After years of testing generative AI and machine learning tools, many insurers are moving beyond questions about whether AI belongs in insurance and focusing instead on when pilot programs are ready for enterprise-wide deployment. During Carrier Management’s InsurTech Summit, industry executives said the answer is less about the technology itself and more about organizational readiness, business outcomes, and process integration.
James Thom, chief product officer at Vertafore, argued that insurers demonstrate readiness when conversations shift away from AI models and technical capabilities and toward measurable business results. He warned that carriers often pursue technically interesting projects that fail to solve meaningful business problems. According to Thom, successful AI initiatives become part of core workflows rather than standalone tools layered onto existing processes.
The discussion highlighted issues that claims organizations are also confronting as they evaluate AI-assisted claim handling, document processing, fraud detection, and customer communications. Executives emphasized that trust remains a critical factor. Human review and oversight continue to play a central role in validating AI-generated recommendations and building confidence in automated processes.
William Steenbergen, chief technology officer at Federato, said insurers must clearly define where AI fits within decision-making frameworks. In many cases, AI is being used to augment professionals rather than replace them. He noted that organizations can measure growing trust by tracking how often employees review and validate AI-generated outputs over time.
The panelists also pointed to challenges that extend beyond technology. Change management, employee adoption, legacy system integration, and regulatory compliance remain significant hurdles. Craig Weber of Cognizant described insurance as a highly interconnected ecosystem where introducing AI into one process can create unintended downstream impacts elsewhere in the organization.
For claims leaders and adjusters, the key takeaway is that AI implementation is increasingly becoming an operational and governance issue rather than a technology experiment. Insurers that successfully integrate AI into workflows while maintaining oversight and compliance may gain efficiency advantages, while organizations that delay preparation risk falling behind competitors as AI capabilities continue to advance.
