Rural and critical access hospitals cannot afford AI adoption, falling further behind well-funded health systems

Rural and critical access hospitals have less than 50% adoption of basic predictive AI tools compared to 86% adoption at top-tier hospital systems, creating a widening gap in care quality and operational efficiency. These under-resourced hospitals lack the capital, technical expertise, and vendor relationships to implement AI solutions, while the cost of staying behind compounds annually. Current enterprise AI solutions are priced for large health systems, leaving smaller hospitals unable to compete or improve patient outcomes.