Life and annuity (L&A) insurers are beginning to move beyond AI-assisted decision-making toward more agent-led execution models, supported by advances in foundation models, orchestration capabilities, domain-specific platforms, and evolving regulatory clarity. Agentic AI introduces the potential to coordinate and execute multistep workflows across underwriting, policy administration, servicing, and claims with reduced manual intervention. While adoption remains in early stages, L&A insurers are starting to prioritize high-volume, repeatable processes for near-term efficiency gains and are evaluating more complex workflows for phased autonomy, supported by governance, auditability, and integration with core systems. 

These developments are explored in Avasant’s Agentic AI Use Cases and Adoption in the Life and Annuity Insurance Industry Playbook. The playbook outlines how L&A insurers can begin identifying where agentic AI may deliver near-term operational value and where more deliberate process redesign will be required. It introduces a two-by-two prioritization framework that maps L&A processes based on workflow complexity and potential for agentic AI adoption, helping L&A insurers sequence investments while managing risk and readiness. 

The analysis covers a range of L&A insurance processes across the value chain, including product design, underwriting, policy servicing, claims management, distribution, and customer engagement. Each process is positioned within one of four quadrants: foundational automation, legacy constraints, strategic transformation, and scalable execution. These positions reflect expected adoption pathways and structural considerations rather than current-state maturity. 

The playbook covers agentic AI adoption across the following two segments: 

• Life insurance
• Annuity

The report provides several findings, including the following: 

• Agentic AI signals a potential shift from AI supporting decisions to AI progressively enabling coordinated execution across underwriting, servicing, and claims workflows in L&A insurance. 
• A layered, ecosystem-driven approach will likely be required for adoption, integrating foundation models, domain platforms, orchestration layers, and enterprise systems rather than deploying standalone tools. 
• Low-complexity, high-volume processes such as claims intake, policy servicing, and customer engagement are expected to be early candidates for agent-led execution. 
• High-complexity processes, including underwriting, fraud detection, and policy life cycle management, will likely require phased adoption, strong governance, and process redesign before broader deployment. 
• Legacy systems, data fragmentation, and regulatory dependencies remain key constraints that L&A insurers will need to address to scale agentic AI effectively. 

The playbook guides L&A insurers in assessing processes for agentic AI adoption and operational complexity, offering a clear framework to prioritize scaling, redesigning, or deferring actions. This enables L&A insurers to align agentic AI initiatives with operational priorities, regulatory expectations, and enterprise readiness as they gradually transition toward more coordinated and autonomous operating models.