The rate of AI adoption in hospitals is clearly rising across multiple fronts. A February 2025 AMA survey found that 66% of physicians reported using health‑care AI in 2024—a 78% increase from 38% in 2023. While precise figures vary, industry surveys indicate that around 46% of U.S. hospitals currently use AI in revenue cycle management, and 98% of healthcare leaders expect pervasive AI adoption in that domain within three years.
The following are recent AI implementation announcements from leading IDNs:
Connecticut Health Systems and Yale New Haven – AI to Manage ER Crowding
Connecticut Children’s Hospital and Yale New Haven Health’s innovation arm have deployed a cloud-based AI model that predicts emergency department demand using variables like weather patterns. The system optimizes staffing levels to ease ER crowding—part of a broader statewide AI healthcare initiative
Duke Health – AI Safety & Performance Monitoring Framework
Researchers at Duke University unveiled a brand-new framework to assess and monitor AI tools used in clinical workflows like medical note‑taking and drafting responses within Epic. They've begun piloting it within Duke Health this month, with plans to scale it across other systems—tackling inaccuracies and enhancing care quality.
Intermountain Health – Tackling Clinical Data
Layer Health, a leading artificial intelligence (AI) company in healthcare, announced a strategic collaboration with Intermountain Health. The collaboration includes a strategic investment from Intermountain Ventures, Intermountain’s innovation and venture capital arm, as well as a multi-year initiative to deploy the Layer Health AI platform across multiple clinical registries to improve accuracy, efficiency and scalability of clinical data abstraction. Intermountain’s Clinical Data Management team will first work with Layer Health to validate the AI’s ability to achieve high accuracy prior to deployment, ensuring the AI meets clinical performance standards required to support real-world clinical registry reporting.
RWJBarnabas Health (NJ) – AI for Early Surgical Infection Detection
RWJBarnabas Health announced it is piloting an AI tool that analyzes OR footage and patient-submitted wound photos post-discharge. The aim: detect early signs of surgical site infections and alert clinicians to intervene sooner.
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