Layoffs or 'AI-washing': How Corporations Hide Crisis Behind Neural Networks

When another CEO takes the stage and solemnly announces that the company is laying off three thousand employees for a "strategic focus on AI," the hall typically echoes with applause from shareholders. It looks like a decisive step toward the future, but if you look closely, behind the glittering facade of technological progress often hides the good old desire to adjust financial reports. We have entered an era of "AI-washing," where artificial intelligence has become not only a tool for creation, but also the perfect scapegoat for corporate failures.

Let us recall the context. In 2020 and 2021, the technology sector grew by leaps and bounds. Companies hired tens of thousands of people, believing that the endless digital boom would last forever. But reality turned out to be more mundane: inflation rose, interest rates climbed, and demand stabilized. Now, when it came time to pay the bills and trim bloated staff, admitting management mistakes would mean crashing stock prices. It is far easier to say that it is all "progress"'s fault. AI serves here as a convenient lightning rod: laying off people due to neural networks sounds innovative, but due to poor forecasting — unprofessional.

The term "AI-washing" essentially resembles "greenwashing," when brands pretend to be environmentally friendly for marketing purposes. In our case, companies pretend to be so automated that they supposedly no longer need live employees. But if we look under the hood, we see that most implemented systems are not yet capable of replacing even an intern. Yes, GPT-4 can write a draft letter or basic code, but it cannot manage a project, understand subtle nuances of business ethics, or take responsibility for results. Mass layoffs are happening now, while full-scale AI implementation capable of justifying such magnitude will happen, at best, in a few years.

The problem is that this trend creates a dangerous illusion. Investors begin demanding "efficiency through AI" from everyone indiscriminately, forcing even healthy companies to get rid of valuable staff. This creates an atmosphere of fear and uncertainty in 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 "unnecessary" people. In the long run, this can lead to a loss of institutional memory and degradation of teams that have spent years building processes.

It is interesting to observe how rhetoric is changing. Previously, automation was a gradual process discussed with caution. Today it is a slogan that should magically boost capitalization. But the reality is that replacing a human with a neural network is an extremely complex engineering and organizational challenge, not simply pushing a button "Lay everyone off." Those who today cry loudest about AI transformation may tomorrow face the fact that their systems hallucinate, and there is already no one left to work on fixing the mistakes.

The bottom line: AI has become the perfect screen for corporate cleanup. Before believing in "technological displacement," it is worth checking whether the company is simply trying to hide budget holes behind a trendy three-letter word.