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What AI can—and cannot—tell you about a claim
It can help you read the policy
Large language models can summarize documents and answer questions about them. That can make dense policy language easier to navigate: you can ask where a policy discusses a type of loss, what a term means, or which exclusions may be relevant. But fluent wording is not proof that the answer is right. The National Association of Insurance Commissioners (NAIC) warns that AI can produce information that sounds accurate while being wrong, and advises careful review when the information will inform an important decision. NAIC: Insurance Topics | Artificial Intelligence.
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It does not settle whether your loss is covered
A policy explanation is not the same as applying the complete contract to a specific loss. Coverage may turn on the exact policy wording and endorsements, exclusions and conditions, what happened, what evidence supports those facts, and applicable law or regulation. An AI answer that overlooks one provision or assumes a fact you have not established can give you a misleading yes or no. The NAIC sources do not provide a validated accuracy rate for AI predictions of individual claim approval or payment.
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Insurers report using AI for tasks such as analyzing accident images, estimating repair costs or settlement values, and detecting possible fraud. Health insurers have also reported claims-adjudication uses. These are examples of tools within insurer workflows; they do not show that a general-purpose chatbot can predict the outcome of your claim. NAIC: Insurance Topics | Artificial Intelligence.
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How widely do insurers report using or exploring AI?
NAIC surveys asked insurers about using, planning to use, or planning to explore AI or machine-learning models. These figures describe reported activity, not accuracy, claim approvals, savings, or consumer outcomes.
| Insurance sector | Respondents reporting use, plans, or exploration | Report date |
|---|---|---|
| Auto | 88% of 193 responding insurers | December 2022 |
| Home | 70% of 194 responding insurers | August 2023 |
| Life | 58% of 161 responding insurers | December 2023 |
| Health | 92% of 93 responding insurers | May 2025 |
Because each percentage combines current use with plans or exploration, it should not be read as the share of claims decided by AI. The figures come from separate NAIC reports summarized in its AI overview.
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Why a claim outcome is more complicated than a policy summary
- The full contract matters: The declarations, policy form, endorsements, exclusions, limits, and conditions may all be relevant. A short summary can omit a qualification that changes how a provision applies.
- The loss facts matter: The cause, timing, location, damage, and supporting records or images may affect how the policy applies. A model cannot confirm facts it has not been given or evidence it cannot assess.
- Rules and insurer review matter: Applicable insurance laws and regulations constrain insurer decisions. Insurer processes may use automated tools alongside claims professionals, but the sources do not establish that a person reviews every AI-supported decision.
These factors explain why a general-purpose AI prediction cannot resolve a particular claim. They are not evidence that every insurer uses AI or that any specific model is accurate or inaccurate for a given claim.
How to use AI to review your policy more safely
- Provide the relevant documents, not just a short excerpt. Check that you are using the current policy and include applicable endorsements. Avoid treating a partial clause as the whole contract.
- Ask for the source language. Request the exact policy wording and page or section reference behind each explanation. Compare the quotation with your document rather than relying on a paraphrase.
- Separate coverage, exclusions, conditions, and limits. Ask the tool to identify each separately and explain how they might interact. Do not let a single yes-or-no response hide unresolved terms.
- Ask what facts are missing. A useful answer should identify assumptions and unanswered questions, not fill gaps with confident guesses. Check those assumptions against what actually happened and the evidence you have.
- Protect private information. Before submitting a policy or claim file, check the tool’s privacy and data-handling terms. Insurance documents can contain personal, financial, medical, or property details.
- Verify consequential answers with a person. Contact your insurer or a qualified insurance professional when the explanation is unclear, the claim is disputed, or a decision could affect your finances.
These checks also help you judge whether a tool is useful: it should show its source, distinguish uncertainty, flag missing facts, handle sensitive data transparently, and direct you to human help when needed.
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What to do if the insurer denies or disputes a claim
- Ask for the insurer’s written explanation. Request the policy provisions and facts supporting the decision. An AI-generated summary is not a substitute for the insurer’s written coverage determination.
- Check the explanation against the full policy. Review the cited wording and endorsements, and note any provision or fact that appears to be missing or misread.
- Correct factual errors and keep records. Provide relevant corrections and evidence, and preserve correspondence, claim documents, and photos or other records of the loss.
- Seek appropriate help if the dispute remains. Contact a qualified insurance professional or check with your state insurance department about applicable complaint options. The process and deadlines depend on the state and type of insurance, so confirm the rules that apply to your claim.
What AI regulation means for consumers
On December 4, 2023, NAIC members adopted a Model Bulletin on the Use of Artificial Intelligence Systems by Insurers. It says insurer decisions made or supported by AI must comply with applicable insurance laws and regulations, including requirements related to unfair trade practices. It sets expectations for insurer governance and risk management and describes documentation a state insurance department may request during an investigation or examination. NAIC characterizes the bulletin as guidance, not a model law or regulation, so its effect is not identical or automatically binding in every state. NAIC adoption announcement and the adopted Model Bulletin.
Regulators and insurers also identify risks associated with AI and big-data use, including inaccurate outputs, unfair discrimination or bias, weak transparency, privacy exposure, data vulnerability, and cyber threats. These are risks to manage, not proof that every insurer or AI-supported decision has those problems. NAIC: Insurance Topics | Big Data.
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NAIC says claims professionals, agents, and customer-service representatives continue to review information, exercise judgment, and work with consumers. That does not establish universal human review of every automated or AI-supported decision. The practical response is to ask how a decision affecting your claim was made and how to challenge factual errors.
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