AI automation for insurance.

Insurance is a data-entry business wearing a risk-transfer costume. US insurers wrote roughly USD 1.7 trillion in net premiums in 2024, and property and casualty carriers alone accounted for USD 918.6 billion of it, up 7.1 percent over the prior year, per the Insurance Information Institute. In an industry first, US-domiciled P&C insurers crossed USD 1 trillion in direct premiums written in 2024, reaching about USD 1.05 trillion, an 8.0 percent jump, according to S&P Global Market Intelligence. Behind every one of those policies sits a chain of manual steps: a submission is re-typed into a rating engine, a quote is rebuilt in a proposal, a binder is keyed into the policy admin system, and a loss is re-entered again at FNOL. The industry employs close to three million people in the US, and a large share of their day is spent moving the same information between systems that do not talk to each other.

The cost of that friction is well documented at the point where money is priced. McKinsey found that 30 to 40 percent of an underwriter's time in commercial P&C goes to administrative tasks such as rekeying data or manually executing analyses, not to assessing risk. On the front of the funnel, speed decides who wins: in commercial lines the carrier that quotes in hours beats the carrier that quotes in days, yet a large fraction of submissions never bind while still consuming underwriter attention. On claims, the first notice of loss sets the trajectory for the entire file, and data captured there is re-keyed across the claims, policy, and finance systems by hand. Slow, inconsistent handling is not just an expense problem: unfair or unreasonably delayed claims settlement is a regulated market-conduct risk.

This is exactly the work AI is good at. Intake agents read ACORD forms, emails, loss runs, and PDFs and write structured submissions into the agency management or underwriting system. Quoting agents assemble multi-carrier proposals and flag appetite and eligibility. Underwriting-support agents pull third-party data, run the checklist, and prepare the file so an underwriter decides instead of collecting. FNOL and claims agents capture the loss, classify severity, check coverage, and route the file, with a licensed adjuster owning the decision. The goal is not to let software bind coverage or pay claims on its own: it is to hand the routine, rules-based paperwork to automation so producers, underwriters, and adjusters spend their time on judgment. Adoption is accelerating because the tooling now plugs into the systems carriers and agencies already run, from Guidewire and Duck Creek on the carrier side to Applied Epic and AMS360 in the agency.

Compliance is the gate, and it differs by border. In the US, insurance is regulated state by state under the NAIC model framework, including the Unfair Claims Settlement Practices Act, which each state's Department of Insurance enforces through market-conduct examination, so claim timelines, notices, and documentation have to hold up. In Canada, OSFI oversees solvency for federally regulated insurers while the provinces license and supervise market conduct, through bodies such as Ontario's FSRA and Quebec's AMF, and personal information collected in quoting, binding, and claims falls under PIPEDA federally and Quebec's Law 25. The Insurance Bureau of Canada reports P&C compliance costs rose 81 percent from 2022 to 2024, so automation that produces a clean, auditable record earns its keep fast. We are a Calgary-based agency serving agencies and carriers across Canada and the US, so we design for both regimes, keep a human on every regulated decision, and prove the ROI in weeks.