Eighty-four percent of large brokers with over $100 million in revenue now use generative AI. Claude, ChatGPT, and Copilot save producers hours every week on prospecting and reporting. But these tools are trained on public internet data, not insurance data.
That gap matters more in insurance than in almost any other industry. Regulation changes state by state. One wrong sentence in a submission or coverage recommendation can trigger an E&O event. And one in two agency records is missing critical fields, so generic AI often builds a confident answer on an incomplete picture.
The agencies pulling ahead are not the ones using AI first. They are the ones grounding AI in insurance-specific data. This whitepaper shows you what that gap costs and what to look for in a platform built to close it.
Come visit Zywave's website to learn:
- Why Insurance Needs Specialized AI Context
- The Hidden Cost of Incomplete Records
- What Generic AI Gets Wrong About Insurance
- The Difference Between Data and Intelligence
- Four Questions to Ask Before You Trust an AI Platform
