Work where you are an expert and can assess quickly whether AI is good or bad.
Work that is mere translation between frames or perspectives. For example, you have developed a policy but now have to turn it into a dozen different training documents for different audiences in your organization. AI is very good at this sort of translation, increasing and decreasing complexity of documents so that people can understand them.
Work where you know that AI is better than the Best Available Human that you can access, and where the failure modes of AI will not result in worse outcomes if it gets something wrong.
Work where you need variance, and where you will select the best answer as an editor or curator. Asking for a variety of solutions - give me 15 ways to rewrite this bullet in radically different styles, be creative - allows you to find ideas that might be interesting.
Beyond these clear-cut cases, here are five subtle but important areas where AI use can be counterproductive:
When you need to learn and synthesize new ideas or information. Asking for a summary is not the same as reading for yourself. Asking AI to solve a problem for you is not an effective way to learn, even if it feels like it should be.
