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Medicare just bet the farm on AI to fix prior authorizations.
On January 1, CMS quietly launched the most ambitious healthcare AI experiment in government history: the WISeR Model.
Six states, New Jersey, Ohio, Oklahoma, Texas, Arizona, and Washington, are now guinea pigs for an AI system that decides which Medicare services get approved.
Here’s what’s actually happening:
The government is using machine learning algorithms with human review to analyze prior authorization requests in real-time. The AI identifies potentially wasteful services, flags unusual patterns, and streamlines approvals for routine care.
Think about that for a second.
We’re handing over Medicare gatekeeping decisions to algorithms. The same prior authorization process that denies 2 million Medicare requests annually. The same process that delays cancer treatments, surgeries, and critical medications.
Now it’s powered by AI.
The irony? While 14 major health systems just dropped Medicare Advantage plans citing prior auth nightmares, CMS is doubling down on the very technology insurers use to deny care.
But here’s where it gets interesting:
CMS claims their AI is different. It includes mandatory human oversight. It focuses on reducing waste, not denying care. It promises to speed up approvals for legitimate services.
If this works, we could see authorization times drop from weeks to minutes. Physicians could get instant approvals for routine procedures. Patients could access care without bureaucratic delays.
If it fails? We’ve just automated Medicare denials at scale.
The six-year pilot runs through 2031. That’s 70 million Medicare beneficiaries watching to see if AI becomes their advocate or adversary.
The real question isn’t whether AI can manage prior authorizations.
It’s whether we trust algorithms to decide who gets care.
♻️ Repost if AI should enhance healthcare decisions, not replace human judgment
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Author:
Jonathan Govette is a seasoned healthcare and technology executive with more than two decades of experience building, scaling, and advising digital health companies. He is the Co-Founder and CEO of Oatmeal Health, an AI-driven Lung Cancer Screening and Diagnostics company focused on expanding access to early detection for underrepresented populations, particularly patients served by Federally Qualified Health Centers and value-based health plans.
With a background in engineering, product development, and strategic partnerships, Jonathan has founded and led multiple health technology ventures across clinical care delivery, regulated medical software, and AI-enabled diagnostics. His work sits at the intersection of medicine, technology, and health equity, with a consistent focus on translating complex clinical problems into scalable, real-world solutions.
Jonathan has spent much of his professional life dedicated to improving outcomes for marginalized and underserved communities. He has designed and implemented frameworks that align clinical quality, reimbursement, and technology to sustainably advance health equity at scale. This mission is deeply personal and informs his leadership philosophy and long-term vision for healthcare transformation.
In addition to his operating experience, Jonathan is an author and long-time writer in the healthcare domain, with over 20 years of published work covering digital health, medical innovation, and healthcare systems. He is a frequent mentor to early-stage founders and regularly advises startups on product strategy, partnerships, and go-to-market execution in regulated healthcare environments.
Before entering industry full-time, Jonathan nearly pursued a career in medicine with an early path toward cardiothoracic surgery, an experience that continues to shape his clinical perspective and respect for frontline care delivery.
CEO | Oatmeal Health | AI Lung Cancer Startup | Engineer | Writer | Almost Became a Doctor (Cardiac Thoracic Surgeon) | 3x Health Tech Founder | Startup Mentor | Follow to share what I’ve learned along the way.
