AI's Data Problem

Everyone in insurance is talking about AI. Almost nobody is talking about what AI actually needs to work.

AI models are only as reliable as the data you feed them. In an industry where policy records have been migrated, re-keyed, and patched across multiple legacy platforms for thirty years, that foundation is shakier than most executives want to admit.

Before any carrier deploys a predictive model in underwriting or claims, someone needs to do the unglamorous work of auditing field-level data consistency, resolving duplicate records, and establishing clear data ownership. That work doesn't appear in vendor demos.

The insurers who will get durable value from AI in 2025 and beyond are the ones investing in data governance right now — not just GPU infrastructure. The algorithm is the easy part.