When it comes to medicine, Washington, D.C., is not anti-AI. In a string of recent legislative announcements, the White House has made AI innovation a national priority. The U.S. Department of Health and Human Services (HHS) is exploring strategies to accelerate AI in clinical care. And the FDA has already authorized more than 1,500 AI-enabled medical devices.

But these efforts, similar to the approach taken by the private sector, have focused solely on advancing AI for clinicians, hospitals, and health systems.

What Congress and federal agencies have not embraced is the larger opportunity outside the walls of medicine: empowering patients with medical expertise through the same general-purpose AI tools they are already using today.

The medical potential of consumer AI

An estimated 133 million Americans currently use generative AI, and half of U.S. adults (67 million) are relying on these tools to answer health-related questions. Patients are asking large language models like ChatGPT, Claude, and Gemini about their symptoms, medications, lab results, chronic diseases, and whether they need to see a doctor.

A recent study in Nature Medicine explains why these patient-facing AI models deserve more attention from the federal government.

Researchers compared two specialized, physician-facing AI tools (OpenEvidence and UpToDate Expert AI) with three widely available, low-cost large language models (from OpenAI, Anthropic, and Google).

The result? General-purpose consumer AI models performed as well as or better than the tools built specifically for doctors and hospitals. That finding challenges the assumption that progress in medical AI depends on developing primarily specialized applications for clinical use. It does not. The tools needed to empower patients already exist as general-purpose large language models on their phones.

To accelerate that shift, government needs to help all Americans access these LLMs and apply the expertise they offer to maintain and improve their health.

The opportunity to improve America’s health

If American medicine were achieving superb outcomes, a cautious and more institutional approach to GenAI might make sense. But with 400,000 people dying annually from misdiagnosis, 250,000 from preventable medical error, and at least half a million from poorly controlled chronic disease, the quickest path to saving lives and making healthcare more affordable is to help patients use the AI tools already accessible to them.

Although dozens of AI applications are possible, two opportunities would produce the greatest improvements in patient health.

First, conditions such as diabetes, hypertension, depression, and asthma affect 75% of Americans and are poorly managed. Less than half of patients with hypertension have their blood pressure under control, and an even smaller percentage of patients with diabetes have their blood sugar effectively controlled. Based on data from the CDC, successful control of these chronic conditions could reduce the number of heart attacks, strokes, and kidney failures by as much as 50%. Doing so would save hundreds of thousands of lives and reduce medical costs by hundreds of billions of dollars.

Patients could use generative AI to analyze daily clinical data and alert them when their blood pressure or blood glucose is not responding as expected, allowing for earlier medication changes. And the same tools could also reassure patients when everything is going according to plan and help avoid unnecessary visits.

In addition, these same large language models could guide patients at night, on weekends or during the long wait for a primary care or specialty appointment. A worried parent whose child spikes a fever at night should have a better option than guessing, searching social media, or deciding alone whether to go to the ER versus waiting for the pediatrician’s office to open the next day. That same expert guidance should be available to adults trying to decide whether an aging parent’s new symptom requires immediate urgent care.

The role for the federal government

Assuming inexpensive LLMs perform as well as expensive medical AI tools, elected officials and federal agencies should expand access to them. In addition, they should create educational resources that help individuals and families use these tools reliably and safely.

This approach will be most valuable for the tens of millions of Americans who have difficulty accessing medical care, particularly those living in inner cities and rural communities.

To make access to medical expertise easier, Congress and governors should legislate funding to increase availability of these large language models in homes, libraries, community centers, senior centers, and public-health clinics. With access as the foundation for patient empowerment, NIH and HHS should then create plain-language educational tools that teach people how to enter medical information, write clearer prompts, ask follow-up questions, and recognize when a problem requires urgent medical attention.

The goal of patient empowerment would not be to replace clinicians. It would be to fill in the cracks between office visits and reduce the risks of medical errors and clinical complications before they arise.

If chronic diseases were well controlled, medical errors were rare, and clinical access was easily available at night and on weekends, caution and the incremental introduction of GenAI might make sense. But that is not the reality for tens of millions of Americans today.

With healthcare becoming harder to access and increasingly unaffordable, large language models like ChatGPT, Claude, and Gemini can help millions of Americans protect and improve their health. That should matter to elected officials and regulatory agencies. Encouraging the use of technology already available on people’s phones and in their homes would be an effective place to start.

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Robert Pearl, the author of “ChatGPT, MD,” teaches at both the Stanford University School of Medicine and the Stanford Graduate School of Business. He is a former CEO of The Permanente Medical Group.

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