When a regulator or auditor asks how a compliance determination was reached, ""we asked our AI"" is not a defensible answer. Generative models can return different results for the same question and cannot cite the exact rule behind a finding, which turns unverified automation into regulatory exposure, failed audits, and rising operational cost. The distinction that matters for regulated manufacturing is architectural: deterministic AI compliance produces reproducible, source-traceable outputs, while probabilistic systems produce plausible guesses. This analysis breaks down why deterministic AI for audit-ready compliance rests on a verified regulatory knowledge base, a deterministic engine, and a generative layer confined to the interface. It shows how continuous, cross-framework determinations replace last-minute audit scrambles and manual, framework-by-framework review. Certivo, an AI-powered compliance system of record, applies this model so every determination traces
