The United States government is currently piloting an ambitious program leveraging artificial intelligence to inform insurance-coverage decisions, specifically within the contentious realm of prior authorization for medical care. This initiative, designed to curb unnecessary medical spending and reduce waste, is unfolding against a backdrop of widespread patient and physician frustration with a system often described as opaque, burdensome, and detrimental to timely care. While proponents argue AI could streamline approvals and enhance efficiency, critics warn of an alarming potential for increased wrongful denials and further erosion of patient access to medically necessary treatments, raising profound questions about the future of healthcare gatekeeping.
The Prior Authorization Labyrinth: A System Under Scrutiny
For countless Americans, the process of obtaining pre-approval for physician-recommended medical care has become a familiar, often agonizing, hurdle. Personal accounts widely circulate, detailing the arduous "tribulations" patients endure as they navigate a labyrinth of bureaucratic requirements to secure coverage for essential prescription medications, medical procedures, and other vital services. This system, known as prior authorization, requires healthcare providers to obtain approval from an insurance company before rendering specific services or prescribing certain drugs.
The original intent behind prior authorization was rooted in sound principles: to serve as a crucial check on healthcare overuse, control escalating costs, and ensure that patients receive care that is both medically necessary and cost-effective, exploring less expensive alternatives where appropriate. In an ideal scenario, prior authorization prevents unnecessary procedures and safeguards against fraud, ultimately benefiting the healthcare system by conserving resources. However, its practical application has frequently deviated from this ideal. A large majority of physicians, including those surveyed by the American Medical Association (AMA), consistently voice grave concerns about significant care delays attributed to prior authorization. These delays, physicians report, can lead to patients abandoning recommended treatments altogether while awaiting insurers to verify eligibility and confirm medical necessity. The appeals process for denied care, while available, only compounds these delays, often placing further stress on already vulnerable patients.
The Promise and Peril of AI in Healthcare Approvals
In theory, artificial intelligence, with its unparalleled capacity to rapidly process and analyze vast quantities of information, presents a compelling solution to the prior authorization bottleneck. AI algorithms could, in principle, quickly identify and expedite the approval of unambiguously allowable claims, thereby dramatically reducing wait times and alleviating the administrative burden on both patients and providers. This efficiency could translate into swifter access to care, potentially improving patient outcomes and streamlining healthcare operations.
However, the integration of AI into prior authorization is far from universally embraced and is currently facing substantial resistance. A primary concern is the potential for AI-driven systems to increase wrongful denials of health insurance coverage. The American Medical Association’s 2025 survey of physicians underscored this apprehension, revealing that a significant 61 percent of doctors worried that AI tools would exacerbate the denial of treatments they deem medically necessary. This concern is not unfounded; if AI systems are primarily optimized for cost-cutting rather than patient care, or if their algorithms lack sufficient transparency and clinical nuance, they could inadvertently or systematically reject valid claims.
Health policy analysts emphasize that AI’s role should be carefully defined. As Camm Epstein articulated in an email to Undark, "AI should be used to make appropriate care easier to approve, not necessary care easier to deny." This statement encapsulates the central ethical dilemma facing the deployment of AI in such a critical, patient-facing domain. The AMA further advocates for robust safeguards, requiring insurers to provide detailed clinical reasoning to justify any coverage denials and demanding greater transparency regarding the underlying AI algorithms and their decision-making processes. Without such oversight, there is a legitimate fear that AI could become an even more formidable gatekeeper, further distancing patients from the care they need.
Government Initiatives: The WISeR Model in Focus
Amidst this evolving landscape, the Trump administration has launched a pilot program in six states, specifically designed to leverage AI in an effort to reduce unnecessary medical spending. This initiative, known as the Wasteful and Inappropriate Service Reduction (WISeR) Model, commenced this year and is slated to run through December 2031. Overseen by the Centers for Medicare and Medicaid Services (CMS), WISeR’s primary objective is to decrease unnecessary procedures and identify waste and fraud within Original Medicare.
The WISeR model integrates advanced technologies such as machine learning with human clinical review to evaluate services deemed potentially vulnerable to overuse, fraud, and abuse. Targeted procedures include, but are not limited to, skin and tissue substitutes, electrical nerve stimulator implants, and knee arthroscopy for knee osteoarthritis. The aim is to create a more efficient and fiscally responsible Medicare system by proactively flagging questionable claims.
The Medicare Landscape: Advantage vs. Original
The introduction of AI-driven prior authorization into Original Medicare marks a significant shift in federal healthcare policy. Historically, prior authorization has been extensively utilized in Medicare Advantage (MA) plans, which are privately run alternatives to the government’s traditional Original Medicare program. Medicare Advantage has seen explosive growth, now enrolling approximately 55 percent of all Medicare-eligible seniors and disabled individuals. Within MA, insurers issue millions of full or partial claim denials annually based on prior authorization criteria.
Federal government reports, including those issued by the HHS Office of Inspector General (OIG) in June 2026, have highlighted troubling patterns in Medicare Advantage. One OIG memorandum published in 2022 revealed that more than one in ten instances of Medicare Advantage plans denying beneficiaries’ access to services occurred even when those services apparently met coverage rules. While a substantial percentage of these denials are ultimately overturned upon appeal (for example, 81 percent of MA denials were overturned in 2024), the initial denial and subsequent appeal process create significant obstacles and delays for patients. Erecting such barriers to medically appropriate care is a particular area of concern, especially for vulnerable populations.
