Meta and Microsoft Ride the Wave of Tech Layoffs

Meta and Microsoft have recently made headlines by announcing significant reductions to their global workforce, even as they ramp up investments in artificial intelligence (AI).

The connection appears clear. Janelle Gale, Meta’s chief people officer, indicated that the layoffs—affecting around 10% of the workforce or nearly 8,000 employees—are intended to “offset the other investments we’re making.” Company leader Mark Zuckerberg has previously discussed a “major AI acceleration,” with plans to invest over US$115 billion this year.

Microsoft is also making substantial bets on AI, having recently introduced early retirement packages impacting about 7% of its US workforce.

These tech giants join the ranks of Atlassian, Block, WiseTech Global, and Oracle, all making similar announcements this year, invoking AI without fully attributing the layoffs to it.

What’s occurring here? Our understanding of these layoffs is contingent upon our perceptions of AI and its implications. Broadly, there are three perspectives: AI as superintelligence, AI as mostly hype, and AI as a useful tool.

The end of white-collar work?

From the first perspective, AI is perceived as an emerging superintelligence. This new form of intellect learns, reasons, and is expected to soon outperform humans in most cognitive tasks (Spoiler: it’s not!).

The job losses symbolize more than mere corporate restructuring; they represent an early sign of something significantly disruptive.

In February 2026, AI entrepreneur Matt Shumer vividly compared this moment to the eerie weeks before the COVID-19 pandemic altered global awareness. He argued that many haven’t yet realized we’re on the brink of an “intelligence explosion.”

His essay drew substantial critique, with commentators pointing out its lack of hard data and suggesting it sometimes resembled a marketing pitch for Shumer’s AI products.

Nevertheless, it resonated with a genuine concern. Something significant is indeed happening within software engineering, where tasks are well-defined and success metrics are clear.

However, the leap from this situation to “all white-collar work will be automated” is a considerable one. The notion that AI could evolve into a universal mind capable of self-improvement is exaggerated.

Furthermore, most professional roles involve far more complexity than coding: ambiguous directives, competing stakeholder interests, ambiguous outputs, and fluctuating success metrics. While coding may serve as a barometer, coal mines and boardrooms operate under vastly different conditions.

Are tech companies retracting from hiring sprees?

The second perspective views the AI discussion as largely hype. In this view, AI is used as a convenient cover. Companies that aggressively expanded during the pandemic and are now facing financial pressures are using AI as a justifiable explanation for cuts.

OpenAI’s CEO Sam Altman termed this phenomenon “AI washing,” referring to companies attributing layoffs to AI when they would have happened regardless.

For instance, Meta announced in March the closure of its Metaverse platform, Horizon World, set for June. Reality Labs, the department developing this technology, employed 15,000 individuals as of January 2026.

Without detailed insight into the current layoffs, it’s possible that Meta is simply reframing prior shortcomings as AI-driven efficiency improvements.

A more cynical interpretation suggests that conducting layoffs under the pretense of AI is a strategy to boost stock prices. For example, when Block cited AI and eliminated nearly 4,000 jobs, its stock experienced a jump the following day.

By announcing AI-driven layoffs, companies may find that investors reward them for projecting a forward-thinking image. This tactic is historically familiar: technology has often served as a convenient guise for financial restructuring.

Are layoffs a means to enforce AI usage among staff?

The third perspective is more nuanced, viewing AI as a potent tool that companies must adapt to effectively leverage.

This has significant ramifications for job requirements and quantity. This perspective appears to hold considerable validity.

From this viewpoint, tech leaders believe that AI will revolutionize software development, though the specifics remain unclear.

Thus, when confronted with uncertainty, tech firms often resort to creating pressure. They reduce headcount and expect those who remain to maintain prior productivity levels while motivating teams to discover how to utilize AI to achieve those goals.

This strategy doesn’t rely on the belief that AI will replace everything, but rather anticipates that the pressure will compel humans to explore ways to enhance productivity through AI.

This aligns with industry experience. For instance, Google CEO Sundar Pichai reports a 10% increase in engineering speed due to AI adoption across the organization. This could correlate with the 7–10% workforce reductions observed across many of the mentioned companies.

Implications for knowledge workers

These three perspectives are frequently presented as mutually exclusive. In reality, all three coexist simultaneously. A candid answer to “what is truly happening here” likely encompasses “a bit of everything.”

What is undeniable is that software development often serves as an early signal of broader transformations in knowledge work. The productivity gains from AI are tangible for those who adapt, though adoption varies significantly and is slower in less technical sectors.

In this landscape, the ability to understand AI and make sound decisions regarding its application is becoming an essential professional skill.

The employees at greatest risk are not necessarily those whose roles can be replicated by AI. They are those who wait for external pressures rather than taking proactive measures now.

In the coming years, we will gain clarity on whether AI is primarily hype or a valuable tool.

If Meta, Microsoft, and their counterparts begin rehiring individuals with different skill sets, redesign workflows, and genuinely enhance their capabilities, the argument for useful AI will appear strong. Conversely, if they merely pocket the payroll savings, the skeptics will have been vindicated.

To gauge the direction of tech companies, focus not on what they cut but on what they choose to hire.

Kai Riemer, Professor of Information Technology and Organisation, University of Sydney and Sandra Peter, Director of Sydney Executive Plus, Business School, University of Sydney

This article is republished from The Conversation under a Creative Commons license. Read the original article.