Why talk about a bubble and what the risks are
The fundamental argument of the proponents of the bubble theory is the apparent discrepancy between the capitalization of AI-related companies and their actual financial results.
They note that global markets have valued 17 AI-related companies at an additional USD 4.9 trillion in capitalization growth for the entire S&P 500 index – that’s almost two-thirds of the total USD 7.5 trillion growth. According to analysts, such concentration and strong revaluation of assets are classic signs of a speculative bubble.
Legendary financier Michael Burry, famous for predicting the 2008 crisis, also warns about the risks of overvaluation of AI assets and a possible strong fall of markets in case of a bubble collapse.
The market is also showing signs of capital overheating, with companies such as Amazon, Microsoft and Meta having to announce massive spending to support AI projects, which is already being reflected in their stocks – some have entered a bear market, down more than 20% from their peaks.
The financial mechanisms for inflating the bubble are being exacerbated by active debt raising. Analysts point out that tech giants could rack up trillions of dollars in corporate bond issuance in 2026 to fund ambitious AI plans, putting further pressure on the financial strength of markets, Axios writes.
Opposing view: long-term investments
However, not all experts support the thesis of an inevitable bubble and sharp collapse. Some of the industry’s biggest executives emphasize that the current growth in AI investment is a strategic bet on long-term infrastructure, similar to the era of building railroads or the internet.
For example, Alphabet CEO Sundar Pichai noted at the AI Summit in New Delhi that the current technology shift “could be 10 times faster and 10 times larger than any previous revolution,” and called for a long-term view of investment rather than panic.
Proponents of this position point out that the high capitalization of AI companies reflects not only speculation but also fundamental demand for AI products and cloud services, as well as the prospects for radical productivity improvements in the coming years.
In addition, analysts at Yardeni Research, for example, note that valuation metrics for technology stocks (P/E) have declined from record levels late last year, indicating the beginning of a “real rebalancing of markets” rather than an accelerated bubble phase.
Implications for markets and investors
If bubble fears are confirmed, the consequences could be significant:
– A correction in technology sector equities: a sharp fall in valuations of AI-rich companies in the US and EU markets;
– systemic risks: deterioration of market sentiment could spread to related sectors (finance, communications, semiconductors);
– change in investors’ strategy: shift to more conservative assets, increase in the share of cache and protective instruments.
On the other hand, if technologies start to show sustainable profitability and real revenues from AI solutions, the market structure may move to an era of more balanced growth.
From all this, we can conclude that the debate around the AI bubble goes beyond speculation: it reflects the fundamental contradictions between the rapid capital build-up and the industry’s modest current financial performance. Regardless of the scenario, it is important for investors and corporate leaders to consider both sets of signals – both the risks of overheating and the prospects for technological proliferation.
