It seems like the talk around the AI bubble is heating up, and the experts seem to be more and more confident that we're heading for a correction. A few thoughts:

1/ If you believe AI is way overhyped, then we're in for a correction. If you believe it's properly hyped, we're also in for a correction. In every meaningful technological revolution, the money comes into the market before that technology has reached its potential. Too much money too fast inevitably leads to a bubble bursting (this was the case with railroads, electricity, the telephone, etc.). In all of these cases, the technology eventually grew into the hype, but it took a lot of time, and the pace of that evolution was impossible to predict. Boom >> Bust >> Recovery.

2/ A lot of people are comparing the AI bubble to the dot-com bubble of 2000. On one hand, this is a ridiculous comparison. Many of the public companies in the dot-com boom were pre-revenue, and the PEs reached around 200, whereas the leading public AI companies have enormous revenues, and the PEs are in the 20s and 30s. On the other hand, this doesn't reflect the strength of the bubble in the private markets, as, for a variety of reasons, there is proportionally so much more money in the private market than there was back then. And it's easier to mislabel yourself as an AI company in the private market, leading to even more inflated valuations. As a reference point, between 1996 and 1999, 2,290 companies went public. Between 2020 and 2024, only 640 companies went public. So the average investor might be protected from much of the pain of a correction.

3/ A reason to be more optimistic about the pace of AI adoption versus the dot-com bubble was comparing each era's constraints. When Amazon went public, there were only 17 million adults with internet access, compared to around 5 billion today. So AI's TAM is, in theory, almost the entire world's population. AI has its own constraints, such as data, compute, and regulatory hurdles, though those feel much less restricting.

4/ Finally, I do wonder about the mislabeling point that may be more rampant than we saw in the dot-com boom. Finding a software company these days that isn't labeling itself as an AI company in some form is like finding a needle in a haystack. But much of it is simply old-fashioned, rule-based, deterministic software that doesn't think or reason on its own. The difference between AI and regular software isn't well understood by most people, and there aren't significant incentives for private investors relative to public market investors to highlight the distinction (they're more focused on achieving their next valuation markup rather than pursuing outsized operating margins).

In short, it’s hard to believe we’re not in some kind of bubble, but a correction feels like it’ll be more moderate and proportionally more impactful in the private markets. But even that should be taken with a grain of salt, as bubbles are intrinsically more about human psychology than any kind of fundamental logical reasoning, and, well, humans are weird.