Four in 10 insurers now use artificial intelligence in underwriting, according to new research from Sollers Consulting. The shift, driven by competitive pressures and a softening market, moves a function that historically trailed other parts of the business into a decisive phase of digitalisation.
In 2025, the share of insurance IT roles demanding underwriting expertise doubled, expanding faster than any other specialisation in the sector. Sollers identified 126 active AI use cases across insurance, with 13 focused on underwriting. While this is fewer than in claims operations, the field is growing quickly.
Commercial lines lead adoption
Commercial insurance shows the most progress. One-fifth of providers already use AI to process data from unstructured documents and triage incoming submissions. Jakub ΕliwiΕski, Head of Underwriting at Sollers, said: "Underwriting was the last major function to be digitised, and the pace is now changing rapidly. We are already seeing AI support triage submissions and help underwriters generate quotes more quickly and consistently in standardised lines. Extending this to more complex, lower-volume risks will take another one to two years, as the necessary data foundations first need to be put in place."
Imbalance in AI application
For now, AI's impact concentrates on submission intake and document processing, leaving pricing and risk selection largely untouched. That balance will likely shift as insurers build underwriting workbenches that connect pricing models more tightly with user interfaces. Scaling these systems beyond initial triage requires a fundamental redesign of IT and business architectures, plus careful change management.
Regional differences take shape
London is moving away from traditional spreadsheet reliance, adopting adaptable pricing platforms that link directly to core underwriting infrastructure. Australian insurers, prompted by recent mergers, are beginning to digitise entire commercial underwriting processes. Carriers in North America extend AI from personal lines into complex commercial risks. Across the UK personal and commercial market, France, and the Nordics, the emphasis remains on data integration and interoperability-the necessary groundwork for automation. Poland and Central and Eastern Europe are transitioning fastest from pilot programmes to production-ready automated pre-screening and OCR-driven document processing.
Portfolio analysis as a practical bridge
Near-term, portfolio analysis and data aggregation offer insurers a sensible focus. Using AI for near real-time visibility into portfolios of highly customised contracts solves a major operational hurdle without altering core risk selection. This also addresses regulatory demands and frees underwriter capacity.
Why this matters for insurance professionals
The automation wave is arriving first in triage and document handling, so underwriters should expect their daily workflow to shift toward higher-judgment tasks. Teams that start building data foundations and becoming familiar with integrated pricing workbenches now will be positioned to handle more complex, lower-volume risks when technology catches up. As AI adoption accelerates across underwriting, staying informed through resources like the AI for Insurance training can help professionals navigate the changes.
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