MI9: An Integrated Runtime Governance Framework for Agentic AI

TL;DR

MI9 is a comprehensive runtime governance framework for agentic AI systems, providing real-time controls and monitoring to ensure safety, alignment, and responsible deployment in complex, unpredictable environments.

Contribution

This paper introduces MI9, the first integrated runtime governance framework specifically designed for agentic AI, addressing emergent behaviors and risks during deployment.

Findings

MI9 effectively monitors and controls agentic AI behaviors in real-time.

MI9's components cover diverse governance challenges not addressed by existing methods.

Scenario analyses demonstrate MI9's comprehensive safety and alignment capabilities.

Abstract

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.