The continuous process of identifying and evaluating risks in real-time, allowing for timely responses to emerging threats in AI systems.
Moves beyond static, point-in-time risk reviews by integrating live monitoring (performance drift, security alerts, bias incidents) with automated risk-scoring engines. Governance workflows define risk thresholds tied to automated triggers (e.g., rollback, rapid incident response), ensuring AI threats are addressed as they arise rather than discovered after harm.
A payment-fraud AI platform implements dynamic risk assessment: live transaction data feed into a risk dashboard that scores emerging fraud patterns. When risk scores exceed thresholds, the system throttles transactions and notifies fraud analysts for immediate investigation - stopping fraud spikes in near real time.
