With each passing year, healthcare grows more expensive and less accessible. New technologies could slow—or even reverse—that trend. Artificial Intelligence can expand access, lower costs, and improve quality, but only if lawmakers don’t block its path. Precautionary regulations are piling up, stifling innovation and leaving AI tools subject to a patchwork of inconsistent restrictions. What’s needed is a clear, outcomes-focused framework that lets healthcare providers deploy AI tools already proven to match or exceed human capabilities. Patients and clinicians should have more choices, not fewer.
Thirty states have enacted laws regulating AI in healthcare. Most of these rules fall into three categories: limits on AI in processing insurance claims, mandates that patients be told when they are interacting with AI, and restrictions on how AI may be used clinically.
Transparency, especially in insurance claims processing, is important to maintain patients’ trust. But AI’s clinical applications offer the greatest potential to improve lives. In just a few years, AI enabled healthcare has moved from science fiction into a reality in which computers often match—or outperform—human clinicians in diagnostics and enhance the care they provide. That is exactly why well-intentioned but poorly informed legislation poses such a risk.
The potential benefits of AI in healthcare are substantial and will be measured in both quality of life and lives saved. Studies show that AI systems already outperform physicians in several diagnostic fields. One recent analysis found that AI was roughly four times more likely than doctors to arrive at the correct diagnosis in challenging cases. Other research shows AI can achieve expert-level accuracy in cancer detection and is better at identifying optimal diagnosis and treatment recommendations due to superior adherence to medical guidelines and more consideration of patient histories.
Many states provide guidelines for AI to be used more broadly in medical diagnosis and treatment. For example, in Texas if a licensed professional reviews the results and AI doesn’t make any final clinical decisions, it is essentially considered another tool at a doctor’s disposal. Texas has the closest example of an ideal model—permissive enough to encourage use and innovation while preserving professional oversight.
These capabilities are especially powerful in rural areas that struggle to attract and retain specialists and even primary-care physicians. Though it should be noted that even Texas’ laws would prevent AI from filling in for the lack of specialists in rural areas—as the AI tool must fall into the doctor’s particular field. To make full use of the diagnostic potential of AI in the region that needs it the most, general practitioners will need access to AI diagnostic tools from a variety of specialties.
AI can also cut administrative costs, reduce readmissions at hospitals, improve patient monitoring, as well as enhance telehealth, diagnostics and predictive analytics. Rural hospitals have been shutting down for years; AI could help keep more open by lowering operating costs while improving outcomes and access. While AI handling administrative tasks helps with doctor burnout in urban areas, in rural ones it can also be a financial lifeline for a hospital.
But the benefits extend far beyond rural America. Counsel Health, an AI enabled primary-care platform, claims its model allows clinicians to handle about 15 patient visits an hour, compared with the usual three or four. That kind of efficiency matters nationwide as physician shortages deepen. AI gives clinicians the tools to care for more patients without compromising quality.
Lawmakers should not stand in the way of a technological leap that could save lives. Regulators must shift from micromanaging AI tools to setting outcome-based, clear standards that protect patients while allowing innovation to flourish. The choice is simple: embrace AI as a force multiplier for strained healthcare systems or let outdated rules deny patients the care they need.
