Blab AI
AI Adoption Grows Nationwide, but Rural Hospitals Lag Behind
Across the United States, artificial intelligence is moving from buzzword to business staple, yet the technology’s reach feels uneven when the eye is turned to rural hospitals. A 2024 McKinsey & Company survey found that more than 70 % of organizations now deploy AI, up from roughly 50 % in 2023. In the health sector, the American Medical Association (AMA) recorded a doubling of physician AI adoption—from 38 % in 2023 to 66 % in 2024—while the majority of U.S. hospitals report using AI tools in some capacity.
But a 2025 study from the University of Minnesota reveals a stark divide between urban and rural facilities. Led by Professor Brian Whitacre of Oklahoma State University, the research examined survey data that asked hospitals whether they use AI for scheduling, treatment recommendation, health monitoring, billing simplification, and other functions.
The study found that only about half of rural hospitals reported AI use, compared with over 80 % of urban facilities. Because the data represent the first year AI use was surveyed, the study could not establish a trend.
Whitacre noted that the survey’s snapshot limits insight into how AI adoption changes over time. He highlighted several factors that appear to influence whether a rural hospital adopts AI. Hospitals that belong to a larger system are more likely to use AI, and those in better financial health are also inclined to adopt. Conversely, independent or financially weaker rural hospitals are much less likely to implement AI.
Mercy Hospital in Ada, Oklahoma, illustrates how system affiliation can support AI integration. The hospital is part of the Mercy Healthcare System, and Chief Medical Officer Dr. Benjamin Lynch explained that the system provides resources that an independent rural hospital might not have. Mercy works with data scientists and clinicians to vet AI tools before, during, and after implementation.
The hospital uses AI to streamline patient information sharing, suggest possible diagnoses, analyze CT scans and X‑rays for urgent findings, and record patient data. It is also developing AI for early detection of chronic conditions such as diabetes and cancer. Lynch emphasized that Mercy’s goal is to improve efficiency, speed, and quality of care while keeping clinicians in control.
Whitacre has called for targeted investment to help rural hospitals that lack the funds to evaluate and integrate AI. He pointed to the new Rural Health Transformation Program, which promotes AI use in rural healthcare but does not provide guidelines on appropriate applications or evaluation methods.
According to Whitacre, hospitals with limited resources need help understanding what AI use should look like for them and how to ensure the technology is appropriate for their patients. The study’s preliminary results suggest that financial stability and system affiliation are key drivers of AI adoption in rural settings.
Whitacre plans to expand his research to track how AI affects rural hospitals’ efficiency and financial performance over multiple years. As AI adoption continues to rise across the United States, the gap between urban and rural hospitals remains a critical issue.
The findings underscore the need for clear guidance, financial support, and collaborative frameworks to help rural facilities harness AI’s potential without compromising patient care or community employment. For more information or to collaborate on the research, Brian Whitacre can be reached at brian.whitacre@okstate.edu or 405‑744‑9825.
But a 2025 study from the University of Minnesota reveals a stark divide between urban and rural facilities. Led by Professor Brian Whitacre of Oklahoma State University, the research examined survey data that asked hospitals whether they use AI for scheduling, treatment recommendation, health monitoring, billing simplification, and other functions.
The study found that only about half of rural hospitals reported AI use, compared with over 80 % of urban facilities. Because the data represent the first year AI use was surveyed, the study could not establish a trend.
Whitacre noted that the survey’s snapshot limits insight into how AI adoption changes over time. He highlighted several factors that appear to influence whether a rural hospital adopts AI. Hospitals that belong to a larger system are more likely to use AI, and those in better financial health are also inclined to adopt. Conversely, independent or financially weaker rural hospitals are much less likely to implement AI.
Mercy Hospital in Ada, Oklahoma, illustrates how system affiliation can support AI integration. The hospital is part of the Mercy Healthcare System, and Chief Medical Officer Dr. Benjamin Lynch explained that the system provides resources that an independent rural hospital might not have. Mercy works with data scientists and clinicians to vet AI tools before, during, and after implementation.
The hospital uses AI to streamline patient information sharing, suggest possible diagnoses, analyze CT scans and X‑rays for urgent findings, and record patient data. It is also developing AI for early detection of chronic conditions such as diabetes and cancer. Lynch emphasized that Mercy’s goal is to improve efficiency, speed, and quality of care while keeping clinicians in control.
Whitacre has called for targeted investment to help rural hospitals that lack the funds to evaluate and integrate AI. He pointed to the new Rural Health Transformation Program, which promotes AI use in rural healthcare but does not provide guidelines on appropriate applications or evaluation methods.
According to Whitacre, hospitals with limited resources need help understanding what AI use should look like for them and how to ensure the technology is appropriate for their patients. The study’s preliminary results suggest that financial stability and system affiliation are key drivers of AI adoption in rural settings.
Whitacre plans to expand his research to track how AI affects rural hospitals’ efficiency and financial performance over multiple years. As AI adoption continues to rise across the United States, the gap between urban and rural hospitals remains a critical issue.
The findings underscore the need for clear guidance, financial support, and collaborative frameworks to help rural facilities harness AI’s potential without compromising patient care or community employment. For more information or to collaborate on the research, Brian Whitacre can be reached at brian.whitacre@okstate.edu or 405‑744‑9825.
