The AI-layoffs story everyone’s telling isn’t the one happening in the room.

I recently sat down with Business Insider to talk about what’s actually going on behind the “AI is taking our jobs” headlines. You can read the interview here, this is the longer version of what I told them.

I’m the cofounder and managing partner of Customertimes, a 1,000-person firm that helps Fortune 500 companies implement AI. Before this, I spent almost a decade in pharma leading technology transformation projects. That combination means I’m in the room for two different conversations most people never see side by side: the public one about layoffs, and the private one about what AI actually costs and delivers.

Almost none of the CFOs, CIOs, and CEOs I talk to every week tell me, privately, that they’re replacing people with AI. The gap between that private conversation and the public narrative is exactly why the hysteria around AI layoffs reads so strangely from the inside.

What’s actually happening: AI as cover, not cause.

Long before generative AI, companies were already automating repetitive work through robotic process automation. The underlying goal hasn’t changed: find the inefficient process, automate the routine part, free people from work nobody wanted to keep doing manually.

What I actually see now is companies using AI as the explanation for restructuring that was coming regardless. A process stops making sense, leadership had already planned to reorganize it. There’s nothing unusual about reorganizing for efficiency, businesses have always done that. The problem is honesty: a lot of these companies aren’t straight with their employees or shareholders about what’s actually driving the decision.

The money doesn’t go where people assume.

The public story is simple: cut headcount, pocket the savings, hand leadership a bigger bonus. What I see behind the scenes is messier.

CFOs and CIOs tell me constantly that they underestimated token costs, and plenty of organizations have burned through a year’s AI budget in a few months, some describe it as “token maxing,” spending accelerating far faster than the productivity gains that were supposed to justify it. On top of that, companies are investing heavily in keeping proprietary processes and trade secrets out of public models, building separate internal AI infrastructure specifically to protect that knowledge. None of that is cheap, and none of it shows up in the “AI saves money” headline.

So when a company announces layoffs in the same quarter it reports record profit, the assumption that the savings landed in executive pockets is often just wrong. Infrastructure, token bills, and licensing eat a lot of it before it ever reaches a bonus pool.

People want to see where the money went and they’d back a fair split.

In the survey behind this interview, 86% of adults said companies saving money through AI should pass some of that savings on as lower prices for consumers. That’s a reasonable bar, and it’s one most companies aren’t answering at all.

My actual recommendation to the executives I work with: publish something simple showing where the AI savings went. Into employee bonuses. Into lower prices. Into reinvestment. Pick one, be specific, show a number. When a company stays silent instead, it creates a vacuum and a vacuum always gets filled, usually by the least charitable explanation available. Stay quiet long enough and the conspiracy theory about you gets written whether you show up to correct it or not.

What AI can’t take off your plate and what it can hand back to people.

AI is genuinely excellent at repeatable, structured work. You can automate a CEO’s earnings presentation with an AI avatar today. What you can’t automate is accountability, the decision to restructure, the responsibility for the people affected, the judgment call on where the savings actually go. That’s still a human in a chair.

And I’d push back on the assumption that AI mostly makes people less necessary. At Customertimes, we invest heavily in AI training, and I’ve watched testers and business consultants pick up new AI-driven skills in a matter of weeks. The pattern I actually see isn’t people becoming less valuable, it’s people becoming capable of delivering a lot more than they could before.

If your company has gone through AI-linked layoffs, were you ever told where the savings actually went or did you have to guess?