AI is moving beyond prediction and recommendation to actively influence underwriting, claims, policyholder service, fraud operations, and financial outcomes. Trusted Autonomy in Insurance explores how insurers can govern this new generation of AI by securing the complete decision lifecycle, from AI intent and evidence to tool use, approval, and execution. The whitepaper examines where traditional security and governance controls fall short, highlights priority AI risk scenarios across the insurance lifecycle, and introduces an insurance AI control plane spanning discovery, observability, pre-execution governance, MCP security, runtime guardrails, endpoint AI security, evidence, and containment. It also explores evolving regulatory and governance expectations, including the emerging AI governance landscape Globally including United States, and provides practical guidance for insurance leaders looking to scale AI adoption while protecting policyholders and maintaining accountability.
Complete this form to access this resource