There is no published evidence here that clinicians’ use of AI automatically raises or lowers medical malpractice premiums, or that every AI-related claim is covered. The impact depends on two different things: how insurers use AI in their own operations, and how a clinician or practice uses AI in care. Insurance regulators expect insurers’ AI-supported decisions to comply with applicable law; clinical liability still turns on the facts, the policy, and the care provided.
How AI can affect medical malpractice insurance
AI can enter the picture on both sides of medical professional liability insurance. Insurers may use it to support underwriting, pricing, customer service, claims handling, marketing, and fraud detection. Separately, a clinician may use an AI tool in diagnosis, treatment, or another part of care. Those are distinct issues: insurer automation is governed by insurance rules, while a clinical claim may examine how the tool was used and how the clinician acted on its output.
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The NAIC says insurers remain responsible for compliance with applicable insurance standards and consumer protections when using AI, including accuracy, fairness, and avoiding unfair discrimination. Regulators may require insurers to explain their use of AI, and human oversight remains important. The NAIC’s public material does not establish how widely medical malpractice carriers use AI or show that a physician’s AI use changes that physician’s premium. (NAIC: Artificial Intelligence)
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The NAIC AI Systems Evaluation Tool is intended to help regulators gather information about insurers’ AI use, governance, risk controls, higher-risk models, and input data. As of the NAIC’s March 2026 update, 12 states were piloting the tool; adoption at the 2026 Fall National Meeting was anticipated, not yet reported as completed. This is a regulatory monitoring effort, not evidence of a medical malpractice premium rule.
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Does using AI increase a clinician’s premium?
The available evidence does not answer that question at the carrier or policy level. No AI-specific medical malpractice premium or claim-frequency statistic is established in the material cited here. It would be inaccurate to conclude that AI use necessarily makes a clinician’s premium higher—or lower.
The NAIC reported that the 2025 medical professional liability direct loss and defense-and-cost-containment ratio was 75.60%, 4.55% higher than in 2024. The NAIC also said direct losses incurred, defense and cost-containment expenses, and direct premiums written and earned increased in 2025 compared with 2024. These are overall medical professional liability market measures, not AI impact statistics; the NAIC does not attribute the changes to AI. (NAIC: Medical Malpractice Insurance)
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What medical malpractice insurance generally covers
Medical professional liability insurance protects physicians and other licensed healthcare professionals against liability associated with alleged wrongful professional practice, including related defense expenses. Whether a particular allegation involving an AI tool is covered depends on the policy’s terms and the facts; these general descriptions do not decide coverage for a specific AI-related claim. (NAIC: Medical Malpractice Insurance)
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These are general distinctions, not a substitute for reading the policy. Ask the broker or carrier how the actual wording applies to the timing and circumstances of a clinical AI allegation.
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Who may be liable if an AI tool contributes to a medical error?
There is no settled, universal answer established by the sources here. In the UK, NHS Resolution says clinicians using AI in care, diagnosis, or treatment continue to owe patients a duty of care. It describes the application of existing clinical negligence principles as fact-specific and says relevant case law has not yet clarified standards of care for care delivered using AI. Its guidance applies to NHS clinical services and NHS indemnity schemes subject to their usual terms and conditions; it is not a statement about US malpractice policies. (NHS Resolution guidance on AI, coverage and liability)
In assessing a particular clinical event, relevant questions may include whether the clinician relied on the AI output or used independent judgment, whether applicable guidance, training, or regulatory approval was followed, and whether known limitations were ignored. The answers depend on the tool, its intended use, the clinical workflow, and the evidence in the case. An AI vendor may have contractual or other responsibilities, but the material here does not establish that a clinician’s malpractice policy necessarily covers a vendor’s product liability.
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What to document when AI is used in care
NHS Resolution recommends governance that can explain how AI is introduced and used. The record should be proportionate to the tool’s function and the nature of the claim, rather than treating every AI interaction as identical.
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- Decision-making: Where relevant, record how an output was considered and why a recommendation was followed or overridden.
- Governance and information: Maintain evidence of governance and compliance with information-law requirements.
- Contracts: Address liability levels, standards, and warranties in agreements with suppliers.
- Staff preparation: Educate staff on the tool, its appropriate use, and its limitations.
For practical evaluation, consider the tool’s intended use and regulatory status, the degree of clinician oversight, validation and known limitations, auditability, documentation, and how contracts allocate responsibility. These are useful review dimensions, not a ranking of products or policies.
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What insurance regulators are saying about insurer AI
Rules differ by jurisdiction. As one state-specific example, a June 12, 2026 bulletin from the Texas Department of Insurance says AI-supported decisions by regulated entities remain subject to applicable insurance laws, including protections against unfair discrimination and requirements concerning claims practices. The bulletin also identifies state provisions addressing claims settlement, governance disclosures, rates, licensed agent and adjuster activities, and records. It is a Texas example, not a complete account of every state’s rules. (Texas Department of Insurance Bulletin B-0003-26)
Separately, the Lloyd’s Market Association Medical Malpractice Committee has identified emerging liability exposures and potential underwriting and claims implications from AI, and is compiling scenarios to examine risk and coverage questions. That signals industry attention; it does not establish that a specific exclusion or premium change has been adopted.
The American Medical Association announced policies on June 10, 2026, favoring physician oversight, transparency, accountability, evidence-based information, and audits for AI tools used in clinical decision support and coverage determinations. Those policies express a professional association’s position; they are not themselves statutes or binding insurance contract terms.
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Because the available public material does not settle policy-specific AI coverage, take the actual policy and workflow to the broker or carrier and ask:
- Does the policy address claims involving AI-assisted care?
- Are there relevant exclusions, endorsements, consent or documentation conditions, or reporting requirements?
- How could coverage interact with indemnity from an employer, facility, or AI vendor?
- For a claims-made policy, what reporting and extended reporting period terms apply if the policy ends or changes?
- Does the carrier require disclosure of particular AI uses, or provide written guidance about them?
Request answers tied to the policy language and your circumstances. General descriptions of malpractice coverage or insurer AI rules cannot determine whether a particular claim is covered.
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