Strategic AI: test decisions when information is incomplete
Many business decisions happen before all the facts are known. A planning assistant should make uncertainty visible and help teams compare options rather than presenting a single answer as inevitable.
G-ATAI analysis
For a business pilot, separate observed facts, assumptions and unknowns in the interface. Ask the assistant to compare a few plausible scenarios using the same objective and constraints. Keep a simple baseline alongside it. If a recommendation only works when one hidden assumption is true, the person reviewing it needs to see that dependency before acting.
We recommend evaluating plans against deliberately incomplete inputs and changing conditions. Track how often new evidence changes the preferred option, whether the system admits uncertainty and what a wrong choice would cost. Success in a game does not establish reliability in a business workflow. Start with reversible decisions, record the reasons for human overrides and expand only when the evidence supports the added responsibility.
Questions before deployment
- Which assumptions change the recommended decision?
- How does the plan compare with a simple baseline?
- Can the owner reverse an action if new evidence arrives?
Independent commentary inspired by MIT News. No affiliation or endorsement is implied.
