A practical way to choose your first AI use case
Choose a pilot that can produce useful evidence without exposing the business to unnecessary risk.
Many AI programs stall between an impressive demo and real use. A good first use case matters to the business, has enough data to test and keeps a person accountable for the result.
Look for repeated judgment
Good candidates often involve summarizing, classifying, finding patterns or drafting a first response. The work should happen often enough that improvement compounds.
Avoid starting with rare, irreversible or safety-critical decisions. Keep a qualified person accountable for the outcome.
Score readiness honestly
Consider business value, data availability, error consequence, workflow fit and adoption effort together. A high-value idea with poor evidence is a research question, not a production plan.
Design the exit before the pilot
Define what success, revision and shutdown look like. A time-boxed pilot should produce a decision—not become an indefinite layer of manual work.
