Risk-Based AI Observability
Prioritize AI observability signals by the risk they reduce.
AI risk can be invisible while uptime stays green. Map The Harm Before The Metric Start with affected people, decisions, data, and business consequences. A resume assistant, customer-support bot, pricing recommender, and medical intake summarizer create different risks. The metric set should follow the harm profile. Measure Early Warning Signals Risk signals might include segment-level outcomes, override rates, appeal rates, policy exceptions, missing-data frequency, evaluator disagreement, unsafe-answer detections, or drift in refusal behavior. These signals reveal failures that infrastructure dashboards will not catch. Assign An Action Owner A risk metric without an owner becomes a compliance artifact. Decide who reviews…
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