Several flaws here: dependomg on the tasks, you can train and retrain models. Instruct new ones. Previous errors will be greatly reduced, or disappear completely. ( if we talk about errors only ). Hallucinations are mathematically certain for less specialized models, but this is another problem all togheter.

Using ai is indeed saving money ( and time ). It excels at tedious tasks with well defined constraints. This saves me so much time everyday: ie: find X in dataset Y that do not much Z. This work was usually done by humans, with an higher error rate. If I take 3 minutes to classify 1 millions rows, which would have took me at least 3 days before, that is money saved.

This said, they trying to push the reverse centaur approach, human overseeing the ai worker, which is flawed. But companies reason in stakeholders profile and 3 months windows.

When I started as a junior i was the guy classifying 1 M records. That is how I leaned. Now we dont have juniors anymore. But companies seems to dont care about the next 5 years.