Tech executives keep pointing to artificial intelligence as the force behind wave after wave of job cuts. The pattern looks familiar to Paul Osterman. The MIT Sloan professor emeritus has watched companies promise leaner operations for 20 years. Now they have a fresh label for it.
Wix became the latest to join the chorus. Late last week its CEO Avishai Abrahami told employees and investors the Israel-based website builder would shed about 20% of its workforce. That meant roughly 1,000 positions from a headcount of 5,277 at the end of the first quarter. He cited currency pressure from a strong shekel. He also highlighted AI. Fortune reported Abrahami called the technology “the most significant shift in how companies are built since the invention of modern programming languages in the 1970s.” The company needed to become “a faster, leaner, and flatter organization.”
His words carried echoes. Block CEO Jack Dorsey opened the year with plans to cut 4,000 jobs. He spoke of building “smaller and flatter” teams and embracing a “new way of working.” Snap and Atlassian deployed similar language in their own reductions. The message felt consistent. Technology demanded fewer layers. Productivity would rise. Staff counts would fall.
Osterman hears something else. “They’ve been saying that for 20 years,” he told Fortune. Executives reach for whatever rationale fits the moment. In downturns they blame the economy. During booms they talk efficiency. AI now supplies the perfect cover. “AI is a perfect excuse to justify big layoffs,” Osterman said. “It makes it seem as if it’s not our decision, our fault—it’s the technology.” Observers have labeled the tactic AI washing. Companies frame painful cuts as forward-looking moves. Markets sometimes reward the story. Cisco announced 4,000 layoffs this month yet saw its stock jump 13% the same day.
The broader numbers tell their own tale. Layoffs.fyi and other trackers show the tech sector has shed more than 130,000 jobs in 2026 so far. TrueUp data puts the 2026 total on pace toward 370,000 by year end. Many announcements mention AI explicitly. Reuters documented a surge in such references since late 2025. A Challenger, Gray & Christmas survey tied AI to 7% of planned U.S. layoffs announced in January. Goldman Sachs economists estimated the technology drove 5,000 to 10,000 net monthly job losses in exposed industries last year. Yet skeptics wonder how much represents genuine displacement versus convenient narrative.
Sam Altman has called out the exaggeration. The OpenAI CEO acknowledged at a BlackRock event that some firms engage in AI washing. They blame the technology for decisions rooted in other pressures. Overhiring during the pandemic. Rising costs. Slower growth. A New York Times investigation in February questioned how many companies possessed mature AI systems ready to replace the roles they eliminated. Forrester analysts argued many announcements reflected financially motivated cuts dressed up as technological inevitability. TechCrunch covered the debate early this year.
But something deeper may be at work. Osterman points to a structural change that predates the current AI boom. Companies have steadily increased their reliance on contractors, freelancers and gig workers. He estimates these “disposable workers” now comprise 35% of the American workforce. Official Bureau of Labor Statistics figures from 2023 put contingent workers at 6.9 million, or 4.3% of the total. That marked an increase from 3.8% in 2017. The real share sits higher when marginal employees and those with limited advancement paths get included.
These arrangements offer clear advantages to employers. No benefits costs. Easy to scale up or down. Less commitment during uncertain times. AI adds fresh uncertainty. Executives talk of agentic systems and automation that could reshape entire workflows. That uncertainty makes flexibility look attractive. Why lock in full-time headcount when the future feels unpredictable?
The human costs accumulate. Research shows contractors and temporary staff earn lower wages on average. They report less job satisfaction. They prove less likely to invest extra effort on behalf of employers. The system erodes the stable employment model that delivered shared prosperity after World War II. Osterman believes society need not accept permanent drift toward precarious work. “We created a stable employment system of high wages and shared prosperity in the past,” he said. “That’s what we should be thinking about doing now.” His forthcoming book, set for August release from Harvard University Press, lays out the evidence and policy ideas.
Recent developments keep the questions alive. Cloudflare cut more than 1,100 jobs in May, about 20% of its workforce, while noting a 600% spike in internal AI usage. Coinbase and Upwork announced reductions framed around AI restructuring. Meta has signaled possible further cuts of 20% or more to offset massive AI infrastructure spending. The Guardian tallied more than 165,000 tech layoffs over the past year. Its April reporting captured the tension between genuine productivity gains and corporate spin.
Venture capitalist Marc Andreessen, a vocal AI advocate, offered a blunt assessment on a podcast. Many large tech firms had grown overstaffed. AI now gave them “the silver-bullet excuse.” The remark aligned with Osterman’s view. Companies trim staff they wanted to trim anyway. They wrap the decision in innovation language. Employees sense the shift. Some hoard knowledge of personal AI tools rather than share productivity hacks that might accelerate their own obsolescence.
Yet AI does deliver measurable gains in certain tasks. Developers complete code faster. Support teams handle more queries. Marketing teams generate content at scale. The debate centers on degree. How many roles vanish outright versus change? How quickly? And who captures the value? Investors cheer margin expansion. Workers face uncertainty. Policymakers wrestle with retraining needs and potential inequality.
Osterman refuses fatalism. His analysis spans decades of labor market data. The move toward contingent work accelerated long before ChatGPT. AI supplies fresh justification and new tools to manage dispersed teams. The combination risks locking in a workforce model that treats large portions of talent as interchangeable. Companies gain agility. Society risks losing the loyalty, institutional knowledge and innovation that stable employment can foster.
Wix, Block, Snap and Atlassian represent only the visible cases. Hundreds of smaller cuts follow the same script. Each announcement cites AI. Few detail exact mechanisms or timelines for replacement technologies. The language stays high level. Flatter. Leaner. Faster. The pattern persists because it works. It reframes layoffs as strategy. It aligns with shareholder priorities. It deflects blame.
Industry insiders know the subtext. Headcount discipline matters in any market. The difference now lies in the storytelling. AI offers a narrative both futuristic and impersonal. Executives avoid sounding heartless. They sound visionary. Osterman sees through it. So do growing numbers of economists and labor researchers. The real conversation should address what kind of workforce America wants to build. Disposable by design? Or anchored in security that encourages risk-taking and long-term contribution?
The coming months will test which vision prevails. More companies will announce AI-driven restructurings. Some will back those claims with concrete automation deployments. Others will not. Tracking the gap between rhetoric and reality may prove the clearest measure of how seriously the industry takes its own promises. For now the evidence suggests many simply follow a well-worn path. They reduce staff. They praise technology. They move on. Workers bear the cost. The disposable model tightens its grip.
WebProNews is an iEntry Publication