Suppose an AI model fully automates a $200k job. Its economic value - measured in contribution to GDP - will be both far more and far less than $200k.
There are two ways of thinking about the model's economic value:
(1) It'll be far more than $200k. After all, the human worker's labor was worth $200k; AI workers will have a bunch of advantages over humans, like not needing to sleep and being able to run in parallel, so their labor will be worth even more.
(2) It'll be far less than $200k. Competition between labs might drive the price of AI down until it's basically equal to the cost of the GPUs and energy. And this is obviously way lower than the human worker's contribution to GDP.
The important idea is that both are right.
The marginal contribution to GDP of running an additional instance of this model will probably be relatively low.
But we'll end up running way more copies of it, so the model's total contribution to GDP will be way higher than the human workers it replaced.