Meta and Microsoft Navigate the Surge of Tech Layoffs

Meta and Microsoft have recently captured attention by announcing significant cuts to their global workforce, even while increasing investments in artificial intelligence (AI).

The link is apparent. Janelle Gale, Meta’s chief people officer, mentioned that the layoffs—impacting about 10% of the workforce or nearly 8,000 employees—aim to “balance the other investments we’re undertaking.” Company leader Mark Zuckerberg has previously spoken about a “major AI acceleration,” intending to invest over US$115 billion this year.

Microsoft is also making considerable bets on AI, recently introducing early retirement packages affecting around 7% of its US workforce.

These tech giants join companies like Atlassian, Block, WiseTech Global, and Oracle, all of which have made similar announcements this year, invoking AI without fully linking the layoffs to it.

What’s really happening here? Our understanding of these layoffs depends on our views of AI and its implications. Generally, three perspectives emerge: 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 viewed as an upcoming superintelligence. This new form of intellect learns, reasons, and is anticipated to soon surpass humans in most cognitive tasks (Spoiler: it’s not!).

The job losses signify more than simple corporate restructuring; they hint at an early sign of something significantly disruptive.

In February 2026, AI entrepreneur Matt Shumer likened this moment to the unsettling weeks before the COVID-19 pandemic reshaped global awareness. He suggested that many are unaware we’re on the verge of an “intelligence explosion.”

His essay faced considerable critique, with commentators highlighting its lack of hard data, claiming it sometimes resembled a marketing pitch for Shumer’s AI products.

Nonetheless, it struck a chord with genuine concern. It’s evident that meaningful changes are occurring within software engineering, where tasks are well-defined and success metrics are clear.

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

Moreover, most professional roles encompass far more complexity than coding: ambiguous directives, competing stakeholder interests, unclear outputs, and dynamic success metrics. While coding may serve as a barometer, coal mines and boardrooms operate under fundamentally different conditions.

Are tech companies retracting from hiring sprees?

The second perspective interprets the AI discussion as primarily hype. From this viewpoint, 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 plausible justification for cuts.

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

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

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

A more cynical interpretation posits that conducting layoffs under the guise of AI is a tactic to boost stock prices. For instance, when Block cited AI and eliminated nearly 4,000 jobs, its stock saw a rise the following day.

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

Are layoffs a means to enforce AI usage among staff?

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

This has significant consequences for job requirements and numbers. This viewpoint appears to hold considerable merit.

From this standpoint, tech leaders believe that AI will transform software development, although the specifics remain elusive.

Thus, faced with uncertainty, tech firms frequently resort to imposing pressure. They reduce headcount and expect remaining employees to maintain productivity levels while encouraging teams to identify how to use AI to meet those objectives.

This strategy doesn’t depend on the belief that AI will replace everything but rather anticipates that the pressure will motivate humans to find ways to enhance productivity through AI.

This aligns with industry observations. For example, 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 noted among many of the mentioned companies.

Implications for knowledge workers

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

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

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

The employees at greatest risk aren’t necessarily those whose roles can be duplicated 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 peers begin rehiring individuals with different skill sets, redesign workflows, and genuinely enhance their capabilities, the argument for useful AI will be compelling. Conversely, if they merely pocket the payroll savings, the skeptics will have been validated.

To assess 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.