> but ML enthusiasts (as opposed to experts) are so eager to use it that they end up prescribing it as a solution to every problem

Interesting you say "as opposed to experts". I think that's right on. It's been my experience on data science teams that the data scientists are often the ones pushing back on ML solutions and it's leadership who want GPT-3 or whatever latest ML model in the stack. I had one team where we were told we needed to call our ML work "AI" because if we didn't, leadership would think we weren't cutting edge and spin-up a competing team who was doing "AI".