AI, obviously! A bubble doesn't mean demand vanishes overnight. There is - at current price points - much more demand than supply. That means the market can tolerate price hikes whilst keeping the accelerators busy. It seems likely that we're still just at the start of AI demand as most companies are still finding their feet with it, lots of devs still aren't using it at all, lots of business workflows that could be automated with it aren't and so on. So there is scope for raising prices a lot as the high value use cases float to the top, maybe even auctioning tokens.

Let's say tomorrow OpenAI and Anthropic have a huge down round, or whatever event people think would mark the end of the bubble. That doesn't mean suddenly nobody is using AI. It means they have to rapidly reduce burn e.g. not doing new model versions, laying off staff and reducing the comp of those that remain, hiking prices a lot, getting more serious about ads and other monetized features. They will still be selling plenty of inferencing.

In practice the action is mostly taking place out of public markets. We won't necessarily know what's happening at the most exposed companies until it's in the rear view mirror. Bubbles are a public markets phenomenon. See how "ride sharing"/taxi apps played out. Market dumping for long periods to buy market share, followed by a relatively easy transition to annual profitability without ever going public. Some investors probably got wiped along the way but we don't know who exactly or by how much.

Most likely outcome: AI bubble will deflate steadily rather than suddenly burst. Resources are diverted from training to inferencing, new features slow down, new models are weaker and more expensive than new models and the old models are turned off anyway. That sort of thing. People will call it enshittification but it'll really just be the end of aggressive dumping.