Companies Are Cutting Jobs Based on What AI Might Do, Not What It’s Actually Doing. Here’s What That Means for Your Career.

Nearly 300,000 jobs were cut in Q1 of 2026 alone, and more than half were labeled “AI-driven.” But a closer look at the data tells a very different story than the one most professionals are hearing.

A client of mine, a senior operations director with 18 years of experience, was let go in February. The company’s internal messaging called it a “strategic realignment driven by AI integration,” which sounded precise enough to seem like it meant something. When she asked her VP directly what AI system had replaced her function, the answer was revealing: there wasn’t one, and there wasn’t even a timeline for one. Her entire role had been eliminated based on the assumption that at some point in the future, the work she was doing might be handled differently.

That assumption is now driving layoff decisions at a scale that most professionals don’t fully appreciate.

Harvard Business Review published a piece earlier this year that captured the core of what’s happening with unusual clarity: companies are laying people off based on AI’s potential, not its actual performance. The layoffs and hiring slowdowns are real, the authors explained, even though most organizations are still waiting for generative AI to deliver on its promises. It’s a strategy built on anticipation rather than evidence, and the cost is being absorbed almost entirely by the people who lose their positions while the organizations hedge their bets.

The numbers make the pattern more and more obvious. In the first quarter of 2026 alone, 92 companies announced layoffs totaling nearly 295,000 jobs according to layoff tracking data, and of those, more than 169,000 were categorized as AI-driven.

But a separate MIT study released just this week found that AI is gradually redefining roles rather than erasing them in one sweep, and that some companies are using the term “AI” to justify broader cost-cutting that has very little to do with technology at all. Axios reported on the study and noted that critics are now calling this “AI-washing”: repackaging financial restructuring as forward-looking innovation so it plays better in earnings calls and internal communications.

This is in line with statistics I’ve been watching for months inside hiring. As I wrote in my article “AI Washing in Hiring”, the hiring system didn’t suddenly become more intelligent; it’s simply better at sounding intelligent. That same principle now applies to how organizations explain their layoffs, and most professionals on the receiving end have no way to tell the difference between a genuine technology-driven shift and a financially motivated cut wrapped in AI language.

What This Actually Looks Like When You Pull the Numbers Apart

Harvard Business School research published in HBR in March analyzed nearly all U.S. job postings from 2019 through early 2025, and what they found should reframe the conversation entirely. Openings for routine, automation-prone roles did fall by about 13% after ChatGPT launched, which is significant in and of itself. But demand for more analytical, technical, and creative positions grew by 20% over the same period.

The net picture is one of reshuffling, not mass erasure: the labor market is reorganizing around judgment, context, and the kind of human interpretation that current AI systems still can’t replicate.

What that means, practically, is that many of the jobs being eliminated right now aren’t being replaced by technology. They’re being cut during a window of economic uncertainty and relabeled in ways that satisfy investors and boards who want to see that the company is “positioning for the future.”

The Wall Street Journal reported earlier this year that employment growth forecasts for 2026 have dropped to just 15,000 to 49,000 jobs per month, well below the historical norm of 150,000 to 200,000 during healthy expansions. In that kind of environment, any revenue pressure leads companies to cut people rather than scale back hiring plans, because there aren’t many hiring plans left to scale back. And AI becomes a convenient narrative layer over what are fundamentally margin-protection decisions.

A Newsweek report from late 2025 quoted one economist at the University of Texas who said the fear of AI-related displacement is, in his words, grossly overblown. What isn’t overblown is the economic climate itself, and the way it compounds every other pressure professionals are already navigating.

What This Means If You’re Mid-Career and Watching It Happen Around You

If you are a professional in your thirties, forties, or fifties watching these headlines and wondering whether your experience still carries the weight it used to, here is what I want you to hear: the people being let go in most of these rounds are not being outperformed by software. They are caught inside a financial calculation that borrows AI’s credibility to explain itself, and that is a very different problem than obsolescence.

It requires a very different response, too.

The response isn’t to panic-learn every AI tool on the market or to stuff your resume with buzzwords that signal you’re “AI-fluent.” It’s to understand where real value is being created inside organizations right now, and to position yourself squarely inside the work that AI cannot replicate: high-stakes decision-making, cross-functional leadership, relationship-driven problem solving, and the kind of judgment that only develops after years of pattern recognition in complex environments.

As I discussed in my article “Why Being Qualified Is No Longer Enough”, qualification now functions as a floor rather than a differentiator. What separates professionals who continue to advance from those whose careers slow down is how well they can translate their expertise into language that speaks directly to what organizations fear most: making a bad hire, losing institutional knowledge, or investing in a candidate who can’t navigate ambiguity. Those fears are heightened right now, and the professionals who can address them directly in interviews, in networking conversations, in how they show up on LinkedIn, are the ones cutting through the noise.

If you’ve been laid off in one of these rounds, or if your industry is going through it and you’re wondering when the other shoe drops, I want you to resist the impulse to internalize the story the company told on the way out. Start by asking a more useful question: what work do I do that requires the kind of judgment a model can’t simulate, and how do I make that unmistakably clear to the next organization that meets me?

That’s the foundation of everything you should focus on from this point forward.

The Harvard researchers noted that 94% of workers surveyed said they prefer AI as a collaborative tool rather than a replacement, and that companies pursuing a purely displacement-focused strategy are likely to face significant pushback from employees and customers alike. That signals something important about where the market is heading: organizations that cut too aggressively now may find themselves scrambling to rehire, exactly as HBR warned.

For professionals navigating this moment, the opportunity is to be the person the company realizes it needs again in 18 months; except this time, you set the terms.

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