Large Language Models (LLMs) are rapidly moving from experimental tools to embedded capabilities within modern insurance platforms. This session explores how built-in AI—designed directly into core insurance workflows—can meaningfully support underwriters, operations teams, and business users without disrupting established processes or governance.
We will share how our insurance suite leverages LLMs as an “intelligent co-pilot” across key operational touchpoints, including submission intake, data enrichment, risk analysis, decision support, documentation, and user guidance. Rather than replacing expert judgment, these capabilities are designed to augment human expertise by reducing manual effort, surfacing relevant insights, and improving consistency and speed.
The talk focuses on practical implementation lessons: where LLMs deliver real value in day-to-day insurance work, how human-in-the-loop controls and explainability are built in from the start, and how privacy, security, and regulatory considerations are addressed in production environments. Attendees will leave with concrete examples of AI-powered workflows, measurable operational benefits, and a clear framework for integrating LLMs responsibly into their own insurance systems.