Episode 19 — Define AI Risk KRIs: Signals That Warn Before Harm Happens (Domain 2)
Key Risk Indicators (KRIs) serve as the early warning system for AI failures, and defining them correctly is a critical component of Domain 2. This episode explains the difference between KPIs, which measure performance, and KRIs, which signal changes in the risk environment before an incident occurs. For the AAIR certification, understanding how to select and monitor KRIs—such as a sudden increase in model error rates, data drift alerts, or a rise in user complaints—is essential for proactive risk management. We explore how to set threshold levels that trigger specific escalation or remediation actions when a KRI indicates that risk is exceeding the organization's tolerance. Examples of KRIs for generative AI might include the frequency of "unfiltered" responses or the detection of proprietary code in outbound prompts. By establishing these metrics, organizations can shift from a reactive stance to a predictive one, identifying and addressing AI vulnerabilities before they escalate into significant business losses or safety incidents. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
