Generative AI’s arrival in insurance made headlines for speed. Accuracy, consistency, and scalability determine whether it stays. This webinar examines why AI built on insurance-specific language models, knowledge structures, and operational rules outperforms general-purpose AI on what matters most to underwriting organizations: getting the right answer, consistently, across every submission, team, and line of business.
Join Datos Insights Senior Principal Meredith Barnes-Cook as she sits down with mea Group CEO Martin Henley and EMEA CEO and Global Growth Leader Max Richter for a practical conversation on how insurance-native AI changes underwriting work from submission intake through renewal, and what carriers, MGAs, and brokers gain once they move beyond the pilot stage.
You’ll learn:
- What enterprise-scaled, AI-driven results require
- How to judge your AI success: the accuracy, consistency, and repeatability tests that predict whether it will scale or stall
- Why insurance-native AI runs alongside the systems you already have, and what that means for integration scope, timeline, and the demands on your IT team
- What underwriters do with the hours AI hands back, and how leading teams are building talent around the new role
For technology leaders, the real questions are how insurance-native AI fits into that existing architecture, what integration actually takes, and whether it holds up to the auditability standards regulators are tightening. For underwriting leaders, the question is simpler: where do general-purpose tools fall short, and what does industry-specific AI close?
Can’t attend live? Register anyway and we’ll send you the recording.
