Runtime Controls

Runtime controls are mechanisms that monitor, enforce, and adjust AI system behavior during active execution or inference. These controls enable organizations to impose real-time guardrails such as output filtering, rate limiting, and dynamic policy enforcement without requiring model retraining. For enterprise governance, runtime controls are critical because they provide the last line of defense against harmful outputs, unauthorized data access, or policy violations, and they allow compliance teams to adapt restrictions quickly as risks evolve.

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ResearchGlobal2026-09-16

Accountability Gap in AI Agent Governance: Who Owns the Gateway?

NHIMG has published practitioner guidance arguing that accountability for AI agent risk should attach to the gateway between agent and tool, not to a job title. The guidance identifies three unresolved ownership questions: who enforces controls, who approves exceptions, and who produces evidence that controls are active in production. Compliance teams with agent governance policies on paper but no named functional owners are the primary audience.

NHIMG agentic AI MCP accountability agent governance runtime controls compliance ownership