October 20, 2025
2 min read
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Every medical innovation is usually met with both some excitement and some appropriate skepticism.
If someone today introduced a nonsurgical treatment for appendectomy, many general surgeons would find every reason to criticize it. But I’ve long been a believer that if it’s good for the patient, it’s good for both the doctor and the industry.
Today, AI’s entrance into medicine is facing a very mixed audience, but many doctors probably don’t recognize the measured way this group of technologies is likely to enter our field. Based on what we now know, I suspect there will be three phases of the transformation of medicine by AI.
The early days of AI in medicine are happening now and will continue over the next couple of years. AI scribes and workflow tools are already producing efficiency improvements that are most welcome. We now have AI screening systems for mammograms, skin lesions and ocular fundus photos that already take away some low complexity volume from specialists and allow primary and ancillary care providers to do more. I view this mostly as a positive for specialists, allowing us to serve an exploding older population by working at our highest level of capability rather than performing mundane diagnostics, although this will eventually put downward pressure on already low reimbursement.
Over the next 4 to 7 years, we’ll see the emergence of more personalized treatment powered by AI, using large data models to predict outcomes based on information that today we don’t even consider. Surgical systems will have greater autonomy to determine their own settings for better safety based on preoperative data and intraoperative events. Again, specialists may see fewer patients, with primary care providers or others diagnosing disease earlier and potentially performing more surgical tasks. Patients will expect AI integration of practices, putting pressure on those slow to adopt. And a real risk exists of the deskilling of new doctors who may struggle to combine disparate medical information into a cohesive diagnosis
The deepest integration of AI in medicine will probably take place in 8 to 10 years. Even skeptics will at least accept the role of adjunctive AI in diagnosis and medical planning. Robotic systems will assist or complete many procedures autonomously, with patients forced to accept that even AI decision trees and robots can make choices that lead to complications. Malpractice will be harder to prove when doctors using AI have the protection of a “second opinion” that will newly define the standard of care.
Health systems will fully embrace home-based monitoring and remote patient management for common diseases. Large software companies, whose names we currently know and don’t know, will unify recordkeeping and allow unprecedented patient access and ownership of their information as well as interoperability between specialties and platforms. Many doctors may be reduced to proceduralists. Rural health care will advance because connectivity, not the presence of doctors, will determine access to care. Sadly, many will still choose not to access care. In urban and suburban settings, I suspect a robust concierge’s medicine sector will also emerge, although corporatization of this industry may also undermine physician independence.
At a high level, this rising tide of AI in medicine will slowly raise outcomes for those doctors who evolve to cooperate rather than compete with its inevitable role. Eric Shinseki said, “If you dislike change, you’re going to dislike irrelevance even more.” Indeed, the next 100 years will be marked by much more change in medicine than the last. Most of us will likely practice long enough to see dramatic changes, and most of us eventually will probably tout them as the most important advancement we have witnessed.
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For more information:
John A. Hovanesian, MD, FACS, an ophthalmologist specializing in cataract, refractive and corneal surgery at Harvard Eye Associates in Laguna Hills, California, can be reached at drhovanesian@harvardeye.com.
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Disclosures:
Hovanesian reports consulting, investing or having board relationships in several companies with AI offerings.
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