What “AI Washing” Actually Means for Tech Hiring

Sam Altman, of all people, called it out first. “AI washing,” he said in February, is when a company blames AI for a layoff it was going to do anyway. That is a useful term from the one executive in the world with the most to gain by telling you the opposite.

We see the pattern constantly on our side. A company runs a round of cuts. The press release talks about AI transformation. Six months later we are helping them backfill the same roles under different titles, or sourcing contractors for the work they claimed AI would absorb. The layoff was real. The AI framing was the cover story. And that cover story is now warping how both hiring managers and candidates read the market.

The Cuts Are Real. The AI Part Is Mostly Branding.

Most of the layoff announcements we have read this year describe a workforce reduction and then vaguely attribute it to AI. They do not describe a redesigned workflow. They do not describe which tasks the tool now handles. They do not describe what happened to the work itself. The work did not actually go anywhere. It got quietly redistributed to the people still on payroll, or handed off to contractors, or dropped on the floor.

That is not an AI transformation. That is a normal layoff in a nicer suit. Demand softened, the company overhired in 2022, a product line underperformed, margins got squeezed. Every one of these has been a reason to cut headcount for decades. None of them sound strategic on an earnings call. “We are restructuring around AI” does. That is most of what is happening right now.

A Bad Quarter Looks Like Mismanagement. An “AI Transformation” Looks Like Strategy.

Three incentives make the AI framing the most attractive cover a CFO has had in twenty years.

Markets reward it. A cut framed as forward-looking AI strategy gets a different stock reaction than the same cut framed as “we read the market wrong.” Same decision, different share price.

Boards reward it. It signals the company is on the program without requiring leadership to actually deploy anything real or measure whether it worked.

And it ends the conversation. Nobody on an earnings call presses hard on “we are restructuring for AI.” Everyone presses hard on “we had a bad quarter.” The framing is not PR. It is a working shield.

Candidates Are Panicking About a Wave That Hasn’t Fully Hit Yet

This is where the narrative stops being harmless corporate theater and starts damaging real careers. We talk to engineers every week who have convinced themselves that AI has already eaten a fifth of their field. It has not. The roles getting cut this quarter are largely the same ones that would have been cut in any downturn. Some of them are AI-exposed. Most of them are just cost lines on a spreadsheet.

The people acting on the panic are making bad moves. Mid-level engineers are taking deep pay cuts to pivot into anything with “AI” in the title, abandoning fields where they are five years deep and actually in demand. Strong candidates are accepting the first offer that lands because they assume the next one might not come. Some of the best engineers we know right now are pricing themselves as if the market is worse than it is, and leaving real money on the table.

The hiring side has its own version of this. We have watched companies rewrite job descriptions around AI capabilities they do not actually need, because a competitor publicly restructured around AI last quarter and everyone assumes that competitor must know something. In most cases the competitor just ran a normal layoff with better packaging. Copying the homework is how you end up searching for five months for a unicorn who does not need to exist for your role.

Real AI Restructuring Rewrites the Work. AI Washing Just Removes the People.

There is a clean way to tell the difference, and we use it with every company we work with.

Real AI restructuring changes the shape of work. It shows up as job descriptions being rewritten, training being built, new roles appearing on the org chart that did not exist two years ago. It pairs cuts in one part of the business with serious investment in another. When companies do it honestly, the remaining team ends up doing different work, not just more of the same work with fewer people.

AI washing just removes roles and points at AI as the reason. No redesigned workflow, no new role structure, no visible investment in the people who stay. The work gets absorbed by whoever is left, which is how you get burnout six months later and quiet contractor hiring twelve months after that.

For anyone reading this market as a candidate, look past the announcement and look at what the company is actually building. Are they investing in the team that stayed? Are the new roles genuinely different from the old ones? For anyone hiring through this market, the lesson is simpler. Do not copy a competitor’s layoff as if it were a strategy. It was probably just a cover story, and falling for it will cost you more than ignoring it would have.

TechX works across both sides of this. We train engineers on real production work, not AI theater, and we help hiring teams figure out what their actual AI needs look like versus what the market narrative says they should look like. If you are trying to separate signal from noise in this market, let’s talk.