AI use case: definition, selection and scoping
Why the Term Matters
Many AI initiatives fail not on the technology but on a use case that is too broad or too vague. Whoever wants to solve everything at once never builds anything testable. We scope use cases deliberately tight so that a prototype stands at the end of a workshop. A sharp use case is the most important prerequisite for turning an idea quickly into a result you can judge.
When It Is Relevant
- There is an idea but it is still too broad for a concrete build.
- A workflow should be automated and needs clear boundaries.
- Before the build it should be clarified which result is exactly meant.
- Several ideas compete and one should be tested first.
When Not
When the application is already sharply described and everyone means the same result, you do not need another scoping round, you start the build. And when a standard product fully solves the case, the question is not the use case but the product selection.
Industries That Use It
- Automotive suppliers: pre-structure requests and specifications from tenders automatically, as a tightly cut first case.
- Travel and tourism: sort and answer customer requests and booking details before processing.
- Legal services: detect contract clauses and prepare them for review, with a clear limit.
- Human resources: pre-sort applications and requests without replacing the decision.
Typical Use Cases
- An assistant that categorises and answers incoming requests.
- A workflow that reads documents and passes them on structured.
- A check of texts against defined criteria.
- A summary of long documents for fast review.
- A search over internal knowledge with cited sources.
Decision Guide
| Signal | AI use case fits | Alternative |
|---|---|---|
| Idea present, too broad | scope the use case tight | idea workshop for selection |
| Case already sharp | build directly | prototype in the workshop |
| Standard product solves it | rather not | licence the product |
| Result unclear | make the use case precise | clarify the goal with the business unit |
Example
An automotive supplier has the idea to process tenders with AI, which is too broad for a start. In the workshop the case is narrowed to pre-structuring incoming specifications and built as a prototype. Real tenders show whether the scope holds. This describes the approach, not an asserted metric.
Service Connection
The use case is sharpened in the AI workshop, built as a prototype and then moved into AI development or AI automation.
Sources
This framing describes common practice when scoping AI use cases. Technical and legal details depend on the concrete case and the chosen systems and should be checked there.