The landscape of healthcare in the United States is perennially marked by the struggle between cost containment and patient access to necessary medical care. At the heart of this tension lies prior authorization, a bureaucratic hurdle that, while intended to ensure medical necessity and curb wasteful spending, has frequently become a source of profound frustration and delayed care for millions of Americans. In an ambitious and controversial move, the government is now piloting a program that integrates artificial intelligence (AI) into this fraught process, raising critical questions about whether this technological leap will streamline approvals or merely automate denials, exacerbating an already tortuous system.
The Enduring Challenge of Prior Authorization
Prior authorization (PA) is a requirement from health insurance companies for patients or their providers to obtain approval for a prescribed medication, medical procedure, or service before it is rendered. Its stated purpose is multi-faceted: to act as a crucial check on overuse, to ensure that recommended treatments are medically necessary, and to guide patients towards less costly, equally effective alternatives when available. By preventing unnecessary procedures and medications, insurers aim to control healthcare costs and improve the quality of care by ensuring appropriateness.
However, the practical application of prior authorization has long been a source of significant contention. Patients and their loved ones often recount harrowing personal stories of navigating complex administrative labyrinths to gain pre-approval for physician-recommended care. These tribulations frequently involve prolonged waits, extensive paperwork, and repeated appeals, often at critical junctures in their health journeys.
Physicians, too, are vocal critics. A large majority express concerns about the administrative burden and, more critically, the detrimental impact of care delays on patient outcomes. The American Medical Association (AMA) has consistently highlighted that these delays can lead to patients abandoning recommended treatments while awaiting insurer verification of eligibility and medical necessity. For instance, a 2025 AMA survey of physicians revealed widespread dissatisfaction, with doctors spending an average of 14 hours per week on prior authorization tasks, diverting valuable time away from direct patient care. The survey also indicated that 94% of physicians reported care delays due due to prior authorization, and 80% believed that prior authorization sometimes led to patients abandoning treatment altogether.
The stakes for patients are high. Those who are denied care can submit an appeal, but this process demands additional time and effort, which many, especially those with acute or rapidly progressing conditions, simply cannot afford. Federal reports from agencies like the HHS Office of Inspector General (OIG) have further illuminated the systemic issues. For example, reports issued in June of the current year (referring to the article’s implied publication date of late 2025/early 2026) documented instances where Medicare Advantage plans—the privately run alternative to original Medicare—denied requests for essential services like skilled nursing and rehabilitation admissions, even when they appeared to meet coverage rules. These findings underscore a significant concern: the erection of obstacles to medically appropriate care.
The public views prior authorization as a major burden. A KFF Health Tracking Poll indicated that prior authorizations rank as one of the public’s biggest frustrations in accessing healthcare. In Medicare Advantage, which now covers roughly 55% of Medicare-eligible seniors and disabled individuals, insurers issue millions of full or partial claim denials annually based on prior authorization decisions. A Commonwealth Fund survey released in June 2025 found that approximately one in five working-age adults with private insurance reported that they or a family member had been denied coverage for physician-recommended medical care that year. Alarmingly, 41% of those who experienced a prior authorization denial reported delayed care, and over a quarter stated that their health problem worsened as a direct result.
The Promise and Perils of AI Integration
Against this backdrop of systemic inefficiencies and patient suffering, the advent of artificial intelligence offers a tantalizing, albeit controversial, potential solution. AI, with its capacity to rapidly sort through and analyze vast quantities of information, could theoretically expedite the approval of unambiguously allowable claims. By automating routine decisions and flagging complex cases for human review, AI promises to reduce the administrative burden on providers and accelerate access to care for patients. Proponents envision a future where AI algorithms efficiently cross-reference patient data with clinical guidelines, insurance policies, and medical literature, leading to faster, more consistent, and potentially more equitable decisions.
However, the integration of AI into prior authorization is far from universally embraced. Significant resistance stems from the fear that AI-driven systems could increase wrongful denials of health insurance coverage. The same 2025 American Medical Association survey that highlighted physician concerns about existing PA processes also revealed profound skepticism regarding AI’s application. A substantial 61% of doctors worried that AI would exacerbate denials of treatments they deemed medically necessary. Critics argue that while AI is excellent at pattern recognition and data processing, it lacks the nuanced clinical judgment and empathy required for complex medical decisions. The potential for algorithms to be biased or to misinterpret individual patient circumstances is a major ethical concern.
Health policy analysts echo these sentiments. Camm Epstein, in an email to Undark, articulated a widely held view: "AI should be used to make appropriate care easier to approve, not necessary care easier to deny." This statement encapsulates the core tension surrounding AI in healthcare – whether it will serve as a benevolent assistant or an inscrutable gatekeeper.
The WISeR Model: A Federal Experiment with AI
In an effort to harness AI’s potential while addressing the inefficiencies of the current system, the Trump administration launched a significant demonstration project this year: the Wasteful and Inappropriate Service Reduction Model, or WISeR. This initiative, spearheaded by the Centers for Medicare and Medicaid Services (CMS), aims to reduce waste and fraud in Original Medicare, targeting unnecessary procedures. The WISeR project, slated to run through December 2031, is currently being piloted in six states.
