More than 85,000 technology sector jobs have been eliminated in the United States through April 2026 — a 33% increase on the same period last year — and the companies doing the cutting are saying the same thing: AI made us do it. Automation anxiety, the creeping fear among workers that their roles are being quietly engineered out of existence, is no longer a fringe concern. It is rapidly becoming a defining feature of the post-2025 labour market.
The numbers crystallised with striking speed this week. Meta announced it was laying off roughly 8,000 employees — approximately 10% of its global workforce — while tax software giant Intuit said it was cutting around 3,000 positions, about 17% of its staff, as it accelerates AI integration into its product suite. In a memo to employees, Meta CEO Mark Zuckerberg offered a sobering admission: “success isn’t guaranteed” in the AI era, even for one of the world’s most valuable technology companies.
What Happened: A Week That Sharpened the Debate
The twin announcements from Meta and Intuit landed against a backdrop of broader workforce turbulence. According to placement firm Challenger, Gray & Christmas, more than 85,000 tech sector jobs have been cut through April 2026, representing a one-third increase year-over-year. Across all industries, over 300,000 layoffs have been recorded so far this year — though that figure is approximately half of last year’s total, a gap partly explained by the mass federal government reductions that dominated headlines in the early months of the second Trump administration.
Speaking at Web Summit Vancouver, Kyle Hanslovan, a cybersecurity entrepreneur, put it plainly: “I think many will be pressured in the next five years, where their job can be automated.” His remarks echoed a wider conversation unfolding across the technology industry about where human labour fits in an era of increasingly capable AI systems. The issue is not entirely new — we have been writing about whether and how governments should regulate AI for years — but the pace of corporate action is giving it a new and urgent edge.
Also at the Web Summit panel, Sim Desai, CEO of pre-IPO marketplace Hiive Capital, struck a more measured tone: “Inevitably there will be some disruption. We can’t pretend that there won’t be,” he said, but added that in the short term, “there’s a lot of job creation, because a lot of people are investing in adopting AI tools.”
Why Automation Anxiety Is Reaching a Tipping Point
Automation anxiety is no longer abstract. It has a face, a salary bracket, and increasingly, a graduation date. Anthropic co-founder and CEO Dario Amodei has predicted that AI could eliminate as much as half of all entry-level white-collar jobs within the next one to five years. That warning resonates with data from the New York Federal Reserve, which shows the unemployment rate for recent college graduates has climbed to 5.6% — well above the 35-year average of 4.5%. The cohort entering the workforce right now may be the most exposed of any in recent memory.
Public sentiment reflects that unease. A Stanford University study found that nearly two-thirds of Americans — 64% — expect AI to lead to fewer jobs over the next 20 years. That anxiety broke into open view when former Google CEO Eric Schmidt delivered a commencement address at the University of Arizona and told graduates that AI’s transformation would be “larger, faster and more consequential than what came before.” He was met with audible boos. It was a rare and telling moment: a technology leader visibly confronted by the human cost of the industry he helped build.
The concern is not limited to entry-level positions. The broader shift toward AI tools capable of replacing analytical and quantitative roles suggests that the disruption will eventually move up the skills ladder, not just sweep through it from the bottom. Finance, legal research, coding assistance, and data analysis — once considered safe harbours for educated workers — are all being reshaped by large language models and automation platforms.
That said, the macroeconomic picture remains stubbornly complicated. The U.S. economy has added 304,000 jobs through the first months of 2026, according to the Labour Department’s establishment survey. The overall unemployment rate sits at a historically low 4.3%. Amazon founder Jeff Bezos, speaking to CNBC, predicted that AI would ultimately generate a labour shortage, not a surplus: “it’s going to elevate all of these people. We’re going to have so much productivity.” Whether that optimism is well-founded or a convenient narrative for those benefiting most from the transition remains an open question.
