Author: Claude, Shenchao TechFlow
Shenchao Introduction: A Gartner survey of 350 companies with annual revenues exceeding $1 billion shows that 80% of firms that have deployed AI or automation technologies have implemented layoffs, but there is no positive correlation between the layoff rate and return on investment—companies that cut more jobs aren't earning more than those that cut fewer.
Companies achieving high returns are actually those using AI to amplify employee output rather than replace employees. Meanwhile, in the first four months of 2026, nearly 50,000 positions have been cut due to AI, and tech industry layoffs have hit a new high since 2023.
The logic of companies using AI to replace employees is being contradicted by data.
According to a Fortune report on May 11, a survey by research and advisory firm Gartner of 350 global corporate executives found that companies conducting major layoffs in the name of AI have not gained better financial returns as a result. The surveyed companies all have annual revenues exceeding $1 billion and are already piloting or deploying AI agents, intelligent automation, or autonomous technologies.
Helen Poitevin, Vice President Analyst at Gartner and lead researcher for the study, told Fortune: "Focusing solely on layoffs to extract value from AI is a short-sighted move. Purely chasing returns by cutting headcount is likely to lead most companies down a dead-end with limited gains."
This survey was completed in Q3 2025. Its conclusion is bluntly glaring: Layoffs create budgetary space, not return on investment.
80% of Companies Cut Jobs, But Those Cutting More Aren't Earning More Than Those Cutting Less
Gartner's core finding is: Among companies that have deployed autonomous business capabilities, about 80% reported layoff actions. However, there is almost no difference in the proportion of layoffs between high-return companies and low-return (or even performance-deteriorating) companies.
In other words, from a statistical perspective, there is no discernible causal relationship between cutting jobs and making money.
The survey shows that companies achieving the highest returns are taking an opposite path. They position AI as "people amplification," using technology to enhance the output efficiency of existing employees rather than directly replacing human labor. Poitevin calls this model the "human-amplified business," where AI empowers humans rather than replaces them.
In another independent Gartner survey targeting CEOs, about one-third of executives expect AI to assist humans in decision-making but not make independent decisions, while another 27% expect AI to operate autonomously with minimal or no human intervention. The divergence between these two approaches is deepening.
Nearly 50,000 Jobs Cut Due to AI in First Four Months of This Year, Tech Industry Layoffs Hit Three-Year High
Gartner's research conclusions sharply contrast with the current reality of the job market.
According to the latest report released in May by outplacement firm Challenger, Gray & Christmas, AI has been the primary reason for U.S. corporate layoffs for two consecutive months. In April 2026, 21,490 positions were cut due to AI, accounting for 26% of the total layoffs of 83,387 that month. Cumulatively for the first four months of 2026, positions cut due to AI reached 49,135, representing about 16% of the year's total layoffs so far, up from 13% at the end of March.
Andy Challenger, Chief Revenue Officer at Challenger, summarized it pointedly: "Whether individual roles are truly being replaced by AI or not, the budget for those roles is being taken by AI."
By industry, the tech sector is the hardest hit. The tech industry cut 33,361 jobs in April, with a year-to-date total of 85,411, a 33% increase year-over-year, the highest for the period since 2023. Cognizant plans to cut 12,000 to 15,000 jobs globally, Cloudflare is laying off about 1,100 employees (approximately 20% of its workforce), Coinbase is cutting 14% of its staff, and Snap is eliminating 1,000 positions—all citing AI as a core driver.
Contrasting with the layoff wave is a sharp contraction in hiring. In April, companies announced only 10,049 new hiring plans, a staggering 69% decrease month-over-month and a 38% drop year-over-year.
"AI Washing" Layoffs: How Many Layoffs Are Really Due to AI?
A recurring question is raised: How many of the layoffs implemented by companies in the name of AI are genuinely driven by AI?
OpenAI CEO Sam Altman directly raised this question in an interview this past February. He acknowledged the existence of so-called "AI washing" phenomena: companies packaging layoffs they would have conducted anyway as AI-driven structural adjustments. "I don't know the exact percentage, but there is certainly some AI washing, where people attribute layoffs they were going to do anyway to AI," Altman said.
Deutsche Bank analysts also noted in a recent research report that "AI redundancy washing will be a prominent feature of 2026," with large companies using AI as a rhetorical shield for layoffs, while actual drivers may be tariffs, economic uncertainty, or other cost pressures.
Gartner's Poitevin leans towards a milder interpretation: current AI-related layoffs are more like companies "testing the waters" rather than genuine structural resets. "In our view, this looks more like a one-off, small-scale experiment for many companies, not something that translates into full return on AI investment."
Long-term Forecast: AI to Become a Net Job Creator by 2028-2029
Gartner's stance is distinctly two-sided.
Short-term data is not optimistic. Previous Gartner research shows that AI agents successfully complete standard office tasks about 30% to 35% of the time. Gartner also predicts that over 40% of AI agent projects will be canceled by the end of 2027 due to cost overruns, unclear business value, and insufficient risk management.
But Gartner offers an optimistic long-term forecast: autonomous business will begin to become a net job creator between 2028 and 2029, when new types of jobs that AI cannot perform will emerge. Poitevin emphasizes: "In the long term, autonomous business will create more work for humans, not less. Structural factors like demographic decline and high-trust consumption scenarios will ensure that human capital remains central to operating, governing, and scaling autonomous systems."
On the spending front, Gartner expects AI agent software spending to grow from $86.4 billion in 2025 to $206.5 billion in 2026, and to $376.3 billion in 2027. Even with most projects failing, capital is still accelerating its influx.
This creates an absurd yet real situation: corporate layoffs have not brought returns, AI project failure rates remain high, but no one is willing to get off the ride.
