this is speech-to-text! OP is looking for text-to-speech.

This is an issue if it’s unsupervised, but the transcription models are good enough now that with oversight then they’re usually useful: checking and correcting the AI generated transcription is almost always quicker than transcribing entirely by hand.

If we approach tasks like these assuming that they are error-prone regardless whether they are done by human or machine, and will always need some oversight and verification, then the AI tools can be very helpful in very non-miraculous ways. I think it was Jason Koebler said in a recent 404 podcast that at Vice he used to transcribe every word of every interview he did as a journalist, but now transcribes everything with AI and has saved hundreds of work hours doing so, but he still manually checks every transcript to verify it.

AI saves time. There are few use cases for which AI is qualitatively better, perhaps none at all, but there are a great many use cases for which it is much quicker and even at times more efficient.

I’m sure the efficiency argument is one that could be debated, but it makes sense to me in this way: for production-level outputs AI is rarely good enough, but creates really useful efficiency for rapid, imperfect prototyping. If you have 8 different UX ideas for your app which you’d like to test, then you could rapidly build prototype interfaces with AI. Likely once you’ve picked the best one you’ll rewrite it from scratch to make sure it’s robust, but without AI then building the other 7 would use up too many man-hours to make it worthwhile.

I’m sure others will put forward legitimate arguments about how AI will inevitably creep into production environments etc, but logistically then speed and efficiency are undeniably helpful use cases.