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AI adoption in reinsurance expected to stay gradual, AM Best says

AM Best says AI projects have so far skewed toward efficiency and cost reduction, with underwriting and risk analytics benefits likely to emerge incrementally rather than through immediate transformation.

Reported · Written up by our desk · Reinsurance

AI adoption in reinsurance is likely to progress gradually, even as interest grows, because the business relies on professional judgment and limited data for low-frequency, high-severity events, according to AM Best. In a recent report, AM Best said many early investments have centered on efficiency gains and cost reduction, including applications for document processing, claims administration, workflow automation, and internal knowledge management. The firm also noted that attention is broadening toward underwriting support and risk analytics, such as exposure analysis, portfolio monitoring, trend identification, and underwriting decision-making tools. While AM Best expects AI to differentiate reinsurers that incorporate it with proper governance and risk controls, it warned that meaningful benefits may take time. The report also highlighted challenges including model risk and limited explainability, regulatory compliance risks, governance and bias concerns, talent shortages, uncertain return on investment, and vendor dependence. AM Best said most reinsurers continue to emphasize human oversight, and that AI-enabled improvements to underwriting processes are becoming more apparent, but will likely develop incrementally rather than transform the industry quickly.

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