2026-08-14 · Source: Reinsurance News
Summary in 3 Points • AI adoption in reinsurance is expected to remain gradual due to key challenges • Reinsurers are focusing on efficiency gains, cost reduction, and underwriting support with AI • AI poses challenges like model risk and regulatory compliance issues for reinsurers --- AM Best's recent report indicates that while AI is becoming a major differentiator in reinsurance, its adoption is expected to remain gradual due to several challenges. Reinsurers are currently focusing on efficiency gains and cost reduction through AI applications in document processing, claims administration, and workflow automation. The scope is expanding to include underwriting support and risk analytics, although human oversight remains crucial. Challenges such as model risk, lack of explainability, regulatory compliance, and talent shortages are significant hurdles. Despite these, AI is seen as a potential differentiator for companies that effectively integrate it with proper governance and risk controls.
For the London Market, the gradual adoption of AI in reinsurance could influence underwriting practices and policy wordings, particularly in areas requiring complex judgment. The challenges of model risk and regulatory compliance may necessitate adjustments in risk assessment and pricing strategies. As AI tools become more integrated, there could be opportunities for enhanced portfolio monitoring and trend identification, potentially leading to more competitive offerings. However, the market must remain cautious of the risks associated with AI, such as bias and vendor dependence, which could impact claims and exposure management.