Il'll give you the point regarding LLMs.. but conventional neural networks? Nah. They've been used for a reason, and generally been very successful where other methods have failed. And there very much are investments into stuff with real brains or analog brain-like structures.. it's just that it's far more difficult, especially as have very little idea on how real brains work.

A big issue regarding digitally emulating real brain structures is that it's very computationally expensive. Real brains work using chemistry, after all. Not something that's easy to simulate. Though there is research in this are, but that research is mostly to understand brains more, not for any practical purpose, from what I know. But also, this won't solve the black box problem.

Neural networks are great at what they do, being a sort of universal statistics optimization process (to a degree, no free lunch etc.). They solved problems that failed to be solved before, that now are considered mundane. Like, would anyone really think it would be possible to have your phone be able to detect what it was you took a picture of 15 years ago? That was considered to be practically impossible. Take this xkcd from a decade ago, for example https://xkcd.com/1425/

In addition, there are avenues that are being explored such as "Explainable AI" and so on. The field is more varied and interesting than most people realize. And, yes, genuinely useful. And not every neural network is a massive large scale one, many are small-scale and specialized.