Professor Jay Simon examines how generative AI performs in developing high-quality objectives for organizational and policy decisions—finding that while AI can effectively brainstorm potential goals, human expertise remains essential to ensure rigor, structure, and strategic value.
Key Takeaways:
-
GenAI can produce viable individual objectives but struggles to form coherent, non-redundant sets.
-
The best results come from combining AI output with decision-analysis expertise and structured prompting.
-
A “human-in-the-loop” approach ensures decisions reflect both efficiency and depth of reasoning.
“GenAI tools are helpful for brainstorming objectives, but a human with decision-analysis expertise is needed before the results can support real decision making," says Simon.