We might be able to model some idealised AI transition as people bidding on intelligence. AIs carry out increasingly open ended and underspecified work trying to do what's best for the specific human, given some amount of token usage the human bids for.

I think this continuous model is cleaner and more accurate than a binary 'do you have access to this model or not' (although in reality it will not be a clean auction system because people have other preferences about how they want prices to behave and can impose social costs to encourage sellers to set prices more arbitrarily.)

The price mechanism here would surface high value uses effectively during this transition. People saying 'This is my problem and I will pay to have it solved' gives information that anything short of transformative AI won't have.

You could model the AI company as having a bid price of its own, where below this number it would prefer to receive the cash than over additional AI usage. You would then expect the labs to still use the AI a lot, but if there is diminishing marginal return, and need for revenue, there must be a cross-over point.

They also have an incentive to provide AI services broadly, because they benefit indirectly from the rest of the economy running more efficiently. Neither they, nor the AI, can see what the highest value uses of the AI are overall, so by handing this off to a price mechanism, they get access to the value generated via the improvements in the broader economy (their power costs go down, their food becomes cheaper, their suppliers and their supplier's supplier's run more efficiently, etc, etc).

In reality, there are forces against the labs providing AI services like this too, such as caring about the relative gap in capabilities between themselves and their competitors or bad actors.