Overview
User Acceptance Testing (UAT) confirms whether an AI solution meets agreed business expectations. Production readiness goes further. It checks whether the solution can operate reliably, securely and with clear ownership in a live environment.
A successful test is a milestone, not the finish line.
What changes before production?
1. Data readiness
Verify production data access, permissions, data quality and handling of unexpected inputs.
2. AI quality
Evaluate results against agreed acceptance criteria. Define how uncertain or incorrect outputs are handled.
3. Exception handling
Plan for service failures, timeouts, missing data and unsuccessful processing. Use retries, alerts or human review where appropriate.
4. Security and monitoring
Validate access controls, audit logging, service health, error rates and the monitoring needed to investigate issues.
5. Operational readiness
Confirm deployment procedures, recovery plans, support ownership, escalation paths and business readiness.
The delivery perspective
The solution architect helps ensure that the design, integrations and controls are appropriate. The delivery lead coordinates dependencies, readiness evidence, risks and release decisions across engineering, testing, security, business and operations.
Production readiness should be planned from the beginning, not left until the final days before go live.
The bigger lesson
UAT confirms business acceptance for the scenarios tested. Production readiness confirms that the solution and its operating model are prepared for live use.