Relevance is part of AI evaluation methodology. Practitioners apply it to quantify quality, compare variants, detect failures, and build evidence for release decisions without relying on anecdotes alone.
AI Glossary
Relevance
Coverage in development
Relevance is part of AI evaluation methodology. Practitioners apply it to quantify quality, compare variants, detect failures, and build evidence for release decisions without relying on anecdotes alone.
Definition
Plain English explanation
Relevance helps teams decide whether a model is good enough to ship.
Related glossary terms
Last reviewed
Sources
- NIST AI Risk Management Framework — risk vocabulary context for AI systems
- Brel Digital company and technology profiles — applied usage evidence where tagged
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