Policy adherence measures whether an AI system follows defined rules. Policies might cover content, brand voice, legal constraints, security permissions, escalation paths, or tool-use boundaries.
Policy adherence should be encoded in prompts, policy layers, guardrails, and evals. If the rule matters, it should be testable with concrete examples and tied to a trace or decision point.