Explainability (XAI)

Explainability (sometimes "XAI") is the capacity of an AI system to provide a human-understandable rationale for its outputs — critical for high-stakes decisions like lending, insurance underwriting, or clinical triage, where regulators or affected individuals may demand a reason. Generative AI models are notably harder to explain than earlier classical ML, which is part of why governance frameworks have tightened alongside generative AI adoption.

Definitions are written for enterprise AI governance context, not a formal legal standard. Suggest a correction →