How would the AI bubble end?

Nov 5, 2025

The Nasdaq Composite, which is heavily weighted toward technology stocks, is up +123% in the last three years. We would not know for sure it is a bubble unless it pops. Economists say a bubble is an ‘upward price movement over an extended period of fifteen to forty months that then implodes’ (Manias, Panics and Crashes). Regardless of when the implosion happens, we are pretty sure that the upward price movement criterion is satisfied. Cyclically adjusted price-to-earnings ratio, also called Shiller P/E ratio, recently crossed 40 (WSJ has a chart). It has done that only once before and that was during the dot-com bubble. The long-run average is close to 17.

Stock prices could keep going up for a while or they could crash today. We have no way of knowing. However, there are structural factors at play that can give us an insight into how this will end.

Flash crash scenarios

Big technology companies are investing many tens of billions a year. Some are more creative in financing than others. Meta funded its Hyperion data center in Louisiana using off-balance sheet financing. The company is leasing the data center in four-year chunks along with a ‘residual value guarantee for the first 16 years of operations’ (Meta’s statement). It was creative enough that they had to check with S&P that it would not be considered debt, thereby impacting their credit ratings. S&P released a report saying it is okay, for now.

Meta has enough cash flow to make the payments. But when you pile up many of these deals, it does make the investors jittery. A company’s stock price is, in theory, the present value of its expected future cash flows. If you start eating into those cash flows without showing evidence of commensurate returns, investors will sour at some point and typically when you announce your earnings (Business Insider report).

Credit agencies like S&P could also change their minds when larger portions of these companies’ cash flows start going towards mandatory lease payments, servicing bonds, etc. Big technology companies have a long way to fall in terms of credit ratings (Microsoft’s rating is better than of the US government) but that does not mean that a credit rating downgrade would not spark a selloff.

Slow decline scenarios

If everybody keeps investing in the hopes of not being left behind and the market does not grow sufficiently, we could soon be looking at overcapacity. And overcapacity is not good for prices. This could be a recipe for profits to get competed away. It might become clear over months or even years.

Another factor is having continued market access to monetize the investments. Chinese open AI models have become the standard, capturing 63% of open model users (MIT Technology Review). In a fragmented market, the profits of American AI companies are not guaranteed. While American cloud hyperscalers might still run the compute for Chinese models, many customers will switch to more cost-effective Chinese providers. A general perception that China is winning the AI race is probably enough to start deflating the bubble. Any visible market share loss will add to the perception.

Plateau scenarios

Stocks plateauing after an upward price movement cannot be called a bubble. This is a desirable outcome for most people (unless you are Michael Burry). It is also the least likely because it involves a tightrope walk balancing investments and returns. Companies do not necessarily have to show that they can make their entire money back in the next few years but their revenue growth should affirm sound unit economics to pacify investors. There would be a divergence as some companies are able to make good on their money and others are not. If their net effects cancel out, we would get a plateau.