Moody's Ratings expects artificial intelligence to gradually improve efficiency across the insurance sector, with the clearest near-term impact in retail property and casualty distribution. The credit ratings agency's latest report says insurers are already using AI in selected operations, though the financial benefits so far remain modest.
Moody's expects wider adoption of AI for insurance to improve productivity and reduce operating costs, while introducing new operational, regulatory and cybersecurity risks. The company said AI is beginning to support underwriting, pricing, claims management, and capital and reserving analysis across the industry.
Where AI will hit first
Retail P&C insurance distribution is the area most likely to experience disruption in the near term, Moody's said, because of its high transaction volumes, routine processes and standardised services. The impact on life insurers will be more limited, because life insurance products are more complex, carry longer-term liabilities and face stricter conduct requirements.
Insurers have generally taken a cautious approach to using AI for core underwriting and reserving decisions, according to Moody's. The company expects AI-related benefits to be material but gradual.
Winners and losers
Moody's said AI will contribute to greater differences in performance between insurers. Companies with strong data infrastructure, financial resources and the ability to redesign processes around AI are likely to gain a competitive advantage.
Larger insurers can invest in technology, specialist expertise and data infrastructure. Smaller insurers benefit from fewer legacy systems and greater organisational flexibility. Mid-sized insurers may face the toughest position, with fewer resources than larger competitors and more complex operations than smaller firms.
In competitive markets, insurers may not keep all the financial gains AI creates. Some efficiency savings are likely to pass to customers through lower prices, particularly where products are similar and switching providers is straightforward. Moody's cited motor insurers as an example where increased competition could pressure profit margins.
Insurers that depend on long-term customer relationships and tailored services, including life insurers, may retain productivity improvements better than businesses operating in more standardised markets.
The risks
AI requires significant upfront investment in technology, data infrastructure, computing capacity, governance and specialist staff, Moody's said. Ongoing costs include model training, software licences and computing resources, and many insurers will need to run AI systems alongside existing technology before efficiency gains are fully realised.
AI models can lack transparency, may introduce algorithmic bias and often depend on third-party data and technology providers. While AI may reduce some errors associated with manual processes, Moody's believes failures involving automated decisions could attract greater attention from regulators and consumers, particularly where large numbers of policyholders are affected.
Cybersecurity is another concern. AI can improve the identification of software vulnerabilities but also increases exposure to cyber threats, data loss and fraud. Greater reliance on cloud infrastructure, external AI models and interconnected data systems could increase the effect of cyber incidents affecting technology providers.
Data quality, privacy and security also matter. Inaccurate or incomplete data can produce biased or unreliable AI outputs, while large-scale use of personal information creates challenges in meeting privacy and data protection requirements.
Moody's also said insurers may become increasingly dependent on a relatively small number of AI and cloud technology providers. Growing reliance on external AI services could create additional operational risks and increase regulatory attention as adoption grows across the sector.
Why this matters for insurance professionals
The report describes an industry where AI will change work gradually, not overnight. Underwriting, pricing and claims roles will shift as AI handles routine tasks, but human oversight will remain central to core decisions for some time. Professionals who understand how AI models work, and where they can fail, will be better placed as insurers invest in data infrastructure and governance. Those in retail P&C distribution should watch for price pressure as AI-driven efficiency spreads through competitive markets.
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