anyone really does. Utilizing them properly is going to require significant changes in how work is done. This is a technology that's only a few years old and is changing by the day. With no clear roadmap to follow, companies are going to need to become more creative and innovative if they hope to adapt to an AI world and get the most out of the technology. The current wave of job cuts is likely to make that harder. That's because layoffs don't just harm the people who leave -- they also traumatize those who survive, hurting their morale and commitment and increasing stress. No wonder management research has also found that companies that conduct layoffs during a period of prosperity have worse financial performance than competitors who don't reduce headcount. What's more, these negative effects are strongest in the most innovative and rapidly-growing industries. A study of more than 2,000 Spanish companies, for example, found that when downsizing is combined with significant changes in equipment, techniques or processes (e.g., the type of transformation required to take advantage of AI), innovation declines because employees feel threatened and become less willing to take risks. A similar study of British firms found that although small and medium-sized layoffs don't significantly hinder innovation, large downsizing does. (Such unexpected effects may be one reason rehiring rates are going up.) This isn't to say that layoffs are all bad for the companies that do them; when organizations have too much slack, cuts may actually push them to become more innovative. But even there the path is fraught. If organizations are resource constrained (and given the scale of investment the AI arms race demands, even the wealthiest company could be), the effects of layoffs quickly turn negative once again. The paradox of innovations that are as transformative as AI is supposed to be is that they are never just plug-and-play. Inventing the technology is only the first step; learning how to use it is just as hard, and just as important. It requires employees who are ready to learn, take risks and embrace change -- not ones left traumatized and fearful after their colleagues have been brushed aside. Laying off people now in anticipation of AI's effects might seem very tempting to today's CEOs, but most of those who do will end up regretting it.