D-POAF® Enterprise AI Governance Framework Extends the Decentralized Proof-Oriented AI Framework (D-POAF®) to the enterprise scale. It provides a structured operating model for governing the full portfolio of AI systems running across an organization, their criticality, autonomy boundaries, evidence and reliability, built on two organizational Wave Profiles (Control Wave and Delegate Wave) and four governance pillars: Enterprise AI Policy, AI System Catalogue, AI Autonomy Boundaries and Regulatory Compliance. The framework introduces a centralized AI System Catalogue with a per-system Intent Registry, a deterministic Impact × Reversibility decision matrix that assigns each AI system an autonomy level (A / B / C / D), and direct article-level mappings to the EU AI Act, SOC 2 (Type II) and ISO/IEC 42001. Output is an audit-ready evidence package combining Proof of Delivery (PoD), Proof of Value (PoV) and Proof of Reliability (PoR). Positioned as a complementary governance layer to the core D-POAF® framework, it is intended for enterprise architects, CIOs, CTOs, CISOs, AI governance teams, and risk, audit and compliance functions operating multiple AI systems at scale. With illustrative scenarios showing how D-POAF® and the D-POAF Enterprise AI Governance Framework apply across delivery, governance and enterprise-scale AI operations. Published by Inovionix under CC BY 4.0. More information at https://d-poaf.org.
IHSINE et al. (Tue,) studied this question.