Jun 6, 2025

How Lawsuits in Healthcare Are Reshaping AI Insurance

Lawsuits over AI in healthcare claims may reshape how AI insurers assess risk, draft policies, and handle liability. Here’s what you need to know.

How Lawsuits in Healthcare Are Reshaping AI Insurance

A series of high-profile lawsuits in the last two years have targeted major health insurers over their use of AI in healthcare claims processing. These cases revolve around allegations that AI-driven tools have been used to systematically deny necessary care, sometimes overriding physician judgment and bypassing required individualized review. In this article we look at most significant recent lawsuits and how they are shaping the AI insurance landscape.

Kisting-Leung et al. v. Cigna Corp filed in July, 2023

In this case plaintiffs claim that Cigna (the 4th largest insurance company in the US, according to Investopedia) used an AI tool called “PXDX” to automatically reject claims without individualized review by a physician. According to the lawsuit, Cigna doctors denied over 300,000 claims using this method, spending on average just 1.2 seconds per claim and signing off on denials in batches. Moreover, plaintiffs claim that Cigna did not disclose the use of the PXDX algorithm and falsely stated that medical directors had made the claim decisions.

Estate of Lokken v. UnitedHealth Group, Inc. filed in November, 2023

UnitedHealth has been accused of using an AI model called “nH Predict” (developed by NaviHealth, a UnitedHealth subsidiary) to prematurely terminate coverage for post-acute care, such as rehabilitation stays, for elderly patients. The lawsuit claims that the AI model’s recommendations override treating physicians, apply rigid criteria, and lead to high rates of wrongful denials.

Barrows et al. v. Humana, Inc., filed in December, 2023

Similarly to UnitedHealth, Humana was accused of using the “nH Predict” AI model to wrongfully deny medically necessary care for elderly and disabled patients under Medicare Advantage. Plaintiffs claim that the insurer knowingly used a "highly inaccurate" AI model to deny coverage. This has led to a surge of appeals, 90% of which were reportedly successful, suggesting systemic issues with the model’s accuracy.

Common Legal Themes and Implications for AI Insurance Providers

Recent lawsuits against healthcare insurers for AI-driven claim denials reveal key legal risks that AI insurance providers must now consider. A major issue is the reliance on algorithms over human judgment, which raises concerns about liability when AI systems make flawed or unchecked decisions. Insurers of AI systems will need to scrutinize how much autonomy these tools have and whether proper oversight exists.

Transparency is another critical concern. Plaintiffs claim that insurers failed to disclose their use of AI or misrepresented how decisions were made. For AI insurance providers, this underscores the importance of insuring systems that are explainable, well-documented, and compliant with disclosure standards.

The lawsuits also highlight high error and denial rates, with many decisions overturned on appeal pointing to potentially systemic flaws in the AI. This suggests a need for tighter underwriting, more frequent audits, and clearer policy exclusions for known risks.

These cases are being pursued under multiple legal theories, including breach of contract, bad faith, and consumer protection violations. As a result, AI insurers must prepare for complex, multi-dimensional claims and craft policies that clearly define coverage in the context of evolving legal standards.

Conclusion:

As these legal battles unfold, they’re setting important precedents for how AI is governed and insured across all industries. We will keep following such cases and track how they shape the legal, regulatory, and operational landscape for AI insurance providers. Stay tuned as we continue to explore where AI liability is headed next.

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