The best AI use cases are rarely found by asking where a tool could be applied. They are found by looking at repeated friction, avoidable manual work, missed hand-offs, and decisions that already consume time.
DDAI ranks opportunities by measurable value, data readiness, risk, operational complexity, and the level of human oversight needed. That prevents teams from chasing impressive experiments that do not survive contact with day-to-day work.
A good use-case shortlist should make the next step obvious: pilot, reject, defer, govern first, or build only after the evidence and control model are clear.