Author: Claude, Shenchao TechFlow

Senchao Introduction: A survey by Gartner of 350 companies with annual revenues exceeding one billion dollars shows that 80% of companies that deployed AI or automation technology have implemented layoffs, but there is no positive correlation between the layoff rate and return on investment—the companies that laid off more employees are not earning significantly more than those that laid off fewer.

The companies that truly achieve high returns are those that use AI to amplify employee output rather than replace employees. Meanwhile, nearly 50,000 jobs have already been cut due to AI in the first four months of 2026, marking a new high for layoffs in the tech industry since 2023.

The logic of companies replacing employees with AI is being debunked by the data.

According to a report from Fortune magazine on May 11, a survey by research and consulting firm Gartner found that companies that have conducted significant layoffs in the name of AI have not achieved better financial returns as a result. The companies surveyed have annual revenues exceeding one billion dollars and have piloted or deployed AI agents, intelligent automation, or autonomous technologies.

Helen Poitevin, Vice President Analyst and Chief Researcher of the study at Gartner, told Fortune: “Focusing solely on layoffs to capture AI value is short-sighted. Chasing returns purely through headcount reduction will likely lead most companies down a dead end with limited gains.”

This survey was completed in the third quarter of 2025. The conclusion is bluntly eye-opening: Layoffs create budget space, not investment returns.

80% of Companies Laid Off Employees, but Those That Laid Off More Did Not Earn More

Gartner's core finding is that among companies that have deployed autonomous business capabilities, about 80% reported layoffs. However, there is almost no difference in the layoff rates between high-return and low-return companies (or even companies with worsening performance).

In other words, there is no statistical causal relationship between layoffs and profitability.

The survey shows that the companies achieving the highest returns are taking a contrary approach. They view AI as a "people amplifier," using technology to enhance the output efficiency of existing employees rather than directly replacing human labor. Poitevin terms this model as "human-amplified business," where AI empowers humans rather than replaces them.

In another independent survey targeting CEOs, Gartner found that about one-third of executives expect AI to assist humans in decision-making but not to make decisions independently, while an additional 27% expect AI to operate autonomously with little or no human intervention. The divergence between these two routes is deepening.

In the First Four Months of This Year, Nearly 50,000 People were Laid Off Due to AI, Setting a Three-Year High in the Tech Industry

Gartner's research conclusions sharply contrast with the current realities of the job market.

According to the latest report released by employment placement company Challenger, Gray & Christmas in May, AI has become the primary reason for layoffs in American companies for two consecutive months. In April 2026, 21,490 jobs were cut due to AI, accounting for 26% of the total layoffs of 83,387 that month. In the first four months of 2026, a total of 49,135 jobs were cut due to AI, accounting for about 16% of the total layoffs for the year, up from 13% at the end of March.

Andy Challenger, Chief Revenue Officer at Challenger, summed it up succinctly: “Whether individual jobs have really been replaced by AI or not, the budgets for those positions have been taken by AI.”

By industry, the tech sector is the hardest hit. In April, 33,361 layoffs occurred in the tech industry, with a cumulative total of 85,411 year-to-date, a year-on-year increase of 33%, marking the highest in the same period since 2023. Cognizant plans to cut 12,000 to 15,000 jobs globally, Cloudflare laid off about 1,100 employees (about 20% of its total workforce), Coinbase cut 14% of its employees, and Snap eliminated 1,000 positions, all citing AI as a core driving factor.

In contrast to the wave of layoffs is a sharp contraction in the recruitment market. In April, companies announced new hiring plans for only 10,049 positions, a staggering 69% drop month-on-month and a 38% drop year-on-year.

"AI Washing" Layoffs: How Many Layoffs are Truly Driven by AI?

A recurrent question is: how many layoffs implemented by companies in the name of AI are actually driven by AI?

OpenAI CEO Sam Altman directly raised this question in an interview in February of this year. He candidly acknowledged the existence of so-called "AI washing": companies packaging layoffs that would have occurred anyway as AI-driven structural adjustments. “I don’t know what the exact proportion is, but there is indeed some AI washing, where layoffs that would have happened are attributed to AI,” Altman stated.

Analysts from Deutsche Bank also pointed out in a recent research report that "AI redundancy washing will be a prominent feature in 2026," with large companies using AI as a rhetorical shield for layoffs, while the actual drivers of layoffs could be tariffs, economic uncertainty, or other cost pressures.

Gartner's Poitevin leans toward a more tempered interpretation: current AI-related layoffs appear more like companies "testing the waters" rather than true structural resets. “From our perspective, this is more like a one-time, small-scale trial many companies are conducting, not a practice that can translate into full returns from AI investments.”

Long-Term Forecast: AI will Become a Net Job Creator in 2028-2029

Gartner's stance is notably dual-edged.

Short-term data is not optimistic. Previous studies by the agency have shown that the success rate of AI agents in standard office tasks is about 30% to 35%, and Gartner predicts that over 40% of AI agent projects will be canceled by the end of 2027 due to cost inflation, unclear commercial value, and inadequate risk management.

However, Gartner has provided an optimistic forecast for the long-term outlook: autonomous business will begin to become a net job creator starting in 2028 to 2029, at which point new job types will emerge that AI cannot handle. Poitevin emphasized: “In the long run, autonomous business will create more jobs for humans, not fewer. Structural factors such as demographic decline and high-trust consumption scenarios will ensure that human capital remains at the core of operating, governing, and scaling autonomous systems.”

In terms of spending, Gartner anticipates that AI agent software spending will grow from $86.4 billion in 2025 to $206.5 billion in 2026 and then to $376.3 billion in 2027. Even if most projects fail, capital is still accelerating its influx.

This creates an absurd yet real situation: layoffs by companies have not yielded returns, the failure rate of AI projects remains high, but no one is willing to exit the game.