Two-thirds of Epic hospitals have adopted ambient AI tools

Ambient AI tools for clinical documentation have been linked to reduced administrative burden, increased efficiency and cost savings, driving widespread adoption. A new study from the American Journal of Managed Care found that nearly two-thirds of U.S. hospitals using Epic EHR systems had adopted ambient AI tools by June 2025, underscoring the rapid adoption of AI technologies in hospital settings. 

Researchers studied a national sample of U.S. hospitals using Epic to identify hospital characteristics associated with adoption. Among more than 6,500 hospitals, 42.4% were Epic users, and 62.6% of those Epic users had adopted ambient AI. The study linked adoption data to hospital characteristics from the American Hospital Association annual survey to understand what factors were linked to adoption.  

The results showed that adoption increased across staffing-adjusted workload quartiles and among hospitals in the top operating margin quartiles.  

Adoption was also higher among metropolitan hospitals (64.7%) compared to nonmetropolitan hospitals (54.3%). Additionally, adoption was lower in the Midwest (54.9%) compared to the South (69.5%). Researchers observed no significant differences for the Northeast or the West. 

Nonprofit hospitals had the highest adoption probability, at 70.2%, followed by government hospitals at 45% and for-profit hospitals at 28.8%.  

The three most commonly adopted tools among the Epic hospitals in the study were DAX Copilot, Abridge and ThinkAndor. Together, these three tools accounted for more than 80% of all AI implementations among hospitals using Epic, the study noted. 

"Most existing evidence on ambient AI has focused on short-term, clinician-centered outcomes such as documentation time, after-hours work, and perceived burden," the study stated.  

"Additional studies are needed to evaluate downstream effects on care processes and patient outcomes, as well as to identify potential unintended consequences (eg, documentation quality, equity, safety). If ambient AI improves clinician efficiency and care quality, uneven adoption could contribute to widening differences in performance and outcomes across hospitals." 

The researchers suggested that additional studies and, potentially, policy interventions are needed to support equitable adoption and ensure that financially constrained hospitals can reap the benefits of these tools as much as larger hospitals with more financial resources. 

Jill Hughes has covered healthcare cybersecurity and privacy news since 2021.