While most leaders of the artificial intelligence industry have concluded that the pace of development of this technology should be slowed, Wall Street is not very receptive to the idea and is worried about its financial consequences.
According to ITNA, analysts have repeatedly warned in recent years that the US economy has become overly dependent on AI and rests on heavy debts resulting from massive data center projects and astronomical capital expenditures; a trend that has intensified concern about the formation of a large bubble.
Now that most leading AI labs are seeking to slow development, investors have sounded the alarm about the formation of a “house of cards” in this industry.
According to the report, if this fragile structure collapses, its consequences could be very devastating.
Although this warning is not new and has been raised repeatedly before, it has never really been tested; at the same time, the longer this situation continues, the larger the accumulated risks become.
Meanwhile, Bloomberg quoted the manager of an investment firm as saying that “people may not fully understand how much the market and the economy are tied to this affair.”
Based on the latest estimates, costs related to AI now account for almost half of US GDP growth; such that without it, the country could face a financial crisis on the scale of the dot-com bubble burst.
At the same time, prominent tech figures including Dario Amodei, CEO of Anthropic, Sam Altman, his counterpart at OpenAI, and even Elon Musk have emphasized the need to slow AI development in the face of what they consider an existential threat.
But according to Bloomberg, whether such a slowdown is fundamentally feasible is doubtful; especially since China, as the other major pole of the AI economy in the world, has described these warnings as a form of “fearmongering.”
Also, a senior market strategist told the publication that slowing AI development means reducing capital expenditures, and such a trend could redefine profitability expectations for the entire ecosystem and, given the market’s high concentration on AI, become a serious challenge.
Rising interest rates can also increase risks, because borrowing to cover companies’ predicted staggering costs becomes more expensive.
On the other hand, it is still unclear whether this level of investment will yield returns in the long term or not; in 2026, returns on investment remain a distant and uncertain dream, while open-source AI models are getting closer to leading models every day and have made the path to a profitable business model more ambiguous.
Experts say that if this structure collapses, some companies will survive but many others will exit the field.
Michael Mallani, global market research director at Boston Partners, told Bloomberg that there will certainly be brands, but not many; only a handful of companies will succeed in obtaining the capital needed to justify their heavy costs.