The problem, of course, is that generating a one time solution to a problem is a much easier problem space than a many-input task with human product concerns
Synthesizing a ton of inputs to help clarify a decision or set of options is exactly one of the easiest and most powerful use cases for AI agents right now.
I don't think that part is true, either. The average human could be trained to use an agent to synthesize information in their job to help make product decisions. The average human could not be trained to evaluate whether a reasoning model produced a correct proof in research-level mathematics. To be sure: reviewing a candidate proof at this level written by AI is significantly easier and faster than writing and creating it from scratch. But it's still not something hardly any humans could credibly do.