Insurers Using Advanced Analytics and AI Report Strong Returns on Investment and Premium Growth

Property and casualty (P&C) insurers in North America that invested more resources in advanced analytics and AI achieved greater profitability and premium growth, according to a new survey from WTW, a leading global advisory, broking, and solutions company.

The WTW 2026 Advanced Analytics and AI Survey reveals that insurers using more sophisticated analytics achieved combined ratios six percentage points lower and premium growth three percentage points higher compared to slower adopters between 2022 and 2024.

Laura Doddington, Head of Personal and Commercial Lines, Insurance Consulting and Technology, North America, WTW, stated: “Advanced analytics and AI are beginning to yield significant payoffs, as lead carriers report measurable returns on investment. With insurers planning to ramp up investment across personal and commercial lines, advanced analytics is shifting rapidly from competitive advantage to essential requirement to maintain market viability and drive sustainable growth.”

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Almost all insurers that took part in the WTW survey now use underwriting and pricing analytics. Close to 80% of insurers rely on advanced rating and pricing models, with an additional 11% planning to implement them soon. This makes predictive rating models essentially universal from 2026.

While claims functions have been slower to adopt, more insurers are now signaling aggressive plans to expand their use of advanced analytics. Although one-third or fewer carriers currently use claims advanced analytics for fraud detection (33%) and severity assessment (29%), these figures are expected to reach 65-70% within the next two years. An additional 36% plan to introduce straight-through processing in claims workflow automation, a significant increase from the current 14%.

Large language models (LLMs) and generative AI may be recent additions to the insurance industry, yet over half of survey respondents report already using them – another 29% plan to begin adopting these technologies within the next two years. While only 16% currently use AI to augment human underwriting, this figure is set to rise sharply, with 60% of insurers planning to prioritize this between now and 2028.

If survey respondents follow through with their intended AI and machine learning initiatives, adoption in underwriting, claims, and customer service is set to increase two or even threefold by 2028.

Data concerns and IT bottlenecks are the main challenges experienced by survey respondents in the adoption of analytics, with 42% reporting data-related issues – such as poor quality and limited accessibility – and inadequate IT support as significant barriers.

Building an analytics-driven culture also remains work in progress. Just 20% report having a well-defined analytics strategy to guide daily activities, and only 12% of insurers in the survey regularly offer analytics training to employees.

Doddington commented: “The ability to harness advanced analytics and AI will increasingly define market relevance, operational efficiency, and strategic agility. At the same time, using AI tools without a solid foundation may exacerbate existing issues rather than solve them.

“Data quality and robust governance, combined with the capability to deploy analytics without hitting IT bottlenecks, are crucial for successful AI and machine learning adoption. Insurers that master these fundamentals will be best positioned to leverage these advanced tools and techniques to gain a competitive edge in an increasingly data-driven market.”

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