Google cuts 30,000 jobs as AI fails to create new roles

Google cuts 30,000 jobs as AI fails to create new roles

A figure has been circulating in economic circles for days: 30,000 layoffs at Google. The company has not officially confirmed the scale of the measure, but the data is spreading rapidly and has sparked an uncomfortable question: if artificial intelligence was supposed to create millions of jobs, where are they? The answer emerging from analysis is not reassuring. So far, AI is being used to cut staff, not expand it. And the first victims are not engineers, but departments that seemed untouchable.

Sales department in the crosshairs

The most repeated consensus points out that the bulk of the layoffs do not come from engineering, hardware, or software. The blow falls on sales. Specifically, the advertising team, which for years believed itself safe due to soft skills and client interaction. The irony is bitter: the profiles that mocked engineers for their supposed rigidity are now seeing their positions threatened. Generative AI already drafts business proposals, segments audiences, and optimizes campaigns without needing an army of salespeople.

Some argue that Google is a pathetic company, trinc the patterns of other tech giants and dragging along an inflated structure. For every good worker, this school of thought says, there are a hundred behind them posting online or gaming. The hiring policy of recent years, based on diversity quotas rather than technical merit, would have left a residue of mediocrity that is now being purged. It is a harsh opinion, but it circulates unapologetically.

Is AI the real cause or just an excuse?

Not everyone buys the official narrative. AI technology is not yet mature enough, some argue. Current models have a superficial understanding of things; they do not grasp context like an average worker. Putting AI in charge of complex processes without human supervision is a recipe for disaster. Thus, the AI excuse serves to justify layoffs driven by other reasons: correcting overstaffing, investor pressure, and the end of the boom era.

The most optimistic calculation assumes that AI will free workers from repetitive tasks and create new jobs, as tractors did in agriculture or robots in industry. The pessimistic scenario starts from the premise that this time is different: AI does not only replace muscle, it also replaces judgment. And there, the margin for retraining narrows.

The invisible infrastructure

To understand why Google needs so many people, you have to look at what is unseen. Three million servers, more than two trillion annual searches, billions of users. That a search returns results in 0.3 seconds is not magic. Behind it lies a colossal technological mess: data centers, submarine cables, cooling systems, security, maintenance. Can that be managed with 1,000 people? No. With 10,000? Also no. The question is how many of the 30,000 who are surplus were doing something truly necessary.

The other side of the coin is user support. When your account is blocked, there is no way to contact a human. If Google has 160,000 employees, how is it that no one answers? The paradox feeds the thesis that there is much organizational filler and little operational substance.

The domino effect on the labor market

The impact is not limited to Google. In New York, tech salaries have fallen 30% in six months. Competition for any position is fierce. An IT director with years of experience sends sixty resumes and receives four responses; of two offers, one is €10,000 below the requested amount. Six years ago, that same profile found work in two weeks. The market has turned.

The phenomenon is not exclusive to the United States. In Spain, the feeling is similar: fewer offers, higher demands, falling salaries. AI accelerates the productivity of those who remain but expels those who are surplus. And there are many surplus workers.

What happens to the laid-off?

This is where the debate becomes more acrimonious. One current defends the universal basic income as a logical response: if AI produces goods 24 hours a day, someone must consume them. Without consumers, the system collapses. The objection is equally forceful: there is no money to pay a UBI to millions of unemployed without destroying the economy. Another, darker current suggests that the solution will pass through reducing the population. It is an extreme hypothesis, but it reflects the hopelessness of a debate that finds no exit.

Meanwhile, the layoffs continue their course. Google has not detailed exactly who is affected or when they will be executed. The company remains silent. Unions, if they exist, have made no move. And the 30,000 employees left on the street will soon discover if the tech labor market still has room for them.

The question is not whether AI will destroy jobs. The question is whether anyone is doing anything to manage the destruction that is already happening.