The recent and debated "Citrini Report" (Citrini Research, February 2026) has raised concerns in the markets by presenting an extreme scenario for 2028: while artificial intelligence could boost productivity, it might also lead to a significant decline in wages, employment, consumption, and GDP. Although it is a hypothetical exercise and not an official prediction, its publication caused a 1% drop in the S&P 500 the following day. The report, titled "The 2028 Global Intelligence Crisis" (February 22, 2026) and authored by Citrini Research and Alap Shah, explores the possibility that the success of AI could lead to its own crisis. According to its premise, by mid-2028, automation could reduce the cost of skilled labor to the point where unemployment in these sectors would reach 10.2%, and the S&P 500 would suffer a cumulative decline of 38%. While the authors insist it is just a scenario, the market reaction was immediate, with declines of 4%-6% in companies particularly exposed. The report's reasoning is coherent: AI lowers costs and automates complex tasks, allowing companies to dispense with skilled professionals (consultants, analysts, technicians, lawyers, engineers, executives, etc.), which would increase corporate margins but negatively affect these jobs. The central question is whether this scenario of prolonged deflationary recession is truly plausible. These jobs, in addition to being numerous, represent a significant part of consumption and economic development. Initially, GDP and productivity would grow, but the reduction in income and jobs would generate what the report calls "phantom GDP": accounting growth without backing in real consumption, which accounts for nearly 70% of GDP. Thus, the report concludes that this could lead to a sustained deflationary recession. However, current data nuances this risk. In the U.S., unemployment stands at 4.4% (February 2026), far from the 10% projected by the report. Achieving that level in two years would require a crisis of historical magnitude, similar to that of 2009. Additionally, a 38% drop in the markets, while severe, would not be unprecedented (the S&P 500 fell 57% in 2008). It is likely that a shock of such magnitude would provoke strong political responses, such as fiscal and monetary stimuli, which are not considered in the report. Empirical evidence also shows that AI gradually increases efficiency. A study by the NBER (2023) indicates that AI assistants boost productivity in call center agents by 14%, and another experiment shows that ChatGPT reduces technical writing time by 40%, improving quality. These examples suggest that AI adds microeconomic value and has not yet massively destroyed jobs. Among those supporting the Citrini scenario, it is argued that AI primarily affects high-skilled jobs, which could reduce domestic demand if high wages fall. The report describes how AI could replace human tasks, which, according to the multiplier theory, would lead to a chain reaction of reduced wages, consumption, and business activity. However, there are strong arguments against Citrini's thesis. The adoption of AI is neither instantaneous nor universal; many companies implement it gradually and face technical and regulatory barriers. Additionally, AI also generates innovation and new jobs. Stock analysts warn that the negative reaction to the report may be an overreaction to inflated expectations. Economic history shows that each technological revolution creates new demands before destroying old jobs, and that major corrections often come after long periods of expansion. The experience of the dot-com bubble is illustrative: although AI may lower service costs, savings can be redirected to new investments and sectors, mitigating the impact. In summary, the Citrini Report should be interpreted more as a warning than a prediction, alerting about the risk of profit concentration in capital, but likely exaggerating the short- and medium-term impact. The key lies in preparation: public policies must prioritize education and training in digital and STEM skills, strengthen social safety nets, and develop AI regulation that promotes competition, ethics, and safety. Professions and sectors that adapt will be the big winners.