Use-case assessment & pilot scoping
What the engagement includes
- Use-case definition and success measures
- Information readiness and access review
- Human review and failure-handling requirements
- Pilot design and ongoing cost considerations
AI use-case assessment & pilot scoping
Start with one useful task for AI.
Assess a document-search, response-drafting or enquiry-classification use case with clear information boundaries and human review.
This engagement defines a bounded use case and a controlled pilot. Production delivery requires technical validation, approved information, human review and an agreed support model.
Human review map
Keep responsibility visible throughout an AI task.
Each selection shows one control needed before a pilot can be considered responsible and useful.
Choose one repeatable activity with a clear start and end.
Examples include searching approved documents, drafting a routine response or classifying an enquiry.
Define what the system may use and what must stay out.
Confirm source ownership, accuracy, sensitivity, access and the process for updating approved material.
Treat generated content as a proposed result.
Set the expected structure, quality signals and cases where the system should stop instead of guessing.
A named person checks important output before it is used.
The reviewer verifies facts, tone, permissions and the decision impact using an agreed checklist.
Unclear or sensitive cases leave the automated path.
Record who receives the case, what context they need and how the final action is documented.
Scope control
Agree the scope first.
Production delivery is subject to technical validation and a supported platform.
The accepted quotation records deliverables, inputs, review points and support. Review the delivery controls.
Example AI pilot brief
Illustrative pilot: draft a response using an approved FAQ source. Exclude personal and confidential records. A named reviewer checks factual accuracy, source support and escalation behavior against a client-approved sample. Set acceptance thresholds before testing, and route unsupported or sensitive cases to a person. A successful experiment does not automatically authorise production access.