From Traditional Practice to AI Architecture

Artificial intelligence is transforming insurance, but most AI initiatives stall because they lack structured architecture grounded in real underwriting and claims practice.

In From Traditional Practice to AI Architecture, loss adjuster and AI Solutions Architect Hongxiang Sun argues that insurance professionals, not just programmers, must lead AI system design.

Drawing on his transition from senior loss adjuster to AI Solutions Architect, he explains how Large Language Models actually work, why messy insurance data undermines performance, and how to segment workflows so AI, deterministic code and human judgment each operate in the right place.

This paper offers a practical roadmap for professionals ready to architect robust, compliant AI systems.

Download the whitepaper