With the AI boom in full swing, record valuations and hundred billion dollar deals being regularly signed, many are starting to question whether the entire AI boom is in fact a bubble.
The AI mania is causing industry leaders to sound the alarm. Goldman Sachs CEO David Solomon has warned that a lot of the capital flowing into AI will not deliver returns, Amazon founder Jeff Bezos has stated that though AI will bring great benefits we are likely in an industrial bubble and OpenAI CEO Sam Altman has publicly stated that we are in a bubble and that some people are “going to lose a phenomenal amount of money”.
Google CEO Sundar Pichai has stated that the AI investment boom has an element of irrationality in his view. BlackRock boss Larry Fink has said he does not believe there is a bubble since most of the money is being spent on “cloud and the power of the cloud”, which will likely be well-spent. However, he added that along the way, “we’re going to have some big winners and we’re going to have some big losers”.
The Bank of England recently warned that the entire AI boom could unravel due to the debt-fuelled nature of spending on AI infrastructure. On top of that, a report by Nobel prize winning MIT economist Daron Acemoglu showed that in 95% of cases corporate AI pilot programmes have shown no measurable positive impact. So what are the actual concerns?
State of AI valuations
The top AI-related companies are trading at enormous valuations — far above ordinary technology valuations, with record revenue multiples.
Driven by the demand for AI-capable chips, Nvidia reached a market valuation of $5-trillion briefly in October — larger than the GDP of every country except the US and China. OpenAI has an estimated annual revenue of $10bn (though it claims it is higher). It is now in talks about an initial public offering at a $1-trillion valuation — representing 100 times annual revenue.
Last year AI data integration and analysis company Palantir traded briefly at a $600bn market capitalisation — a whopping 600 times price to earnings ratio. Since January Anthropic had raised more than $20bn, having a new funding round every few months and doubling its valuation every time to a present valuation of $350bn, off revenues of $9bn.
Since September AI search engine Perplexity was at a $20bn valuation, despite annualised revenues of just more than $120m; 120-180 times revenue. These revenue multiples are far above the ordinary listed tech company median of seven to 10 times.
But it is not just the top companies, AI start-ups are raising at record levels too. In 2025 AI start-ups raised a record $150bn globally, representing roughly half of all global venture funding. In the US alone more than 50 AI start-ups raised more than $100m in 2025. AI start-ups around the world are raising incredible amounts of money and at incredible valuations (many with no revenue at all). In fact, there are start-ups raising hundreds of millions of dollars with no revenue and no product — just an idea and a promise.
Safe Superintelligence (SSI) was founded by Ilya Sutskever, a former senior scientist at OpenAI. Ilya raised $2bn in funding and Meta immediately offered to buy SSI for $32bn. SSI has no product, no plan, no monetisation strategy, just one vague goal; “build a safe super-intelligence before someone else builds a dangerous one”.
Thinking Machines Lab was founded by Mira Murati (former CTO at OpenAI) after a fallout with OpenAI. Murati secured $2bn in funding at a $12bn valuation with no product, no revenue and no customers. Flapping Airplanes is the latest AI start-up, founded in January with no product and no revenue, yet it raised $180m at a $1.5bn valuation with the goal to “rethink model training”.
Circular deals by top AI companies
Another issue being raised is that of circular deals being done by the top AI giants. For example, Nvidia agreed to invest up to $100bn in OpenAI to help fund a data centre, OpenAI then committed to outfitting those data centres with millions of Nvidia chips.
OpenAI signed a deal with Advanced Micro Devices (AMD) to get tens of billions of dollars’ worth of its chips. As part of the arrangement, OpenAI is to become one of AMD’s largest shareholders.
OpenAI also struck a separate $300bn deal with Oracle to build data centres across the US. Oracle then bought billions worth of Nvidia chips for those facilities, sending the money back to Nvidia, which then continued to invest in OpenAI. On top of that, OpenAI does not have $300bn for the chips and Oracle does not have $300bn worth of chips to sell.
This type of dealmaking has led some analysts to say while billions of dollars of deals are being signed, in reality the same money is moving back and forth between the top AI companies.
Paulo Carvao, a senior fellow at the Harvard Kennedy School who researches AI policy and worked in tech in the late 1990s, has said these types of circular deals were a large factor during the dot-com crash as well and that while these companies do have tangible products and customers their spending far outpaces their monetisation.
There are two primary fears in relation to this type of circular dealmaking. First, these deals give the spectre of high growth and will artificially inflate companies’ revenue numbers, which inflates their true value. Second, they tie the fortunes of all of these companies together, increasing systematic risk and making any potential crash far worse.
When do we make money?
The hype around AI came because this technology was so novel and exciting that investors thought they needed to get in at any price. However, as time goes on investors are increasingly starting to ask when these top AI companies are actually going to make money.
A recent HSBC report showed that OpenAI likely will not make a profit until 2030 and that it needs to raise at least $200bn just to avoid collapse. Elon Musk’s xAI is burning $1bn a month on compute, allowing free usage to consumers. The issue is that many AI companies do not have profitable business models, though some like Anthropic do. Anthropic is expected to overtake OpenAI in revenue this year and hopes to become cash flow positive in 2028.
Now many argue it does not matter if these companies have a profitable business model as the revenue growth and hype alone are enough to deliver investor returns. But this becomes a real risk given the trillions being spent on AI infrastructure that is heavily debt-fuelled. If the bet does not pay off it could leave these companies in ruin, leading to OpenAI’s overtures to the Trump administration for loan guarantees. This, in turn, led White House AI-czar David Sacks to declare that “there will be no AI bailouts”.
Misallocation of funds
AI does have the potential to completely reshape the future for the better and the results of the AI craze will likely be positive overall. In fact, there is still huge upside for AI investment given the tenchology’s potential. The issue is not whether there is a bubble but one of misallocation of funds within the AI field.
Investors are chasing returns and top-blasting a few large companies when those investments should be going into smaller, promising ventures with profitable business models that can show a tangible benefit to investors and society. Investors top-blasting a few large names will likely lose badly in any future correction, but investors betting on smaller ventures building real, profitable and customer-facing businesses could still win big in the long term.
Gumede, founder of AI business assistant NowNow, is author of “AI works for you”.
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