Topic

Real-Time Governance

Real-time governance refers to the continuous monitoring, auditing, and enforcement of AI system policies as models operate in production rather than only at deployment checkpoints. This approach enables organizations to detect and respond immediately to policy violations, data drift, or emerging risks in live AI systems without waiting for periodic reviews. For enterprises, real-time governance is critical for maintaining compliance with regulations like GDPR and industry standards, reducing liability exposure, and ensuring AI systems remain aligned with organizational values and risk tolerances throughout their operational lifecycle.

1 item

StandardsGlobal2026-06-30

Academic Framework Proposes 7-Day Public Reporting Window for Tier 3 Agentic AI Incidents, Raising the Bar for Enterprise Anomaly Detection

A paper published on SSRN titled 'Transparent Real-Time Governance of Agentic AI Systems' proposes a tiered incident governance framework that would require AI Offices and National Authorities to publish public summaries of significant agentic AI events, including near-misses and blocked misuse attempts, within seven days of a Tier 3 classification. The framework targets agentic AI systems operating with meaningful autonomy and sets specific detection and reporting expectations for enterprise operators. Compliance teams deploying agentic AI should treat this as an early signal of the reporting granularity regulators may soon demand.

agentic AI incident reporting real-time governance anomaly detection near-miss disclosure