By Lewis Nibbelin, Research Writer, Triple-I
Insurance affordability nationwide is constrained by a complex web of interlocking challenges, underscoring the need for solutions that target the root causes of increasing costs. Artificial intelligence has emerged as a leading tool to help ease the pressure, giving insurers opportunities to reduce operational expenses embedded throughout the policy lifecycle.
On the front end, McKinsey research on AI adoption in the insurance industry found a 20% to 40% decline in customer onboarding costs and a 10% to 20% boost in sales conversion rates, with early AI leaders creating roughly six times the total shareholder returns of their peers. The firm highlighted one U.K. insurer who reported more than $82 million in cost savings after implementing AI models for auto claims processing – in part due to a 23-day cut in liability assessment time.
Alongside improvements in claims efficiency and accuracy, AI systems can boost real-time data analysis, allowing insurers to mitigate risks that traditional methods have struggled to assess. Deloitte estimated that integrating the technology into hazard mitigation, for instance, could save approximately $70 billion in direct disaster costs globally by 2050, supported by AI-powered risk modeling capable of real-time detection and loss prevention.
Similar early-warning systems for fraudulent claims can facilitate fairer settlement outcomes and protect insurers and policyholders from unnecessary legal costs that keep upward pressure on premium rates. A separate Deloitte analysis suggested applying AI across the claims cycle could save insurers between $80 billion and $160 billion by 2032 through fraud reduction, translating to billions in savings for their insureds.
Regulatory momentum
A recent homeowners’ insurance affordability playbook from the National Association of Insurance Commissioners (NAIC) acknowledged AI’s potential “to help insurers detect or prevent fraud within the claims system, reducing administrative costs over time that could be passed on to consumers.” Yet these same capabilities can introduce new risks, NAIC emphasized, raising concerns about data privacy and model transparency.
To help establish an AI governance framework, NAIC launched the AI Risk Evaluation Supplement – formerly known as the AI Systems Evaluation Tool – to develop standards for assessing how insurers use AI. Currently in its pilot phase, the program involves 12 states and will continue through September, after which it will be up for consideration at the NAIC Fall National Meeting in November 2026.
While the program is not designed to replace existing market conduct or financial analysis, it’s worth noting that insurers must have a seat at the table as state or national AI regulations take shape. Insurers are well equipped to help ensure these guidelines suit the complex needs of insurance without hindering the industry’s commitments to equity and security, nor its capacity to continue pursuing AI-driven cost savings for consumers.
For further information on the NAIC pilot, read Triple-I’s latest State of the Tech Policy Brief, developed by the AI Policy Council.
Learn More:
Who Trains Tomorrow’s Underwriters? Insurers’ AI Talent Puzzle
Balancing Data Privacy with Modern Risk
Rethinking Claims Management for Today’s Risk Environment
NAIC Expectations for AI Oversight, Explained
How AI Helps Insurers Combat Fraud, Legal System Abuse
Cyber Claim Severity Surges as AI, Litigation Accelerate Risk
