What Needs to Be in Place Before AI: Lessons from Large-Scale Insurance Platforms

Artificial intelligence can only create real value when the underlying data, architecture, and governance are ready for it. In this talk, as a system architect I will share practical lessons from experience of designing and leading large-scale insurance platforms at three startup insurance companies, including quoting engines, carrier integrations, and cloud-native lead acquisition systems. Drawing on two decades of experience in insurance technology, I will outline four key prerequisites for successful AI adoption in regulated industries: solid data foundations, modular and API-driven architectures, strong security and compliance practices, and cross-functional teams and processes. The session is aimed at students, engineers, AI practitioners, and business leaders who want a clear, real-world view of how to prepare complex systems for AI at scale.
Speaker(s): Malar Kondappan
Virtual: https://events.vtools.ieee.org/m/522134