The rate limiting step for when a software project completes, is usually figuring out the architectural issues. Huge schedule misses are usually because something about the big picture was not understood, and a lot of work was done making the wrong thing, and then needed to be undone or thrown away once the problem was realized.
It's similar to how being a faster typist is nice and all, but it doesn't usually speed up your coding that much, because most of the time is not spent typing. Typing speed is not your bottleneck.
Having said that, I think it's too early to say this couldn't be a useful tool. For example, I have heard experienced devs say that AI assists can be very helpful when they have to switch languages to one they are less familiar with. Over time, it is plausible that AI assistants might make dev teams less often make the mistake of trying to cram the entire project into one language, when really it would go better if (to give one example) the query was in SQL and the frontend was in vanilla javascript and the machine learning was in python but the backend was otherwise in Go. Currently, teams are not willing to do that, and are more likely to attempt (mistakenly) to do it all in javascript, or do it all in python. If could be the case that in a couple years, as devs learn how AI coding assistants are best used, that they change how they work, and only then see the advantages.
Or, you know, it could all be a bunch of hooey. But, maybe not, and it will take a while to see.