Data Readiness as a Critical Factor in AI Success for Property/Casualty Insurers

Artificial intelligence (AI) adoption in the property and casualty insurance sector is progressing from pilot projects to practical application, enhancing claims estimation, predictive underwriting, and fraud detection efficiency. However, varied results highlight that success is closely tied to the readiness and quality of data infrastructure. Many insurers struggle with fragmented legacy systems and siloed data environments, causing inconsistencies, incomplete records, and limited enterprise-wide visibility, which degrade AI model performance and trust. Establishing a robust data foundation with attention to quality, lineage, and accessibility is essential before advancing AI solutions to deliver enterprise-scale benefits in insurance operations.