Agentic AI and Retrieval-Augmented Models in Straight-Through Underwriting

Artificial intelligence is reshaping actuarial practice, specifically within regulated decision workflows and unstructured data reasoning. Actuaries are transitioning from rule-based automation to LLMs, RAG, and multi-agent agentic systems that plan and reflect. RAG prevents AI hallucinations by retrieving real data from knowledge bases before generating answers, ensuring accuracy and currency. These emerging architectures support critical actuarial priorities, including transparency, auditability, and human-in-the-loop governance, facilitating more reliable straight-through decision processes in the insurance industry.