Generative AI can enumerate issues, suggest alternative explanations, and help organize text. Fluency, however, does not show that research is complete or that a proposal fits an organization’s particular circumstances. The quality of the question and the scrutiny of the answer remain essential.
Divide responsibilities
AI can help propose counterhypotheses, add perspectives, make checklists, and arrange preliminary information. The user must still verify facts, specify organizational constraints, choose values, and accept responsibility for action.
Tell the system what it cannot know
Internal arrangements and physical-world constraints may not be publicly visible. Saying “this production line cannot be changed” or “we must retain this customer group” can fundamentally alter the relevance of advice. Where such information cannot be shared, treat the response as a provisional hypothesis.
Ask questions that can be checked
Instead of only requesting arguments in favor of a proposal, ask when it could fail, what alternative explanations exist, and which statements require verification. Check consequential facts and citations against original sources. Review the provider’s data-handling rules before supplying confidential material.