Runtime Control

Runtime control refers to governance mechanisms and safeguards that operate while AI systems are actively executing in production environments. This includes monitoring, throttling, and intervention capabilities that allow organizations to manage model behavior, detect anomalies, and enforce policies in real-time without requiring redeployment. Runtime control is critical for enterprises because it enables rapid response to emerging risks, compliance violations, and performance degradation while maintaining continuous business operations.

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Corporate PolicyGlobal2026-08-19

NHIMG: Agentic AI Governance Must Shift to Action-Level Runtime Controls

The Non-Human Identity Management Group has published practitioner guidance arguing that AI agent governance must move beyond deployment approvals to focus on what agents can do at runtime. The guidance recommends session-scoped entitlements, policy-as-code enforcement, and full-session-chain logging as the core control triad. Without these, organizations that have completed vendor due diligence and model inventory may still have no visibility into agent behavior during live sessions.

agentic AI runtime control policy as code least privilege non-human identity observability NHIMG agent governance