Layoffs or "AI-washing": how corporations hide their problems behind neural networks

When yet another CEO takes the stage and announces, with a straight face, that the company is laying off three thousand people to sharpen its "strategic focus on AI," shareholders in the audience usually applaud. It looks like a bold step into the future. Look closer, though, and the shiny facade of technological progress often hides a good old-fashioned urge to tidy up the financial statements. We have entered the era of "AI-washing," where artificial intelligence is not only a tool for building things but also the perfect scapegoat for corporate failures.

Let's recall the context. In 2020 and 2021, the tech sector grew like crazy. Companies hired people by the tens of thousands, betting that the digital boom would last forever. Reality turned out to be more mundane: inflation rose, interest rates went up, and demand leveled off. Now that the bill has come due and bloated teams need trimming, admitting management mistakes would tank the stock. It's much easier to say that progress is "to blame." AI works as a convenient lightning rod: laying people off because of neural networks sounds innovative, while laying them off because of bad forecasting sounds unprofessional.

The term "AI-washing" is essentially a cousin of "greenwashing," where brands pretend to be eco-friendly for marketing purposes. Here, companies pretend to be so automated that they supposedly no longer need human employees. But look under the hood and you'll see that most of the systems being rolled out can't yet replace even an intern. Yes, GPT-4 can write a draft email or basic code, but it can't manage a project, grasp the subtle nuances of business ethics, or take responsibility for outcomes. The mass layoffs are happening now, while full-scale AI adoption that could justify cuts of this size is, at best, several years away.

The problem is that this trend creates a dangerous illusion. Investors start demanding "efficiency through AI" from everyone, pushing even healthy companies to shed valuable talent. That breeds fear and uncertainty across the industry. Employees see algorithms as a threat not because they have become too smart, but because management uses them as a legal way to get rid of "extra" people. In the long run, this could lead to a loss of institutional memory and the erosion of teams that spent years building their processes.

It's interesting to watch the rhetoric shift. Automation used to be a gradual process that people talked about cautiously. Today it's a slogan that is supposed to magically boost market cap. But the reality is that replacing a person with a neural network is an extremely complex engineering and organizational challenge, not just a matter of pressing a "Fire everyone" button. The companies shouting loudest about AI transformation today may find tomorrow that their systems hallucinate and there's no one left to fix the errors.

The bottom line: AI has become the perfect cover for corporate purges. Before buying into "technological replacement," it's worth checking whether a company is simply trying to hide holes in its budget behind a trendy two-letter word.