Rural patients skeptical as federal officials promote AI healthcare

Federal health officials are championing artificial intelligence as a solution to rural America's healthcare crisis, but the people living in those communities aren't convinced the technology will address their most pressing needs.

Health Secretary Robert F. Kennedy Jr. has told senators that AI nurses can deliver "concierge care" to rural patients, while Centers for Medicare & Medicaid Services administrator Mehmet Oz suggested "AI-based avatars" could connect rural residents to mental health services. State health leaders are now deploying portions of the $50 billion Rural Health Transformation Program—created last year as part of President Trump's One Big Beautiful Bill Act—to expand AI adoption among rural health organizations.

Yet interviews with residents in Hot Springs, South Dakota, a city of 3,400 at the southern edge of the Black Hills, reveal deep reservations about replacing human healthcare workers with algorithms.

"I get artificial intelligence for certain things, but for personal healthcare—no," Tara Haffner told reporters outside the American Legion. She expressed concern about AI errors and wanted healthcare decisions to remain between her and her doctor.

Why it matters

The federal government is making a massive bet on AI to shore up struggling rural health systems at the same time it's cutting Medicaid spending by more than $900 billion over a decade. If AI tools fail to deliver measurable improvements in patient outcomes or access to care, rural communities could be left worse off—with fewer resources and unproven technology replacing human clinicians.

The evidence gap

Researchers have documented surprisingly little proof that AI can improve rural healthcare. A recent academic paper found only 26 peer-reviewed studies about AI in rural healthcare settings published between 2010 and April 2025, and few examined actual implementation or patient outcomes.

A report from ARISE, a Stanford- and Harvard-led evaluation group, concluded that healthcare AI tools remain "poorly evaluated" despite rapid industry adoption. While some AI has succeeded in controlled research environments, evidence of real-world performance is scarce, and few studies track what happens to patients.

Qian Huang, an assistant professor at the Center for Rural Health and Research at East Tennessee State University, noted that most AI healthcare tools are tested at large academic hospitals using data from urban patients. Those populations face different health challenges and barriers than rural patients, who may lack reliable transportation or high-speed internet access.

What states are funding

State applications for Rural Health Transformation Program funding reveal plans to deploy AI across a wide range of healthcare functions. Most states are focusing on automating administrative tasks like medical charting, coding, referrals, and prior authorization requests.

Some states are pursuing more ambitious applications. Mississippi wants AI algorithms to guide emergency medics on triage and treatment decisions. North Dakota plans to use AI to detect early signs of chronic disease and behavioral health conditions. Kentucky will explore AI chatbots that deliver "personalized nudges and education" through health coaching and gamified incentives.

Phillip Mues, who oversees technology at Cherry County Hospital and Clinic in Valentine, Nebraska, said AI scribes that record appointments and generate clinical notes have helped reduce clinician burnout. Surveys show the technology lets providers maintain eye contact with patients instead of staring at computers. However, Mues acknowledged AI can't solve every problem—rural hospitals at risk of closing likely can't save enough money through AI to prevent closure.

Implementation challenges ahead

Rural health facilities face significant barriers to deploying AI effectively. Many lack the hardware, IT staff, or high-speed internet connections required to support sophisticated AI tools. Clinicians already stretched thin may not have time for training, and patients may lack home internet access or comfort with technology.

"In rural communities, trust and a personal relationship is essential," Huang said.

CMS spokesperson Timothy Foster said the agency has no AI-specific reporting requirements but is developing a form for states to report overall progress. Many state applications mention tracking only adoption metrics—how many clinicians or patients use the technology—rather than measuring whether AI actually improves care, reduces costs, or saves time.

Some states are requiring outcome measurement. Connecticut will track whether AI-powered patient monitoring devices trigger accurate alerts. Texas will require cost savings reports, while Wisconsin plans to measure patient outcomes and productivity gains.

Huang emphasized that states must share their results so other jurisdictions can learn from successes and failures. "We do not have a lot of resources to waste on tools that don't work in rural areas," she said.

These details were first reported by KFF Health News.