Most organisations can generate a long list of possible AI use cases. The strategic challenge is not idea generation; it is deciding which opportunities deserve scarce attention, data, engineering and change capacity.
A useful portfolio view compares business value with feasibility, information readiness, risk, architectural fit and adoption impact. This creates a common language for discussing opportunities that otherwise look incomparable.
The goal is not to produce a perfect score. It is to expose assumptions, identify evidence gaps and sequence experiments so that learning compounds. High-value opportunities with major data or control gaps may need enabling work before a prototype is worthwhile.
A transparent prioritisation method also improves governance because decision makers can see why one use case was advanced and another was deferred.
Continue the decision
Use the capability assessment to connect the idea to your enterprise context, or discuss the transformation problem directly.