I can't speak to bio applications, but I've gotten a solid exposure to AI in weather.
It is not "better" than the traditional models, in fact the AI models fall apart on a fairly short timeline. However they are useful for very short term forecasts done with less computation. You want to offer specific, precise forecasts over the next 8 hours, AI is going to be a solid strategy. So "it's going to rain on your neighborhood in 17 minutes for 39 minutes" is a tempting one for AI. What's the weather going to be in 3 days, well they come apart by then.
It's kind of like how an untrained person can eyeball a time lapse of radar and be able to guess pretty well what happens next, but you actually need understanding to make longer term predictions The AI models have much more data and much richer data than the human, but the example gives a rough idea of the strengths and weaknesses.
Note that AI in it's current forms certainly have utility. The issue is the magnitude of the investment is large and mostly driven by the parlor trick of text generation that superficially resembles human interaction and presuming that means open ended human replacement grade AI for general purposes is imminent..