There are many companies that are prominently mentioning AI as a reason behind their layoffs, but AI might not actually be why they’re letting go of employees.
That’s the view of Hayden Brown, CEO of Upwork — one of the world’s largest freelance talent platforms — who argues that the narrative around AI and job losses is more complicated than the headlines suggest. While fear is real and widespread, Brown says the data tells a different story, and that much of what’s being called an AI reckoning is actually something far more familiar: companies cutting costs in a tough economy.
“The fearmongering is a real challenge,” Brown said, “because it does create a lot of uncertainty, and I think employees are really wondering what their place is — are they going to have a future, and so on. But the data is actually very different.”
Brown is direct about what he sees happening in corporate boardrooms. “Yes, we do see some companies doing layoffs, and I call it ‘AI washing’ those layoffs — saying, ‘Oh, it’s AI, we’re getting all these AI benefits.’ Quite often, I think it’s just plain tightening of belts and responding to a volatile economy, at a time where companies need to be more lean.”
At the same time, Brown doesn’t dismiss AI’s capabilities. Upwork has conducted its own research into what AI agents can and cannot do — and the findings point strongly toward a human-AI partnership model, rather than outright replacement. “We’ve measured what AI agents can do alone, what they can do with humans, and what humans can do alone. And even for the smallest, simplest tasks — think of things that can be done for a couple hundred dollars — we see that agents complete those tasks seventy percent better if they have human oversight.”
For Brown, this is more than a data point. “That really is, I think, just one indication of the fact that this technology is very powerful, but it still needs human intervention to be usable and useful.”
He returns, finally, to the broader anxiety gripping workers. “The fearmongering around job losses is a factor, but it doesn’t actually… it’s not actually supported in a lot of the data that shows jobs are growing in a lot of areas. The work is changing, and for people who can adapt, there’s going to be a lot of opportunity for them.”
Brown’s framing — “AI washing” — gives a name to something that has been building for a while. Companies have discovered that invoking AI as the reason for job cuts tends to land better with investors than admitting to over-hiring or margin pressure. The optics are cleaner: cutting costs sounds reactive; going AI-first sounds visionary.
The pattern is visible across the industry. Block laid off 40% of its staff in early 2026, with Jack Dorsey explicitly naming AI as the driving force — one of the most direct such statements from a major tech CEO. Upwork itself announced layoffs of 25% of its workforce, with Brown citing both speed and profitability as the rationale. The tension in that framing — a marketplace for human work cutting staff while arguing that humans remain essential — hasn’t gone unnoticed.
Marc Andreessen made a similar argument to Brown’s, attributing the bulk of tech layoffs to rising interest rates and pandemic-era over-hiring, not automation. A January 2026 Oxford Economics briefing concluded that many so-called AI layoffs were in fact the result of hiring excesses from 2020–2022 — dressed up in AI language because it plays better with investors.
That said, the displacement in some sectors is harder to explain away. Customer support hiring has collapsed — the share of new hires going into those roles fell from 8.3% to under 3% in under two years. Finance job openings are at their lowest since the 2008 financial crisis, even as the underlying businesses remain profitable. These aren’t corrections — they’re structural shifts.
Brown’s core point is still well-taken: fear and reality are not always the same thing, and the data on job growth is more nuanced than the discourse suggests. But the line between “AI washing” and genuine transformation is blurry, and it’s getting blurrier. For workers trying to read the room, the distinction may matter less than the outcome. The work is changing — and the opportunity Brown promises will depend heavily on how fast, and for whom, that change arrives.