Recent multisite research reveals that artificial intelligence-enabled ambient documentation tools, known as AI scribes, are associated with modest reductions in electronic health record and documentation time for clinicians. However, the study found these tools do not significantly impact the amount of time spent charting outside of normal work hours.
In Plain English: The Clinical Takeaway
- What AI Scribes Do: AI-enabled ambient documentation tools.
- The Time Saved: A study across five health systems showed clinicians saved 13.4 minutes of EHR time and 16.0 minutes charting.
- The Catch: The saved time is often immediately redirected to other patient care tasks, meaning after-hours documentation remains largely unchanged.
Quantifying the Time Saved in Electronic Health Records
Documentation burden remains a source of physician burnout. To evaluate whether emerging technology alleviates this pressure, researchers analyzed the performance of AI scribes deployed in ambulatory settings. Lisa Rotenstein, MD, from the University of California San Francisco, along with colleagues, reported findings in JAMA showing that a difference-in-differences evaluation of medical professionals across five major health networks connected the use of AI scribes to 13.4 fewer minutes on electronic health records (EHR) (95% CI 9.1-17.7) and 16.0 fewer minutes spent charting (95% CI 13.7-18.3).
The investigation utilized data collected between June 2023 and August 2025 across five academic health centers. Participating clinicians used Epic as their electronic health record vendor alongside software tools such as Ambience, Nuance DAX Copilot, and Abridge. Out of 8,581 total clinicians included in the review, 1,809 chose to utilize the AI scribes while 6,772 opted not to use them. Nearly three-quarters of the cohort consisted of attending physicians (74.1%), while 18.1% were advanced practice clinicians and 7.8% were resident physicians.
Despite these documented efficiencies, the analysis highlighted a persistent challenge. Using AI scribes did not significantly alter the volume of time clinicians spent interacting with the electronic health record outside of regular working hours. Rotenstein explained that when clinicians saved time on documentation, they likely reallocated that to other patient care tasks—messages, chart review, corresponding with other team members, etc.
Who Benefits Most from Ambient Documentation Tools?
| Clinician Subgroup | Observed Benefit of AI Scribes | Study Context |
|---|---|---|
| Primary Care Specialists | Saw more benefit | Comprises 24.4% of the overall study cohort |
| Advanced Practice Clinicians | Saw more benefit | Comprises 18.1% of the clinician population |
| Female Clinicians | Saw more benefit | Part of multisite difference-in-differences analysis |
| High-Frequency Users | Saw more benefit | Used AI scribes in half or more of their visits |
Primary care specialists, advanced practice clinicians, female professionals, and those who incorporated AI scribes into half or more of their appointments were among the specific subsets identified by the research as gaining greater advantages from the technology. In addition, further exploratory evaluations revealed that the time reclaimed from documentation enabled 0.49 more weekly patient visits—amounting to roughly one extra patient every 2 weeks—which translated to approximately $167.37 in monthly supplemental revenue.
Previous research from this study group found that AI scribes reduced burnout and improved well-being. Rotenstein pointed out that these combined results imply AI scribes offer a modest improvement in time spent, yet exert a meaningful influence on clinicians’ perceptions of that time investment. In an accompanying editorial, Vincent Liu, MD, of the Kaiser Permanente Division of Research in Pleasanton, California, and co-editorialists emphasized that this study solidifies that AI scribes can reduce documentation time. Yet, they pointed out that the subsequent issue is whether those saved hours get redirected toward activities that demonstrably enhance patient outcomes and health equity.
Future Trajectory and Training Implications
Liu and his team additionally pointed out that an “AI-native” cohort of providers will emerge in the near future, having interacted with the medical field exclusively alongside these technologies. They argue that future work should assess these trainees’ clinical reasoning, documentation quality, skills acquisition, and supervision.
Disclaimer: This article is for informational purposes only and does not constitute formal medical or administrative advice.
