MI9为智能体AI提供实时治理框架，解决运行中突发风险。
MI9: An Integrated Runtime Governance Framework for Agentic AI
- 通过六组件实时监控智能体行为与风险
- 实现对异常行为的动态检测与分级管控
- 适合需要安全部署智能体系统的生产环境
具备推理、规划和执行能力的智能体AI系统在运行时会表现出涌现性和不可预测的行为，带来传统预部署治理无法覆盖的新风险。为此，我们提出MI9——首个专为智能体AI设计的全集成运行时治理框架。MI9包含六个核心组件：代理风险指数、代理语义遥测采集、持续授权监控、基于有限状态机（FSM）的合规引擎、目标条件漂移检测及分级遏制策略。该框架可在异构智能体架构间透明运作，支持系统性、安全且负责任地部署智能体系统，弥补传统治理方法在生产环境中的不足。多样场景下的分析验证了其对现有方法未能覆盖的治理挑战的全面覆盖，奠定了智能体AI规模化安全部署的技术基础。
原文摘要 · Abstract (English)
Agentic AI systems capable of reasoning, planning, and executing actions present fundamentally distinct governance challenges compared to traditional AI models. Unlike conventional AI, these systems exhibit emergent and unexpected behaviors during runtime, introducing novel agent-related risks that cannot be fully anticipated through pre-deployment governance alone. To address this critical gap, we introduce MI9, the first fully integrated runtime governance framework designed specifically for safety and alignment of agentic AI systems. MI9 introduces real-time controls through six integrated components: agency-risk index, agent-semantic telemetry capture, continuous authorization monitoring, Finite-State-Machine (FSM)-based conformance engines, goal-conditioned drift detection, and graduated containment strategies. Operating transparently across heterogeneous agent architectures, MI9 enables the systematic, safe, and responsible deployment of agentic systems in production environments where conventional governance approaches fall short, providing the foundational infrastructure for safe agentic AI deployment at scale. Detailed analysis through a diverse set of scenarios demonstrates MI9's systematic coverage of governance challenges that existing approaches fail to address, establishing the technical foundation for comprehensive agentic AI oversight.
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