Your Role-Based AI Product Testing Checklist
Traditional QA won’t catch AI failures. Hallucinations, bias, model drift — these risks demand a different approach. This role-based checklist breaks down AI testing into actionable tasks for QA leads, developers, product managers, and business leaders.
Stop guessing if your AI works reliably. Get a systematic framework covering model validation, fairness testing, explainability, and compliance. Each role gets specific responsibilities to ensure your AI product ships with confidence, not crossed fingers.
What you get:
- Role-specific task breakdown for QA teams, developers, PMs, and executives
- AI-specific testing framework: model drift monitoring, adversarial testing, edge case scenarios
- Bias and fairness audit guidelines to prevent discrimination in model outputs
- Hallucination detection checklist to catch fabricated facts before users do
- Compliance and security validation for GDPR, HIPAA, and data leakage risks
- Integration roadmap for CI/CD pipelines with automated AI quality gates