Rural Patients Skeptical of AI Healthcare Push Despite Federal Funding

Federal health officials are betting heavily on artificial intelligence to address healthcare challenges in rural America, but patients and researchers are questioning whether the technology can deliver on its promises.

Health Secretary Robert F. Kennedy Jr. has told senators that AI nurses can provide "concierge care" to rural patients, while CMS Administrator Mehmet Oz has advocated for "AI-based avatars" to connect rural communities with mental health services. State health leaders are following suit, directing portions of the $50 billion federal Rural Health Transformation Program toward AI expansion in rural health organizations.

Yet interviews with residents in Hot Springs, South Dakota—a city of 3,400 at the southern end of the Black Hills—reveal significant skepticism. "I get artificial intelligence for certain things, but for personal healthcare — no," said Tara Haffner, expressing concerns about AI errors and the importance of direct doctor-patient relationships.

The evidence gap

The enthusiasm for AI in rural healthcare far outpaces the research supporting it. According to a recent report from ARISE, a Stanford- and Harvard-led evaluation group, AI healthcare tools remain "poorly evaluated" with limited evidence they perform effectively outside controlled settings. Few studies track actual patient outcomes.

The situation is even more stark for rural applications. An academic review found only 26 peer-reviewed studies about AI in rural healthcare published between 2010 and April 2025, with few analyzing implementation or outcomes.

Qian Huang, an assistant professor at the Center for Rural Health and Research at East Tennessee State University, noted that most AI tools are tested at large academic hospitals using urban patient data. Rural patients face different health issues and obstacles—such as transportation barriers—that may not translate to urban-trained algorithms.

What states are funding

A review of state plans for the Rural Health Transformation Program shows interest in AI for administrative automation: medical charting, coding, referrals, and prior authorization requests. Some states are pursuing more ambitious applications, including AI that suggests diagnoses or treatment recommendations to clinicians.

Mississippi wants predictive algorithms to guide emergency medics with "triage, routing, and treatment decisions." Utah is exploring AI-powered prescription refill requests. Kentucky plans AI chatbots to "deliver personalized nudges and education" through gamified incentives.

Phillip Mues, who oversees technology at Cherry County Hospital and Clinic in Valentine, Nebraska, said AI scribes that record appointments and generate visit notes have helped reduce clinician burnout. Surveys show the technology lets providers maintain "eye contact on the patient, not the computer."

But Mues acknowledged AI's limitations: rural hospitals at risk of closing likely can't use AI to save enough money to prevent those outcomes.

Implementation challenges

Rural health facilities face unique obstacles in deploying AI. Many lack the hardware, IT staff, or fast internet connections required to support the technology. Clinicians already stretched thin may not have time for AI training. And patients may lack home internet access or comfort with the technology.

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

Hot Springs resident Stephanie Keller wears a smartwatch for fitness tracking but has no interest in an AI chatbot using her data for health coaching. "I don't have the time to chat with AI every day. I mean, are you kidding me?"

Measuring success

CMS spokesperson Timothy Foster said the agency has no AI-specific reporting requirements but is developing a form for states to report overall progress and outcomes. Many state applications mention tracking only adoption metrics—how many clinicians or patients use the technology—rather than health outcomes or time savings.

Some states are requiring more rigorous measurement. Connecticut will track how often AI-powered patient monitoring devices trigger accurate alerts. Texas will require cost savings reporting, while Wisconsin lists "patient outcomes" and "productivity and efficiencies" as possible metrics.

Abraham Pritzker of Julota, a healthcare data tracking company, said states should measure whether AI reduces falls, 911 calls, or hospital admissions rather than just usage rates.

Why it matters

The Rural Health Transformation Program represents one of the largest federal investments in rural healthcare infrastructure in recent history. How states deploy these resources—and whether they rigorously evaluate outcomes—will shape rural healthcare delivery for years to come. Without strong evidence and transparent reporting, rural health systems risk investing scarce resources in tools that may not address their most pressing challenges: staffing shortages, financial sustainability, and patient access to care.

The Congressional Republicans created the five-year program last summer as part of President Trump's One Big Beautiful Bill Act, intended to offset anticipated fallout in rural communities from legislation expected to reduce Medicaid spending by more than $900 billion over a decade.

This article is based on reporting by Arielle Zionts and Darius Tahir, originally published by KFF Health News.