AI Validation Readiness Checklist
An assessment structure for AI applications in regulated environments, built on intended use and consequence rather than technology hype.
What's inside
- Intended use and explicit out-of-scope definition
- Consequence and risk evaluation prompts
- Data provenance and representativeness checks
- Human oversight and reviewer accountability design
- Performance criteria and test data considerations
- Model, prompt and version change control
- Monitoring for drift and degradation
Who it's for
Quality, IT, digital transformation, validation leads