What if there really is an AI bubble? Which non-price signals might warn us first?

If there really is an AI bubble, it probably wouldn’t show up first in prices. By the time prices move sharply, the story is usually already visible in the background.

History gives a few useful reference points. In the 2008 housing bubble, rising mortgage delinquencies and early stress in repayments appeared well before the actual crash. Prices stayed high for a while, even as the underlying system was already weakening.

So I keep wondering what the equivalent signals would be in AI.

Not price movements, but behavior changes underneath the surface.

Maybe companies start quietly admitting that AI tools are more expensive than replacing certain roles with humans, despite earlier claims of efficiency gains. Or hiring patterns shift again, moving toward consolidation and cost-cutting in AI-heavy teams.

Maybe funding behavior changes first. Not the disappearance of investment, but a shift in which projects get funded. Fewer experimental AI startups receive money, while a small number of dominant players attract most of the capital.

Or maybe the signal is subtler. Productivity gains that were widely assumed start to plateau, while costs of scaling models continue rising faster than expected.

Of course, none of this guarantees anything. Markets do not always announce transitions clearly, and early signals can easily be noise that people over-interpret in hindsight.

But if you assume there is a bubble somewhere in the system, the real question becomes:

What kind of signal would actually convince you it is not just noise anymore?

And would you expect that signal to show up in companies, in funding behavior, or in how people talk about AI internally first?