AI can help organize a business update into questions, inconsistencies and proposed discussion points. Treat the output as preparation for a review, with people responsible for checking the evidence and making decisions.
Start with a small, well-defined task. Asking for a complete strategy from a handful of numbers invites assumptions that may never become visible.
Prepare a bounded input
Use approved data and tools. Include the reporting period, metric definitions and relevant constraints. For an initial exercise, fictional or appropriately de-identified information avoids exposing confidential business records.
An illustrative brief could say: “This fictional service team completed 18 projects this month and 20 last month. Average project size increased. Two experienced staff members were on leave. List questions for our operating review; do not infer the cause of the change.”
Ask for evidence and uncertainty
Request separate sections for observations supported by the input, missing information, possible explanations and questions for the team. Require each numerical observation to identify its source.
NIST's generative AI risk guidance identifies confidently presented false output as a risk. A fluent explanation is not proof that the model has calculated correctly or understood your situation.
Verify before the meeting
Recalculate important figures using your trusted records or spreadsheet. Remove unsupported claims and check whether the proposed questions fit the business. Do not let the model's first framing narrow the team's thinking prematurely.
Keep the final agenda short. The useful result is a better discussion, not a longer document.
Reference: NIST — Generative AI Profile.