The growing prominence of companies focused on artificial intelligence (AI) and the million-dollar valuations they reach in the US stock market have raised concerns about a possible bubble in the sector. Experts highlight the differences between bubble in AI megaprojects and the dotcom bubble of the late 1990s.
Meanwhile, technology giants such as Nvidia and OpenAI set the pace of innovation and concentrate investments. In this context, questions arise about the sustainability of the sector and the impact of a possible collapse on emerging firms.
Warnings about a bubble in AI megaprojects arise not only from the spectacular growth in stock valuations and massive investments in infrastructure, but also from the financial structure that supports several leading companies.
Experts like Vasant Dharan academic at New York University with experience in the dotcom crisis, emphasize that the current scenario is “very different” from that of two decades ago. For him, the core difference lies in the fact that “most of it has been promoted by the big guys: Nvidia, Microsoft, Meta, Amazon, Google…”
The specialist gave this statement to EFE and added that these companies finance the expansion of AI with “real profits” and avoid the purely speculative nature that led to the collapse of hundreds of small dotcom companies.
This context is reflected in the business results of Nvidiaa company that exceeded projections with year-on-year revenues of $57.01 billion and even higher sales forecasts for the immediate future. Jensen Huang, CEO of Nvidia, stated that “there has been a lot of talk about an AI bubble,” but that the company is seeing “something very different.”
The case of OpenAI symbolizes the current tensions in the AI market. Financial documents revealed by The Wall Street Journal show forecasts for operating losses that would be around $74 billion in 2028, while the company is betting on reversing the trend only in 2030.
For this year, the projection is to incur an expense of 22,000 million dollars against estimated income of 13,000 million, which results in a considerable net loss.
The structure of “circular financing”where companies like Microsoft invest heavily in OpenAI, which in turn spends large amounts on Microsoft’s cloud and Nvidia chips, raises questions about the soundness and financial independence of the sector.
Dhar himself points out: “They are not speculating like crazy,” since, unlike previous cycles, now it is the “big guys” who are betting on infrastructure and innovation with their own capital.
Despite this support, the possibility of a shake-up in the sector if a leading firm faces difficulties is not ruled out. Dhar suggests that even a “bankruptcy” of OpenAI would not affect the daily lives of users, who would quickly migrate to alternatives such as Claude or Gemini.
The greatest risk of a technology bubble, according to experts, lies in the ecosystem of startups that proliferate without a consolidated product.financed essentially by speculative capital. According to Dhar, it is in that niche where 20-year-olds raise millions in investment with just an idea.
Jamie Dimon, director of JP Morgan, asserts that a significant part of the money injected into artificial intelligence “would probably be lost.”
Alphabet CEO Sundar Pichai warned that all companies could be affected if the AI bubble bursts, highlighting the sector’s sensitivity to sudden changes in market expectations.
The current AI boom, unlike the dot-com bubble, is largely driven by multibillion-dollar companies with solid financial foundations and infrastructure investment strategies.
When the dotcom bubble“90% and 98% of those companies went bankrupt; they simply went under,” as Vasant Dhar recalls in an interview with EFE. Now, market leadership is exercised by a select group of companies that dominate the developments and the necessary investment.
The focus, according to specialists, should be directed towards the sustainability of startups and the effectiveness of the infrastructure promoted by the big players. In this way, it will be possible to evaluate whether the phenomenon responds to real growth in the digital economy, or if the risk of an abrupt adjustment in the valuation of the artificial intelligence sector appears on the horizon.
