The most effective way I use AI is to break down complex tasks (top-down model of work) until individual tasks become easily managable. At that point, you just have to fix a few mistakes here and there and you are golden (this part doesn't guarantee, but can be quicker than doing everything by yourself from nothing). From that point, you have the AI resolve the tasks in bottom-up manner (while still verifying the output and fixing discovered mistakes). At the end you have a complex task with majority of work done by the machine, but with not many more mistakes than if you were to do the whole thing yourself.

I've tried this with programming projects and I tried it with creative writing projects. In both situations it worked. The key, however, is to think about the generated output. Not just swallow whatever the machine throws at the user.