Hospitals and academic health centres across Ohio are increasing their use of artificial intelligence to support patient care, research and clinical operations. The shift reflects growing interest in AI-enabled healthcare delivery.
At The Ohio State University, the launch of the AI(X) Hub has strengthened the institution’s role in artificial intelligence research and application. The initiative brings together experts from 15 colleges and includes a dedicated focus on AI for health. Biomedical informatics professors Xia Ning and Raghu Machiraju co-lead the effort. The program aims to translate AI research into real-world healthcare use and accelerate biomedical innovation. It also seeks to train future clinicians and researchers in applied AI. Ohio State plans to hire 100 faculty members over the next five years to support the initiative.
Clinical adoption is also expanding across the state. Cleveland Clinic is rolling out Bayesian Health’s AI-enabled clinical intelligence platform across its U.S. hospitals, including those in Ohio. The system analyzes patient data in real time to support earlier detection and treatment of sepsis, a leading cause of in-hospital death. Pilot programs showed earlier alerts, fewer false alarms and improved identification of sepsis cases.
In Cincinnati, Bon Secours Mercy Health has launched “Catherine,” a conversational AI-powered digital assistant. The tool helps patients with knee, hip and shoulder pain find appropriate care. Developed through the system’s digital transformation arm, the platform uses clinician-reviewed data. It focuses on patient engagement outside traditional care settings.
Community health systems are also testing AI, though challenges remain. Summa Health, based in Akron, piloted an AI tool to predict sepsis risk in emergency departments. While leaders reported promising results, they also cited implementation challenges. These included workflow integration and alert fatigue.
The moves in Ohio mirror a broader trend across the healthcare sector. Health systems are testing AI to address staffing pressures, streamline workflows and improve care delivery. At the same time, they continue to navigate governance, oversight and patient safety as AI becomes more embedded in healthcare.
