Governance Framework for AI-Mediated Autonomous Network Device Management

This document defines a governance framework for systems that use artificial intelligence (AI) services, specifically large language models (LLMs), to autonomously detect, diagnose, and remediate operational anomalies on network devices. As AI-driven automation moves from advisory tooling to closed-loop autonomous operation on production infrastructure, the industry lacks a common set of principles governing what such systems may and may not do. This framework establishes thirteen governance areas covering human authority, harm prevention, management plane protection, minimum necessary action, bounded autonomy, transparency, reversibility, graceful degradation, escalation, AI-specific constraints, startup safety, absolute prohibitions, and review processes. It is intended to serve as a reference architecture for implementers building AI-mediated network management systems and for operators evaluating the safety properties of such systems.