
Specialty Pharmacy's Next AI Opportunity: Geeta Nayyar, MD, MBA
Key Takeaways
- AI value is concentrated in reducing administrative burden—prior authorization, billing, and documentation—rather than transforming the doctor-patient clinical encounter in the near term.
- Specialty pharmacy and managed care can realize early gains by applying AI to operational workflows that currently consume pharmacist time with repetitive, manual tasks.
Geeta Nayyar, MD, MBA, says AI's real health care payoff is cutting administrative friction with clean data and clinical leadership.
Artificial intelligence’s (AI's) real value in health care today isn't in dazzling clinical breakthroughs—it’s in clearing away administrative friction: prior authorization, billing, and the paperwork surrounding every doctor-patient visit, said Geeta Nayyar, MD, MBA, a leading physician-technologist, investor, and author of the bestseller Dead Wrong: Diagnosing and Treating Healthcare's Misinformation Illness, in an interview with The American Journal of Managed Care® (AJMC®).
Nayyar spoke with AJMC ahead of her appearance at the
This interview was edited for clarity.
AJMC: Could you give a high-level overview of what you're covering in your keynote and what you hope attendees take away from it?
Nayyar: We're going to be talking about health care, technology, and the future, and attendees really should walk away with an understanding of the trends that are shaping the industry, have shaped them to date, and are shaping the future. But they should also be able to walk away with some tactful tips as to how to appreciate and approach the future.
AJMC: Where are you seeing AI deliver value in health care right now versus where it's more hype than substance?
Nayyar: We get lost in the hype, and we're too busy boiling the ocean, as opposed to really focusing on the friction points in health care, which are actually relatively simple. There are things on the administrative side that can really make a difference in care, but we are too often focused on clinical care and what happens between doctor and patient, when the reality is most of the friction in the health care system is not coming from the doctor-patient visit. It's coming from everything surrounding it: prior authorization, administrative burden, the bill—all of these sorts of things.
AJMC: For managed organizations and specialty pharmacy, what's the biggest opportunity you see for AI adoption in the next couple of years?
Nayyar: The biggest thing that needs to happen on the pharmacy side is operational efficiency. There are so many manual tasks that we're having our pharmacists do that could really be solved by so much of this technology. It's really the operations side.
AJMC: What are the risks or blind spots you think health care leaders aren't paying enough attention to as they adopt AI tools?
Nayyar: The biggest problem we have is that we have data silos, and we know that AI is only as good as the data we give it. But to date, we don't share a lot of data. The data in the electronic health record is incorrect most of the time. We have amazing 3D AI MRI scanners, but if you don't bring your disc back to the doctor, they don't have a way to read that or access it. It's that we continue to have data silos. The fax machine is alive and well, and AI is not going to be able to action any of that data.
AJMC: Lastly, what would you tell a chief medical office or medical director who's cautious about AI and unsure where to start?
Nayyar: Clinical leadership—you have to have clinical leadership from the get. What's the problem you're trying to solve? How is the staff going to be affected, workflow-wise? But really, [ask] your clinical leaders: what are the problems of the day? What is it that gives the staff and the doctor-patient relationship the most friction? [Start] with those problems, but [lead] with clinical leadership throughout the entire process, not just at the end.
References
- Weber E, Burnaska K, Bowman R, Holvey S. AI in health care: closing the revenue cycle gap. Am J Manag Care. 2025;31(4):161-162. doi:10.37765/ajmc.2025.89717
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