Specialty and commercial carriers face some of the toughest modernization challenges. Professional liability lines depend on complex rating, underwriting, and claims processes that have been shaped by decades of custom rules. Migrating these policy admin systems introduces real risk: undocumented business logic, fragile integrations, and high-stakes compliance requirements.

In this session, Praxent shares how their team used AI to modernize a legacy professional liability core system without disrupting business operations. You’ll see how AI agents embedded in the software modernization process reverse-engineered undocumented rating and underwriting logic, auto-generated regression tests, validated feature completeness, and accelerated delivery. Just as important, we’ll cover where AI fell short and human expertise was required to safeguard accuracy and compliance.

This candid case study offers a blueprint for specialty and commercial insurers who say, “we’d modernize, but no one fully understands this system.”  Attendees will leave with practical lessons on how AI can reduce modernization risk, preserve critical business rules, and help carriers bring complex liability products into a modern core without jeopardizing service continuity.