Guide

Most AI security programs are built around one type of AI deployment. Most life insurers are running five. As AI agents move into claims triage, underwriting support, and policy servicing, they’re influencing decisions regulators already watch.

This guide provides a structured framework for the full AI security landscape in life insurance: the deployment archetypes, the risks each one introduces, and the controls required at every phase of the lifecycle, from governance and discovery through detection and response.

What’s Inside

• Why AI risk in life insurance is a market conduct issue: A manipulated or mis-scoped agent influencing a claim or underwriting decision creates unfair-discrimination exposure, and the NAIC Model Bulletin expects a board-accountable AI Systems Program to govern it.
• The agent is the perimeter: Identity, data, cloud, endpoint, and network controls are context inputs for what the agent decides to do, not standalone AI security solutions.
• The AI security lifecycle: Six phases of coverage structured around the NIST Cybersecurity Framework (CSF), each mapped to distinct capabilities and controls.
• How industry analysts are framing this market: Seven emerging categories, from AI Governance and AI Security Posture Management (AISPM) to AI Detection and Response (AIDR) and Guardian Agents, and where each sits in the lifecycle.
• Five deployment patterns, five distinct risk profiles: Embedded AI Systems, Democratized AI Systems, Homegrown AI Systems, Device-based AI Systems, and Homegrown Models, each with its own threat model, attack surface, and governance requirements.
• Per-archetype security controls: For each archetype, what it is, who builds it, the platforms it covers, and the controls required across every NIST CSF phase.

What You’ll Walk Away With

Whether you’re building a life insurance AI security program from scratch or assessing gaps in an existing one, this guide gives you the frameworks and vocabulary to do it right.

• A clear mental model of AI security: See how the phases, categories, and archetypes connect, and move from ad hoc coverage to a program with defined scope.
• A map of the five archetypes in your environment: Know which types of AI are active across your organization and the specific risks each one introduces.
• A lifecycle framework you can act on: Use the six phases to assess where your program has depth and where it has gaps.
• Per-archetype control breakdowns you can use today: Pressure-test your current coverage, prepare for regulatory examination, or brief your team.