This is a reasonable analysis. It explains where AI is useful but I think it doesn't touch on AI's trustworthyness. When data is good, AI may or may not be trusted to complete it's task in an accurate manner. Often it can be trusted.

But sometimes good data is also bad data. HIPAA compliance audit guides are full of questions that are appropriate for a massive medical entity and fully impossible to answer for the much more common small medical practice.

No AI will be trained to know the latter is true. I can say that because every HIPAA audit guide assumes that working patient data is stored on practice-owned hardware - which it isn't. Third parties handle that for small practices.

For small med, HIPAA audit guides are 100 irrelevant questions that require fine details that don't exist.

I predict that AI won't be able overcome the absurdities baked into HIPAA compliance. It can't help where help is needed.

But past all that, there is one particularly painful issue with AI - deployment.

When AI isn't asked for, it is in the way. It is an obstacle to that needs to be removed. That might not be awful if MS, Google, etc didn't continually craft methods to make that as impossible as possible. It smacks of disdain for end users.

If this one last paragraph wasn't endlessly true, AI evangelists wouldn't have so many premade enemies to face - and there would be less friction all around.