The expansion of AI-driven prior authorization into Original Medicare, where it has previously been rarely deployed, thus raises red flags for many. Critics fear that the challenges observed in Medicare Advantage – including delays, denials, and the administrative burden of appeals – could now proliferate within the traditional Medicare system, potentially compromising access to care for millions more beneficiaries.
Concerns Mount Over WISeR’s Implementation and Ethical Implications
Despite CMS’s stated goal that the WISeR model will "ensure timely and appropriate Medicare payment for select items and services," a growing chorus of critics views its implementation with skepticism. Wendell Potter, a prominent advocate for health insurance reform and a former Cigna executive, has extensively covered the political pushback against WISeR. Similarly, Zena Wolf, a researcher with the Center for Health & Democracy, has cited investigations by major news outlets like The Washington Post, KFF Health News, and The Seattle Times, suggesting that in its initial months, the WISeR model has already led to care delays and denials in some instances across the six pilot states. Even with automated processes, the model appears to impose a high administrative burden on healthcare providers, who must now contend with additional work associated with AI-generated denials.
A particularly contentious aspect of the WISeR model is its financial incentive structure. Vendors participating in the WISeR program, who are hired to carry out the AI-driven prior authorization, earn a share of what CMS terms "averted expenditures." This means these vendors potentially profit from rejecting care requests, creating a direct financial incentive to deny services. This structure reignites long-standing concerns about profit-making within the healthcare system that is based on discouraging or denying patients access to medically necessary care. This ethical quandary has not gone unnoticed by lawmakers, with several introducing resolutions and amendments to block funding for the WISeR model, citing potential threats to patient access.
A Paradoxical Stance: Administrative Contradictions
Adding another layer of complexity, the Trump administration appears to hold a seemingly contradictory stance regarding prior authorization. While CMS actively expands the use of AI in Original Medicare through WISeR, the agency simultaneously advocates for lessening and streamlining prior authorization requirements imposed by private insurers, including Medicare Advantage plans. CMS Administrator Mehmet Oz has publicly warned insurance company executives to ease the burden of prior authorization, threatening federal regulation if they fail to act voluntarily: "If you don’t do it yourselves, then we’re going to do it for you," he stated to the National News Desk.
In response, and possibly to preempt further executive action or legislative intervention, health plans have recently released data suggesting compliance with administration demands. An industry-based survey revealed an 11 percent decline in prior authorization requests between June 2025 and April 2026. However, the true impact of this reduction remains unclear, as it is unknown whether the corresponding denial rate has also decreased. Furthermore, while an industry group survey conducted last year affirmed that all responding health plans agreed that "AI or algorithms without clinician or practitioner review are not used to deny prior authorization requests that involve medical necessity or clinical considerations," and insurers pledged greater transparency around the clinical reasoning for prior authorization, skepticism persists.
Patient Impact: A Human Toll and Systemic Burden
Regardless of the degree to which AI is involved, the public consistently views prior authorization as a "major burden." A newly released Commonwealth Fund survey in June 2026 highlighted the profound impact of these denials. Roughly one in five American working-age adults with private insurance reported that either they or a family member were denied insurance coverage for physician-recommended medical care in 2025. The consequences of these denials are severe: 41 percent of individuals who experienced a prior authorization denial reported a delay in their care, and more than a quarter indicated that their health problem worsened as a direct result. NBC News has reported on patients "stuck in prior authorization purgatory," running "out of time or treatment options," underscoring the critical, sometimes life-threatening, nature of these delays.
The government and private insurers have attempted to implement improvements. The Biden administration, for instance, issued a rule in 2024 aimed at reducing delays for patients with government-run plans and streamlining the prior authorization process for physicians. This rule mandated that insurers make prior authorization decisions within 72 hours for urgent requests and seven calendar days for non-urgent requests, with these timeline requirements coming into effect on January 1 of this year for most public sector health plans. Last year, the Trump administration, in collaboration with insurers, also pledged to further streamline and accelerate prior authorization processes. Private insurance companies vowed to standardize electronic requests by 2027 and committed to "reduce the volume of medical services subject to prior authorization" by 2026, specifically citing common procedures such as colonoscopies and cataract surgeries. These efforts signify an acknowledgment of the systemic problems, but their efficacy in fundamentally transforming the patient experience remains to be fully seen.
Expert Perspectives and The Road Ahead
While industry assurances of human oversight and increased transparency may assuage some concerns about AI’s role, placating detractors will not be easy. Jared Dashevsky, a physician and founder of Healthcare Huddle, an educational platform, articulated a common sentiment among critics: AI has the potential to "eliminate barriers, reduce administrative waste, give us more time with patients. But that’s not what’s being built." Instead, he argues, what is emerging is an "arms race to deny faster and appeal faster. More automation of a broken system that shouldn’t exist in its current form."
This perspective underscores the fundamental tension at play: the desire for technological efficiency colliding with the imperative for compassionate, patient-centered care. The integration of AI into prior authorization represents a pivotal moment for healthcare. Its success hinges not merely on its ability to identify cost savings, but on its capacity to do so without compromising patient safety, delaying essential treatments, or further burdening an already strained healthcare system. The ongoing debate and the outcomes of pilot programs like WISeR will be crucial in determining whether artificial intelligence ultimately serves as a true solution to the prior authorization crisis or merely exacerbates its most troubling aspects. The challenge lies in harnessing AI’s power to serve human well-being, rather than allowing it to become another barrier to care.
