I dont know if biology is a really good model?I don't either, but it's an extant one, and one in which we can collect a fair bit of largely-unbiased data reasonably immune to short-term manias, unlike, say, stock markets or technology hype cycles.
Over about 4 billion years, and under immense selective pressure, maxing out energy expenditure (biology's chief currency) at roughly 25% of the whole to information processing (input, storage, processing, output) seems to afford maximum benefit. It's also quite possible that genus homo's brain size has decreased over the past 200,000 years or so; h. sapiens neanderthalensis had slightly larger brains than modern h sapiens sapiens, though that size may not have been as intellectually or linguistically capable.
The other possibly interesting data series is of the magnitude of impact of information technology on social capabilities given rates of improvement of the former. Robert Solow, "You can see the computer age everywhere but in the productivity statistics". Computer capabilities have increased roughly 33 millions-fold since the 1950s, but productivity hasn't followed that same curve. Even looking at information technology spend vs. growth shows limited gains (computer capacity has become vastly cheaper over the same period, the same outlay buys far more capability than financial values would indicate). It seems likely that AI will follow a similar trend.
Though there've also been some marked transitions where capabilities have exceeded some limit or new applications / formats have become possible. Business computing beginning in the late 1950s, small businesses and universities by the 1970s, personal computing by the early 1980s, general networking in the 1990s, mobile devices in the aughts, algorithmic ad-tech / fin-tech / social media in the 2010s, and AI in the 2020s. There've also been capability-based advances including precision machining, automated equipment and systems controls, digital media (audio/video), accounting, navigation controls (marine, air, rail, land), re-usable rockets (largely from the ability to re-land boosters), massive satellite swarms, and LLM / gradient descent / synthetic annealing artificial intelligence. What the net societal and economic impacts will be isn't clear, and a fair bit of that is already clearly negative, as is the question of how those fruits will be distributed.
All of which affect the question of how big AI's energy footprint can grow. Though I'll note again it's growth rate and duration which matter, not present magnitude.
(Hope for clarity and accessibility that's both sufficiently nuanced and insufficiently verbose, though I've my doubts on the last.)