Health care in America is broken. We have an aging population that requires complex, ongoing care. We have rising costs. We have a workforce of clinicians who burned out. We don’t have enough clinicians. Today, the average wait time to schedule a new physician appointment in a major U.S. city is 31 days.
That is an entire month of waiting. For a patient managing a chronic condition, a 31-day wait is not just an inconvenience. It is the difference between catching a complication early and ending up in the emergency room. It is an access crisis. If patients cannot get in the door, the quality of care inside the building does not matter.
Recently, artificial intelligence (AI) has been pitched as the ultimate fix. This has split the health care industry into two extremes.
On one side, you have the skeptics. They want to ban AI. They point to data privacy risks, the fear of automated decision-making, and the liability of getting it wrong. On the other side, you have the evangelists. They view AI as solving every problem (while also likely getting us to massive unemployment). They believe it will rapidly transform every aspect of medicine and overhaul traditional care models overnight.
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Neither camp is right.
The true power of AI in health care lies in the middle ground. AI is not here to replace doctors. The nuances of human biology, the empathy required in a clinical setting, and the trust built in a doctor-patient relationship cannot be replicated by code. AI must be viewed strictly as an enabler. Its job is to empower doctors to see more patients safely, tackling that 31-day wait time head-on.
To see how this works, look at how physicians spend their time today. They are drowning in paperwork. The electronic health record (EHR) was supposed to modernize medicine. Instead, it turned highly trained medical professionals into data-entry clerks. Doctors spend hours every evening charting notes. This administrative bloat drives burnout, which worsens the clinician shortage.
This is where AI can make an immediate impact. By using background tools like ambient listening, AI can securely draft clinical notes and organize patient histories. It sits quietly in the background. The doctor no longer has to stare at a screen while a patient is talking. They reclaim hours of lost time every week. When doctors spend less time clicking boxes, they have more time to practice medicine. They can open up more schedule slots. They can see more patients without adding to their own stress.
Take chronic disease management, for example. Conditions like cardiovascular disease require consistent monitoring and timely adjustments to care plans. A 31-day delay to see a specialist means a patient might be living with worsening symptoms without medical guidance. By the time they finally get into the exam room, their condition may have deteriorated significantly.
If an administrative AI tool allows that same specialist to clear their backlog and see the patient in 7 days instead of 31, the clinical trajectory changes entirely. The AI didn’t diagnose the patient. The AI didn’t prescribe the medication. The AI simply removed the friction that was keeping the patient and the doctor apart.
When we build clinical capacity through these administrative efficiencies, we directly solve the access problem. By using AI to streamline the clinical workflow, we get patients in front of doctors faster. Faster access leads to earlier diagnoses. Earlier diagnoses naturally translate into better patient outcomes. The equation is straightforward: enable the doctor, improve access, elevate the outcome.
But recognizing this potential is not the same as achieving it. Not everyone trusts AI at this stage, and frankly, they shouldn’t.
Health care deals with human lives, not consumer software. The tech industry mantra of “move fast and break things” has no place in medicine. If we move too fast with AI, we risk alienating the patients and providers we are trying to help.
Integrating AI into medicine requires a step-wise process. We cannot jump straight to automated treatment plans or diagnostic algorithms. We have to start with the low-risk, high-friction areas of health care. Automating back-office operations, streamlining patient scheduling, and handling the EHR burden are the right first steps. These applications do not interfere with clinical judgment. They support it.
By successfully implementing AI in these operational areas, we prove its value. We build trust over time. Once physicians experience the relief of a lighter workload, the skepticism begins to fade. Once patients experience faster access to care, the fear of the technology diminishes.
We cannot afford to ignore new tools, but we cannot afford to deploy them recklessly. AI is not a magic solution. It is simply a powerful administrative tool. If we focus on the middle ground (using AI to clear bureaucratic hurdles, reduce burnout, and enable physicians to do what they do best), we can dismantle the access barriers holding our system back. It is time to stop debating whether AI belongs in health care and start using it to let doctors be doctors again.
Harry DiFrancesco is a health care executive.
