Insurers See Gains from Advanced Analytics and AI Use

Property and casualty insurers in North America are reporting improved profitability and premium growth tied to increased investment in advanced analytics and artificial intelligence (AI), according to a new survey from WTW.

The WTW 2026 Advanced Analytics and AI Survey found that insurers with more sophisticated analytics capabilities posted combined ratios 6 percentage points lower and premium growth 3 percentage points higher than slower adopters between 2022 and 2024.

"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," said Laura Doddington, head of personal and commercial lines, insurance consulting and technology, North America, WTW.

The survey indicates that underwriting and pricing analytics are now widely used across the industry. Nearly 80 percent of insurers rely on advanced rating and pricing models, while an additional 11 percent plan to implement them, making predictive rating models nearly universal by 2026.

Adoption in claims functions has lagged but is expected to accelerate. Currently, 33 percent of insurers use advanced analytics for fraud detection and 29 percent for severity assessment. These figures are projected to reach 65 to 70 percent within 2 years. Similarly, 36 percent of insurers plan to introduce straight-through processing in claims workflows, up from 14 percent today.

Use of large language models and generative AI is also expanding. More than half of respondents report current use, while 29 percent plan adoption within 2 years. Only 16 percent currently apply AI to augment underwriting, but 60 percent expect to prioritize this capability by 2028.

If planned initiatives are executed, adoption of AI and machine learning across underwriting, claims, and customer service could double or triple by 2028.

Despite the momentum, insurers continue to face operational challenges. Forty-two percent of respondents cited data-related issues, including poor quality and limited accessibility, as well as inadequate IT support, as key barriers. Organizational readiness also remains limited, with only 20 percent reporting a defined analytics strategy and 12 percent offering regular analytics training to employees.

"The ability to harness advanced analytics and AI will increasingly define market relevance, operational efficiency, and strategic agility," said Ms. Doddington. "Data quality and robust governance, combined with the capability to deploy analytics without hitting [information technology] bottlenecks, are crucial for successful AI and machine learning adoption."