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AI can affect insurance pricing, but there is no evidence that it is destroying premiums across the market—or that AI caused any one person’s rate increase. The central risk is algorithmic discrimination: a model may use detailed data or apparently neutral variables that act as proxies for protected characteristics, potentially making cover more expensive or harder to obtain for some people.
What the AI risk actually is
Insurers can use AI and other complex algorithms to assess risk, support underwriting and pricing, detect fraud, or manage claims. These are distinct uses: evidence that an insurer uses AI somewhere in its operations does not establish that AI sets a particular customer’s premium.
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The concern is how a model turns information into a decision. It may analyze large amounts of data, including information a customer did not provide directly, and identify patterns that are difficult to see or explain. Even if a model does not explicitly use a protected characteristic, another variable may correlate with it and produce an unfair result. The U.S. Government Accountability Office has described both the potential uses of AI in insurance and concerns about prohibited factors influencing premium models, data accuracy, privacy, and ownership (GAO report).
Can AI raise your insurance premium?
It can contribute to a higher price for someone a model classifies as riskier, or make coverage less accessible. But that is a possible outcome, not an inevitable one. More granular risk assessment could also identify people who are lower risk than older methods suggested. Automation may improve efficiency, help detect fraud, or reduce costs; whether those gains reach customers as lower premiums is not guaranteed.
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EIOPA’s 2024 Digitalisation report, summarized in a 2025 publication, found that 50% of non-life insurers and 24% of life insurers were already using AI in areas across the value chain. Those figures cover multiple uses—including pricing and underwriting, fraud detection, and claims management—so they are not estimates of how many insurers use AI to set prices (EIOPA publication).
How to find out why your rate changed
A premium change by itself does not show that AI was involved. Rates may change for many reasons, and comparing quotes cannot diagnose whether an algorithm affected a decision. Ask the insurer for the specific factors behind the change and whether external consumer data or an automated system was used.
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- Ask for the decision factors. Request the information used to make the underwriting or pricing decision, its source, and how it affected the result.
- Check the data. If the insurer identifies information you believe is inaccurate, ask how to correct it and whether the decision can be reviewed using corrected information.
- Compare like with like. When seeking other quotes, compare coverage, exclusions, premium, and deductible—not just the headline price. A cheaper quote may provide less coverage.
- Use the applicable complaint route. If the insurer does not answer or you believe the decision was unlawful, check the insurance regulator or consumer-protection process for your jurisdiction and policy type.
What New York rules say about explanations
In New York, Department of Financial Services Circular Letter No. 7, issued July 11, 2024, addresses insurers authorized in the state that use AI systems or external consumer data in underwriting and pricing. It sets expectations around governance, actuarial validity, unfair discrimination, vendor oversight, and meaningful explanations of adverse decisions. It is New York guidance, not a rule that by itself governs every U.S. insurer.
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Rules differ by place and insurance line. The NAIC’s AI topic page describes a Model Bulletin adopted in December 2023 and state-level work; the bulletin and working-group process are not a single nationwide statute. Its status updates can change, so consult the NAIC AI topic page for current developments.
How the European Union treats some insurance AI
The European Commission identifies AI systems used for risk assessment and pricing in life and health insurance as high-risk use cases under the EU AI Act. That classification is not a universal rule for all insurance products or jurisdictions. EIOPA has also emphasized that sectoral insurance legislation continues to apply whether or not a system is classified as AI. The relevant requirements depend on the system, insurance line, and applicable law (European Commission overview; EIOPA publication).
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What AI may improve—and what it may put at risk
- Potential benefits: faster information gathering and risk assessment, process automation, fraud detection, and the possibility of finding people who qualify for cover under a more detailed assessment.
- Potential harms: discriminatory effects from proxies, inaccurate or opaque external data, privacy and data-ownership concerns, and higher prices or reduced access for people classified as high risk.
These are risks and possible benefits, not proof that AI always raises—or lowers—insurance prices. The UK Centre for Data Ethics and Innovation discusses these trade-offs in its snapshot paper on AI and personal insurance.
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