Meta, the tech giant, announced on April 23 the layoff of 8,000 employees, representing 10% of its workforce, with forecasts that the number could rise to 15,000 according to some reports. Traditionally, such cuts have been associated with financial problems or revenue declines, but today the situation is different. In fact, Meta has increased its investment in artificial intelligence (AI) to $135 billion. However, AI does not always directly replace workers; in many cases, it becomes the central argument to justify restructuring. Under the promise of greater efficiency and cost reduction, more companies justify layoffs by appealing to automation. However, this is not always a real substitution of human labor by AI systems. Analysts warn about the phenomenon of "AI-washing," where AI is used as a pretext for traditional labor adjustment decisions. A report from Forrester and Orgvue reveals that 55% of companies that replaced staff with AI regretted it, being forced to rehire or accept a decline in service quality. About 29% even rehired for the same positions. The promise of frictionless automation clashes with reality: AI still requires supervision, fails in complex tasks, and does not replace the relational dimension of work. An illustrative case is Klarna, the Swedish fintech that laid off 700 employees, mainly in customer service, presenting the measure as a technological advancement. However, the company had to rehire after realizing that service quality had decreased and that AI could not manage the emotional complexity of human interactions. The immediate savings translated into reputational and operational costs in the medium term. The impact of AI is not limited to automatable sectors. In the content industry, the case of Sports Illustrated is paradigmatic: the publication of AI-generated articles under fictitious identities led to the firing of CEO Ross Levinsohn and a crisis of trust that forced a reevaluation of the editorial strategy. Here, AI affects both employment and the credibility of the informational product. In service platforms like Glovo, unions report that the delivery algorithm is used to unfairly sanction and fire workers, favoring shell companies and rented accounts. In Amazon, international labor movements accuse Jeff Bezos of promoting a "techno-authoritarian future" through automation. On the opposite end, IgniteTech laid off 80% of its workforce in 2023 to radically bet on automation. Management justified the measure by citing internal resistance to change, defending financial results, although the decision has been questioned from a labor and ethical standpoint. In this case, AI is not an excuse but the axis of a productive transformation that redefines which jobs are expendable. The central question is no longer just how many jobs disappear, but how they transform. AI concentrates tasks previously distributed among entire teams into highly qualified individual profiles capable of coordinating multiple automated systems. According to computer engineer Guillermo Merino Jiménez, an employee with AI tools can take on functions that previously required several people, from user experience design to data implementation and analysis. This concentration poses new challenges: fewer teams, greater individual workload, higher qualification demands, and possible intensification of work. At the same time, it redefines the skills needed in the labor market. Merino notes that "we are already very close to achieving something much better than a human," referring to advances in AI learning. Currently, humans are still needed to develop new models and applications, but the turning point will come when AI can self-improve. Some experts predict this could happen in 2026 or 2027, although Merino warns that there will be a transition period. The dominant discourse presents these changes as inevitable, but experience shows that the implementation of AI is not linear. Between corporate enthusiasm and technological limits, key debates arise: which jobs disappear, which transform, and under what conditions this transition occurs. Labor and tax legislation must adapt to this new scenario.