There is still a categorical difference between how they are being used. Specifically analytic vs generative. Generative AI (LLMs and image generators) are the ones people have issues with - pretty much nobody cares about ML processing for analysis.
There’s a bit of a grey area, for example speech recognition. Would you classify that as analytic or generative? Whisper and speech LLMs work pretty well, but can completely make up stuff that wasn’t in the audio at all (see e.g. “thank you for watching” transcribed during silence). Other approaches are closer to the acoustic evidence but may make other mistakes (especially wrongly transcribing long tail, low frequency terms). Pick your poison.
> pretty much nobody cares about ML processing for analysis.
I work in a bank and a can tell you that the customers absolutely hate ML when it rejects their loan application. Over the pond in the US, I have an impression that the fico score is not exactly popular either, but I have no first hand experience.
In the US, FICO scores are mainly unpopular with "credit criminals" who have low scores. The score performs quite well in predicting how likely a borrower is to repay a loan. The problems that arise with credit scores in general are when they're used for purposes they were never designed to serve, like screening job applicants.
For home mortgage lending, FICO scores are now being partially replaced by VantageScore.