Four in ten insurers now use AI in underwriting, Sollers finds
Four in ten insurers are already using AI in underwriting, but Sollers says the real gains are still in submission triage and document extraction.
Sollers Consulting research found four in ten insurers are already using AI in underwriting. The automation is landing in submission triage, unstructured document extraction and the first layers of underwriting workbench design.
Sollers Consulting identified 126 active AI use cases across ten markets, and 13 were directly tied to underwriting. About 20% of insurers are already using AI to triage submissions and extract data from unstructured documents in commercial insurance, where the workflow is crowded with broker emails, schedules, loss runs and attachments that can be machine-read before a human ever opens a case.
Pricing and risk selection are harder to scale because they depend on cleaner data foundations and a tighter link between the business and IT sides of the house. Underwriting expertise in IT roles doubled in 2025. Underwriting workbenches have already improved underwriting quality and professionalized the underwriter’s role, and intelligent document processing sits at the center of underwriting and claims automation.
Many carriers are connecting pricing models and user interfaces more tightly so AI can move beyond document handling into portfolio analysis and decision support. Sollers’ 2025 AI report counted 37 AI-automation use cases across five business lines, with AI mainly concentrated in data capture, document processing and parts of claims handling. Its newer release identifies automation, data extraction and submission triage as accelerating globally.
Accenture’s August 25, 2025 survey of 430 senior underwriting executives across life, commercial and P&C insurance found respondents expected AI adoption to rise from 14% to 70% within three years, while 81% said AI or gen AI would create new roles. In June 2026, McKinsey projected that agentic AI could push commercial and specialty insurers from manual, case-by-case underwriting to a machine-first, human-governed model.
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