The Three-Gate Architecture: Inspection, deployment and allocation in the governance of frontier artificial intelligence

Abstract

Frontier artificial intelligence is acquiring governance arrangements before comprehensive legislation has assigned stable decision rights over its most consequential capabilities. This working paper examines whether recent developments are better understood by separating three distinct objects of control: authoritative knowledge about capability, the capability state that leaves controlled development, and entitlement to receive or retain that state. It terms the corresponding decision sites inspection, deployment and allocation. The study combines a structured qualitative theory audit with a time-bounded, theory-building analysis of publicly documented frontier-AI cybersecurity cases in the United States and related allied responses through 9 August 2026. It argues that the contribution of the Three-Gate Architecture is not a new general theory of AI governance, but an integrative institutional topology that prevents distinct decision objects from being collapsed. The paper also proposes a candidate mechanism - cross-gate translation under reciprocal dependence, through which an inspection judgment may become a deployment condition and differentiated deployment may generate recipient categories. The evidence strongly supports the presence of all three gates, provides moderate support for cross-gate coupling, and does not establish regime formation. The framework is intended as a diagnostic and comparative map of decision rights in frontier-AI governance. The mechanism remains provisional pending repeated, traceable cross-gate causation across model cycles, capability domains and jurisdictions. Version: 0.2Evidence cut-off: 9 August 2026Status: Independent research report / working paper; not peer reviewed.