The Uneven Nature of Automation Anxiety Across Industries
One of the underreported dynamics in this debate is how unevenly automation anxiety is distributed. Hanslovan, whose company Huntress operates in the cybersecurity space, told the Web Summit audience that he is “definitely hiring, even now more than I was before,” listing software engineers, detection engineers, product managers and sales leaders among active roles. Steven Schwartz, co-founder and CEO of creator marketplace Whop — valued at $1.6 billion — said he expects to have a bigger team in two years than today, even while acknowledging that “the future of work is in question in the era of AI.”
This reflects a pattern that has appeared in previous waves of technological disruption: automation tends to eliminate specific tasks and roles while simultaneously creating demand for new skills in adjacent areas. The challenge is that the transition is rarely clean, and the workers displaced are rarely the same ones who fill the new positions. A mid-career accountant and an early-career software tester face very different retraining options than a recent computer science graduate pivoting into AI-adjacent tooling.
The implications extend beyond individual careers. Companies integrating AI tools are discovering that they need fewer junior staff to complete the same volume of work — but they also need new categories of human oversight, prompt engineering, quality assurance, and strategic decision-making that AI systems cannot reliably provide. The ratio of humans to tasks is shifting, not necessarily collapsing. Understanding how AI tools are already reshaping smaller organisations offers a useful early signal for how larger enterprises may follow.
What Happens Next: Plausible Paths Forward
Several near-term developments are worth watching closely. First, the regulatory environment remains unresolved. President Donald Trump pulled a planned AI executive order at the last minute this week — one that would have required the federal government to pre-vet frontier AI models for cybersecurity risks — citing concerns that it could “be a blocker” to U.S. competitiveness in the global AI race. That decision suggests the current administration is likely to prioritise speed of adoption over guardrails, at least in the short term, which could accelerate corporate automation decisions with limited federal intervention.
Second, the pattern of large-company layoffs paired with AI investment announcements is unlikely to abate. Companies that have already taken restructuring charges — Meta and Intuit among them — will face shareholder pressure to demonstrate that the AI tools replacing those workers are generating measurable productivity and revenue gains. If those gains materialise quickly, expect other large employers to follow the same playbook. If they do not, expect a quieter reassessment of how aggressively companies communicate their AI strategies to avoid the reputational backlash of high-profile job cuts without clear benefit.
Third, the entry-level employment crisis among recent graduates may prompt institutional responses. Universities, already under pressure to justify tuition costs, could accelerate curriculum changes toward AI-adjacent skills. Employers may find themselves redesigning graduate programmes to account for a world where a first-year analyst with AI tools can produce the output previously associated with a team. Whether that restructuring benefits or further disadvantages new entrants will depend heavily on how companies choose to redistribute the productivity gains — and whether policymakers create any framework that shapes those choices. The debate about equitable outcomes in AI-assisted hiring and career development is one that labour economists and technologists will need to address together.
For workers navigating this uncertainty, the honest answer is that the picture is genuinely mixed. The data supports both the anxiety and the cautious optimism expressed by leaders at Web Summit. Automation anxiety is real, measurable, and concentrated among those with the least leverage in the labour market. But the economy is still growing, companies are still hiring, and the full consequences of the AI wave — positive and negative — have not yet fully arrived.
Key Takeaways
- Over 85,000 tech jobs were cut in the US through April 2026, a 33% year-over-year increase, with Meta and Intuit among the latest major employers to announce significant AI-driven reductions.
- Automation anxiety is acutely concentrated among new graduates, with the recent college graduate unemployment rate hitting 5.6%, well above its historical average, and Anthropic CEO Dario Amodei warning that AI could eliminate up to half of entry-level white-collar jobs within five years.
- A Stanford study found 64% of Americans expect AI to reduce overall employment over the next two decades — a sentiment that appeared dramatically in public when Eric Schmidt was booed at a university commencement address.
- Despite the layoffs, the U.S. economy added 304,000 jobs through early 2026 and the unemployment rate remains at a historically low 4.3%, reflecting the uneven and sector-specific nature of the disruption so far.
- The Trump administration’s last-minute withdrawal of an AI executive order signals a regulatory posture that favours speed of deployment, which could accelerate corporate automation decisions with minimal federal oversight in the near term.
