What hospital leaders are learning from real-world AI use

Rural hospitals are navigating a familiar reality: limited staffing, thin margins, and growing administrative demands, all while maintaining access to care for their communities. Rather than rehashing these challenges, a recent NRHA educational session focused on something more actionable: what rural leaders are actually doing today to support clinicians and reduce burnout using artificial intelligence (AI).

The session featured operational and clinical leaders from two rural hospitals: Pat Songer, COO and chief of EMS at Cascade Medical in Washington, and Athena Minor, RN, chief nursing and clinical officer at Ohio County Healthcare in Kentucky. Moderated by physician and health care entrepreneur Yair Saperstein, the discussion centered on practical lessons from evaluating, implementing, and driving adoption of AI tools in real rural health care settings.

Together the panelists offered a grounded look at what works, what takes time, and what rural hospitals should prioritize as they consider AI adoption.

Moving past the hype: What AI means in practice

Throughout the discussion, panelists emphasized that AI adoption in rural health care is not about sweeping transformation or replacing clinicians. Instead, it is about reducing unnecessary cognitive and administrative burden so care teams can focus on patient care.

In practical terms, this means applying AI to tasks such as documentation, charting, and ordering — areas that consume time but do not require a clinician’s full expertise. When integrated thoughtfully into existing workflows, these tools can improve care and operational outcomes in a way clinicians love.

For rural hospitals, the value of AI lies not in novelty, but in its ability to fit seamlessly into daily practice.

How rural hospitals are using AI today

Both Cascade Medical and Ohio County Healthcare described ambient listening technology as their entry point into AI-enabled workflows.

At Ohio County Healthcare, Minor shared that while the organization had experience with advanced technologies such as surgical robotics, ambient listening addressed a more immediate and universal challenge: documentation burden. Supporting clinical notes in real time helped reduce after-hours charting and allowed clinicians to remain present with patients rather than focused on screens.

Songer described a similar experience at Cascade Medical. Ambient listening improved patient experience by enabling providers to maintain eye contact and engage more fully during visits. What initially served as a documentation support tool quickly became a meaningful driver of provider satisfaction and patient trust.

In both organizations, AI was positioned as a support to clinical expertise — not a replacement — which proved essential for acceptance.

Implementation: Governance first, adoption follows

A recurring theme was that successful implementation depended on trust, transparency, and governance.

At Cascade Medical, early concerns centered on privacy, HIPAA compliance, and patient consent. Establishing clear policies and guardrails required upfront effort, but once those foundations were in place, clinicians were eager to participate. Adoption spread organically as providers shared their experiences with colleagues.

Ohio County Healthcare faced similar skepticism, particularly among long-tenured clinicians who were concerned about losing control over documentation. Minor noted that once providers experienced improved note quality, reduced charting time, and smoother workflows, resistance faded. Early adopters became internal champions, helping normalize the technology across the organization.

Both leaders emphasized that adoption was never forced. Allowing clinicians to experience the benefits firsthand proved far more effective than mandates.

Measuring success beyond traditional ROI

When asked how they measure impact, both panelists challenged the idea that AI success should be evaluated solely through traditional financial metrics.

While fiscal responsibility remains critical for rural hospitals, Songer explained that improvements in work-life balance and provider satisfaction led to organic gains in productivity without pressure to increase volume. Clinicians who regained time and focus were more willing and able to accommodate patient needs when appropriate.

Minor shared a similar perspective. Even during an electronic health record transition — a period that often reduces productivity — providers using AI-supported documentation were able to maintain efficiency and documentation quality. For leadership, the return was evident not only in operational performance, but also in morale, retention, and patient experience.

Choosing AI tools that fit rural reality

Selecting the right technology proved just as important as implementation.

Minor noted that many AI solutions are designed for large systems and fail to account for rural constraints. Her team prioritized tools that were affordable, scalable, and built with direct clinical input. Solutions that required extensive IT resources or rigid, all-or-nothing contracts were not viable.

Songer highlighted the importance of relationships and adaptability. Rural hospitals often lack layers of decision-making infrastructure, making it essential to work with partners who understand local needs and can adjust accordingly. Flexibility and fit rather than feature breadth were decisive factors.

Advice for rural leaders beginning their AI journey

In closing, the panelists offered guidance rooted in lived experience rather than theory.

Songer encouraged rural leaders not to fear AI, noting that small hospitals are often more agile than larger systems and well positioned to lead innovation when tools are chosen thoughtfully. He also emphasized AI’s potential to improve quality and patient safety through more complete, consistent documentation.

Minor emphasized that adoption was strongest when clinicians understood how the tools fit into existing workflows and felt confident that patient interactions and documentation remained under their control. Clear processes and ongoing communication helped build trust, allowing adoption to spread organically rather than through mandates.

Across both perspectives, transparency, communication, and clinician trust emerged as the foundation for success.

Watch the full educational session

To hear directly from rural hospital leaders and explore these insights in more depth, readers can access the on-demand NRHA educational session Thriving in the AI Era: Strategies for Leveraging AI to Reduce Costs & Burnout.

NRHA adapted the above piece from AvoMD, a trusted NRHA partner, for publication within the Association’s Rural Health Voices blog.
 

Yair Saperstein, MD MPH, is the CEO and co-founder of Avo and a practicing internal medicine physician with experience supporting care teams in underserved and resource-limited hospitals. His work focuses on building practical, workflow-aligned clinical tools that reduce burden and support clinicians in rural and community health care settings.