In about two hours, learn to run sensitivity checks with AI's help and write a one-page brief that ranks the drivers and separates what the evidence supports from what is still open.
What you will be able to do
- Find the inputs that matter: Trace which inputs flow into your outcome measure and shortlist the handful worth testing, instead of walking leadership through all fifty lines.
- Run sensitivity checks you can defend: Change one input at a time over a stated low and high range, record the outcome at base, low and high, and keep a log someone else could rerun from the model.
- Rank drivers by impact and evidence: Place each driver on an impact-by-evidence grid and say in one sentence why it ranks where it does, so leadership sees both what moves the result and how sure you are.
- Separate facts from open questions: Record each supported fact with its source, reporting period, currency, units and calculation method. Label provisional or stale inputs, and give each open question an owner and a due date.
- Draft the brief with AI, then check every figure: Have an approved AI tool draft only from the material you give it, then check every number against the model and your sensitivity log before it goes to leadership.
- Keep sensitive information out of the wrong tools: Sort what can and cannot be shared with an AI tool, and prepare a stripped-down version of model information that is safe to share with an approved one.
Taught at learn.m-a-s-t-e-r.ai: lessons that adapt to your level, an AI tutor you can ask anything, quizzes and flashcards, and a certificate when you finish.
