In February 2026, the question of whether artificial intelligence is experiencing a financial bubble dominates debates on Wall Street, in economic forums, and in tech circles. Colossal investments—more than $2.5 trillion projected in global AI spending this year, according to Gartner—stand in stark contrast to doubts about real profitability. Tech giants like Microsoft, Amazon, Google, and Meta plan to spend between $635 billion and $665 billion on infrastructure during 2026. Companies like OpenAI are burning through cash at alarming rates (projections predict losses of tens of billions before stable profits), while Nvidia and the rest of the supply chain are experiencing stock market euphoria.
The parallels with the dot-com bubble of 2000 are unavoidable. Experts like Ray Dalio warn that the stock market is at levels similar to those of the dot-com bubble, and that a burst could occur in 2026. Analysts at S&P Global and others estimate that the “AI bubble” could be up to 17 times larger than the dot-com bubble in certain indicators. There are clear signs of overheating: extreme valuations in the technology sector, record concentration in a few mega-cap companies (the “Magnificent Seven” account for a large portion of the S&P 500's gains in 2025), and spending on data centers that far exceeds current revenue attributable to AI services (barely 2% in some estimates). Furthermore, reports indicate that 95% of organizations that invested in GenAI did not see a significant return by 2025.
However, not everyone sees an imminent bubble. Asset managers like BlackRock, JP Morgan AM, and DPAM argue that the comparisons are premature. Unlike the dot-com era, where many companies lacked real revenue, today there is mass adoption: accelerated productivity in the US, unmet demand for computing power (Google and others double capacity every few months), and concrete advances in reasoning models, autonomous agents, and scientific applications. Major CEOs plan to increase AI budgets by 2026 (68% according to surveys), and the technology is transforming real sectors, not just speculation.
The reality is likely a hybrid: there is a speculative bubble in valuations and short-term expectations, but also a far-reaching technological revolution. 2026 could be the year of “AI reckoning,” with selective stock market corrections—especially in pure AI companies without solid cash flow—while big tech companies with strong balance sheets continue to invest. Systemic risk exists: a collapse could affect tech jobs, the supply chain, and economic growth.
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