The model combines advanced technologies, including machine learning, with human clinical review to evaluate services that CMS believes may be vulnerable to overuse, fraud, and abuse. Specific areas under scrutiny include skin and tissue substitutes, electrical nerve stimulator implants, and knee arthroscopy for knee osteoarthritis. The integration of AI into Original Medicare’s prior authorization process represents a notable shift, as PA has historically been less extensively deployed in Original Medicare compared to Medicare Advantage plans.
While CMS asserts that the WISeR model will "ensure timely and appropriate Medicare payment for select items and services," critics contend that this shift might not ultimately benefit patients. Wendell Potter, a prominent advocate for health insurance reform and a former Cigna executive, covered the political pushback against WISeR on his Substack publication, "HEALTH CARE un-covered." In the same publication, Zena Wolf, a researcher with the Center for Health & Democracy, cited investigations by leading news outlets such as The Washington Post, KFF Health News, and The Seattle Times, which suggested that in the initial months of its operation, the WISeR model has already caused care delays and denials in some instances across the six pilot states. Furthermore, despite the promise of automated processes, healthcare providers in these states report a high administrative burden due to additional work dealing with denials, effectively shifting the workload rather than eliminating it.
A particularly contentious aspect of the WISeR model is its financial incentive structure. Vendors participating in the program, hired to carry out AI-driven prior authorization, earn a share of what CMS refers to as "averted expenditures." This payment model creates a direct financial incentive for vendors to deny care requests, leading to profound ethical concerns. Critics argue this mechanism exacerbates long-standing worries about profit-making derived from discouraging patients from receiving medically necessary care. Several lawmakers have reacted strongly, introducing resolutions and amendments to block funding for the WISeR model, citing potential threats to patient access.
A Paradoxical Policy Landscape
Compounding the complexity is the Trump administration’s seemingly contradictory stance on prior authorization. While CMS is actively expanding the use of AI in Original Medicare through WISeR, the administration has simultaneously advocated for lessening and streamlining PA requirements for private insurers, including Medicare Advantage plans. CMS Administrator Mehmet Oz has publicly warned insurance company executives that they must ease the burden of prior authorization, or the federal government would impose stringent regulations, stating, "If you don’t do it yourselves, then we’re going to do it for you." This dual approach highlights the administration’s struggle to balance cost control with patient access and provider burden.
In response to governmental pressure and to preempt further executive branch action or legislative intervention, health plans have recently released data suggesting a degree of compliance with administrative demands. An industry-based survey revealed that between June 2025 and April 2026, requests for prior authorization declined by 11 percent. However, the true impact of this reduction remains unclear, as it is unknown whether the rate of denials has also decreased. Critics argue that a reduction in requests does not necessarily equate to improved patient access or reduced administrative burden if the denial rate for remaining requests remains high or even increases.
In a survey conducted last year, all responding health plans agreed with the statement that "AI or algorithms without clinician or practitioner review are not used to deny prior authorization requests that involve medical necessity or clinical considerations." Insurers have also pledged greater transparency regarding the clinical reasoning underpinning their prior authorization decisions. These assurances are intended to alleviate some of the widespread worry about a lack of human review in AI-driven decisions. However, placating detractors, particularly those concerned about the inherent opacity and potential for bias in algorithms, will not be an easy task.
Ethical Implications and the Path Forward
The debate surrounding AI in prior authorization transcends mere efficiency; it delves into fundamental ethical considerations regarding transparency, accountability, and the very nature of patient care. The OIG memorandum published in 2022, which pointed to numerous instances where Medicare Advantage plans denied services despite apparent coverage rules (though 81% of these denials were overturned upon appeal in 2024), underscores the existing fallibility of the system AI is intended to improve. The question then becomes whether AI will enhance human decision-making or simply automate its flaws, potentially at a much larger scale.
The call for more transparency regarding AI algorithms is critical. Without understanding how these systems arrive at their conclusions, it is impossible to audit them for bias, errors, or ethical breaches. The profit motive embedded in models like WISeR, where vendors benefit from "averted expenditures," introduces a dangerous conflict of interest that could prioritize financial gain over patient well-being.
As Jared Dashevsky, a physician and founder of Healthcare Huddle, succinctly put it, AI "could 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."
The future of prior authorization, with or without AI, remains a complex and hotly debated topic. While AI holds genuine promise for streamlining administrative tasks and identifying clear cases of medical necessity, its deployment in sensitive areas like healthcare coverage decisions demands rigorous oversight, unwavering ethical guidelines, and a steadfast commitment to patient-centric care. Without these safeguards, the very technology intended to fix a broken system risks making it even more opaque, more frustrating, and ultimately, more detrimental to the health and well-being of those it is meant to serve. The unfolding story of AI in prior authorization will undoubtedly shape the future of healthcare access for years to come.
