Work by hand where the nuance matters: legal and medical material, anything carrying your own voice, and texts where someone has to decide what stays. A person understands the context and notices what the source is missing.
A model wins on routine: dozens of product descriptions, a draft that needs another tone, a long passage that has to be tightened. It also works as a second opinion, when your own phrasing will not come. The quality of that draft depends heavily on how the task is phrased — when the result comes out too generic, learning to write a proper prompt usually fixes it faster than trying again from scratch.
AI output is checked the way any borrowed text is checked, and in the same order: facts and figures, terms, conditions that went missing, claims that were never in the source. Read it aloud as a separate pass, because models like smooth phrases with nothing behind them — the rest of the tells, and how to make that kind of text sound human, are covered separately.
There are two places where a model usually slips. The first is the small print: a condition such as “on working days” quietly disappears, and the text promises more than the source did. The second is confidence, where “may reduce” comes back as “reduces”. Both are caught by comparing the draft against your list of points.
The practical arrangement is a split one: the outline is yours, the first retelling is the machine’s, the final edit is yours again. Rewrite the text in the iBro AI rewriter, then run the result through steps 4 to 6. If it still reads dry, improve the style and readability in a separate pass.