Realizing ISO/IEC 42001 through Decision Behavior Governance

As ISO/IEC 42001 (Artificial Intelligence Management System — AIMS) becomes the global reference standard for organizational AI governance, a persistent gap remains between declared compliance intent and demonstrable control over AI-assisted decision-making.Most current implementations rely primarily on administrative claims—policies, codes of conduct, risk registers, and manual review processes—which are structurally insufficient for governing the probabilistic and non-deterministic behavior of modern AI systems, particularly large language models (LLMs). This paper argues that the limitation lies not in enforcement rigor, but in the absence of governance at the point of decision formation.Meaningful realization of ISO/IEC 42001 requires a shift from administrative claims to engineering facts: institutionally defined conditions that exist prior to execution and determine the legitimacy boundaries within which decisions are permitted to be formed. We adopt Decision Behavior Governance (DBG) as the analytical foundation for this shift.Rather than proposing a specific architecture, framework, or implementation method, this paper clarifies the conditions under which governance can be said to exist at the engineering stage of AI-assisted decision formation.Under this interpretation, ISO/IEC 42001 compliance is reframed from post-hoc surveillance to an ex-ante question of governance existence, attribution, and auditability—independent of any particular technical realization.