The Decision–Commit Gap: A Governance Architecture for Human–AI Systems

Artificial intelligence systems increasingly participate in decision processes that may produce real-world consequences. While most existing AI governance frameworks focus on alignment, safety layers, or human oversight, comparatively little attention has been paid to the architectural transition between interpretation and irreversible action. This paper introduces the concept of the Decision–Commit Gap, describing the structural boundary at which continuously evolving interpretation becomes a discrete commitment with external consequences. To address this gap, the paper proposes the C₂ Governance Framework, a decision architecture that separates interpretive cognition from commitment authority through three structural elements: the Decision–Commit Gap, the Irreversibility Stack, and the C₂ Control Loop. The framework introduces the concept of Human-in-Regulation, positioning human authority not as continuous supervision but as the explicit governance authority responsible for authorizing the transition from interpretation to consequence. By formalizing the seam between cognition and irreversible action, the C₂ framework offers a conceptual architecture for responsible human–AI co-working in socio-technical decision systems.