Artificial intelligence is transforming how consumers shop for policies, how insurers handle claims, how policies get priced and more. But with all of these benefits comes a clear warning: Don't let AI push humans out of underwriting and claims decisions. The human-in-the-loop remains a key defense against liability.
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90% of insurers expect AI claims automation within 24 months
With 90% of senior U.K. and European insurance professionals expecting AI to manage end-to-end claims administration within 24 months, governance frameworks are struggling to keep pace. Because regulators require explainable, auditable decisions, firms must pair AI tools with deterministic rules engines rather than relying on machine-learning models alone for claims decisions. Clear escalation paths, decision logs and audit-ready workflows are essential. Cost ranks low in procurement priorities — only 10% cite it as a strong factor — signaling that integration capability and vendor oversight matter most when evaluating AI solutions.
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AI tools drive record quote volumes in auto insurance shopping
Auto insurance shoppers averaged 3.5 quotes per person in JD Power's 2026 U.S. Insurance Shopping Study — the highest volume in the study's history — as mobile apps and AI tools lower the barriers to comparison shopping. Digital purchases are up 36% since 2021, with 48% of policies now bought online. Carriers that underinvest in AI-driven customer interactions risk losing ground: JD Power's research finds AI users are more likely to switch insurers and feel more confident in their coverage decisions. Usage-based insurance is also gaining traction, with 44% of recent shoppers citing it as a key decision factor.
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Continuous AI monitoring could reshape property underwriting
Water damage costs U.S. insurers nearly $13 billion annually, with claims averaging more than $15,000 — a figure that underscores the stakes of static underwriting models that capture risk only at policy issuance. Carriers moving toward continuous risk assessment can close the gap between assumed and actual risk by verifying that smart home mitigation systems — water shutoffs, sensors, security devices — remain operational throughout the policy term, not just at binding. Premium credits tied to ongoing device verification, AI-driven predictive outreach before freeze or storm events, and dynamic pricing models that reflect real-time property behavior are the near-term priorities for carriers upgrading from annual underwriting snapshots.
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AI underwriting demands transparency, policyholder recourse
As AI-driven underwriting reshapes property insurance — pulling data from aerial imagery, satellite feeds, permit records and third-party risk scores — regulators are tightening oversight. The NAIC's Model Bulletin on AI systems affirms that existing unfair discrimination and trade practice laws apply regardless of the technology used. Colorado, New York and California have each issued additional guidance on algorithmic underwriting. Carriers relying on third-party scores or AI-assembled property files must be able to explain what data drove a premium increase, repair demand or nonrenewal — and give policyholders a documented path to correct inaccurate information. Black-box processes increasingly invite enforcement exposure.
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46% of Gen Z pessimistic about AI's career impact
Nearly half of Gen Z adults (46%) are pessimistic about AI's impact on their careers, outpacing Gen X (33%) and a national average of one-third of Americans, according to Northwestern Mutual's 2026 Planning and Progress report. Only 23% of Americans overall express optimism. The survey also found 20% believe they will never achieve financial independence, despite an anticipated $124 trillion intergenerational wealth transfer. Fewer than one in three Americans plan to leave an inheritance, and the average inheritance falls below $50,000 — underscoring demand for proactive financial planning and advisor-led guidance across all age groups.
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ELDs, dashcams and AI target commercial auto's claims crisis
Rising claim frequency, severity and nuclear verdicts have made commercial auto fleets prime targets for plaintiffs' attorneys — but API-connected ELDs, dashcams and telematics are shifting the dynamic. Integrated systems capture GPS location, speed, braking and impact G-force alongside video evidence, giving carriers objective data to make sharper litigation-versus-settlement decisions. On the underwriting side, AI platforms can push throughput well beyond the five to 10 accounts a day a skilled underwriter can manually process. Fleet operators can further reduce exposure by tightening driver hiring standards, evaluating insurers on loss ratios rather than price, and proactively notifying carriers of vehicle and driver roster changes.
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Branch routes 85% of FNOL calls through AI channels
Branch Insurance now processes 85% of first notice of loss contacts through digital or voice AI channels, with that figure continuing to grow. Insurtech Liberate's AI platform can handle 6,000 calls per second — critical capacity during catastrophe events when human agents are overwhelmed. Beyond volume, AI voice tools detect tone and urgency to route calls appropriately and feed live agents real-time information via earpiece, lifting call-quality scores across experience levels. Carriers evaluating AI for FNOL should benchmark performance against their weakest agents, not their best — a framing executives at Berkshire Hathaway Travel Protection and Branch Insurance say makes the business case straightforward.
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Human underwriters remain key in cyber, E&O automation risks
Automating underwriting in specialty lines — particularly cyber and errors-and-omissions coverage — carries significant financial risk when subtle policy characteristics are missed, executives warned in a recent webcast. Sophisticated AI-driven cyberattacks are forcing insurers to reassess security architecture before expanding automation. Human underwriters remain essential for dynamic, judgment-intensive risks that models cannot reliably evaluate. On the governance side, carriers and MGAs are standing up AI committees with formal decision ownership, audit trails, explainability requirements and escalation protocols — structures that vary by decision type. Any model failure in E&O or cyber underwriting shifts concern immediately from efficiency to claims exposure.
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Vet vendor finances before deploying AI in claims decisions
Full automation of claims decisions exposes insurers to regulatory scrutiny and reputational risk — AI belongs in an assistant role, not a final decision-maker. A rules engine configured by the insurer, with AI handling workflow automation and anomaly flagging, keeps compliance obligations intact. During procurement, demand answers to three questions: Can the vendor demonstrate regulatory compliance? How transparent is the AI decision-making process? Is the vendor financially stable enough for long-term support? With many insurtech firms operating at a loss while overpromising, financial viability is as critical an evaluation criterion as technical capability.
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Allianz, New York Life map careful path to AI-driven operations
Executives from Allianz, New York Life, TIAA and Tokio Marine outlined a measured approach to AI adoption at Insurtech Insights in New York on June 3. Allianz CTO Christian Freytag warned that AI now represents a greater risk to insurers than business interruption or natural catastrophes, and flagged quantum computing-enhanced cyberattacks as a priority threat requiring intensified focus within two to three years. New York Life CIO Deepa Soni projected "substantial" operational impact from AI within five years, emphasizing friction reduction in advisor workflows. Tokio Marine North America's EVP and CIO Robert Pick cautioned against moving faster than governance and oversight frameworks can support — a particular concern for an industry whose core business is risk management.
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Oklahoma insurance commissioner candidates split on AI's role
Oklahoma's June primary will narrow the field of candidates vying to replace term-limited Commissioner Glen Mulready — and the next commissioner inherits some of the nation's highest premium rates with roughly seven months to act. Three of five candidates outlined priorities spanning rate reduction, carrier accountability and AI oversight. All three who responded agreed AI must remain a tool rather than a decision-maker, with Republican Bob Sullivan calling for mandatory disclosure when algorithms influence underwriting, pricing or claims. Democrat Craig MacIntyre warned that AI will deliver zero net value to policyholders. Republican Greta Shuler flagged AI-enabled consumer fraud as an emerging exposure insurers and regulators must address.
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This roundup was created with AI assistance. A Digital Insurance editor reviewed each item before publication.
