Why this decision matters
Acceptance determines the required data, functions, interfaces, performance and handover materials, and therefore affects architecture, workload and pricing.
Early acceptance planning turns a vague request for an AI system into repeatable results and reduces scope misunderstandings and final-stage disputes.
Conditions to confirm before development
- Describe who uses the result and in which workflow
- Identify the data, samples or business records used for retesting
- Define outcome, performance, permission and exception requirements
- Agree code, documents, deployment, training and maintenance boundaries
Implementation and delivery approach
Create an acceptance framework before procurement and use it to assess data, system and third-party dependencies. Separate validation when major uncertainty remains.
Contracts or technical schedules should record environment, test method, responsibilities, pass conditions and treatment of failed items.
Acceptance boundary
Qualitative experience can use representative tasks and a defined review process, but ‘satisfactory results’ alone is not an acceptance criterion.