Human-in-the-Loop
A design where a human reviews or approves an AI system's output before it is acted on. Required for high-stakes insurance decisions, especially adverse ones.
Human-in-the-loop means that an AI system’s output is reviewed by a human before it is used to make or execute a decision. In insurance, this is a standard governance requirement for high-risk decisions, such as coverage denials, prior-authorization rejections, and claims denials.
Regulators look past the formal setup. A human reviewer who almost always agrees with the model, or who has no time to understand the recommendation, is not meaningful oversight. The NAIC evaluation tool asks for documented override records and the reasons humans disagree with the AI. If those records are missing, the human review is a rubber stamp.
California’s SB 1120 makes the requirement explicit for medical-necessity decisions: a licensed clinician must make the final determination. Even without such a law, carriers should design escalation paths so that consequential AI recommendations can be challenged by a person with the right authority and expertise. See our guide to agentic AI in claims.