The Impact of Ambient AI on Resident Documentation and Well-Being: A Pilot Study

Introduction: Burnout among family medicine residents remains a significant challenge, often exacerbated by electronic health record (EHR) documentation burden.1 Emerging technologies such as ambient artificial intelligence (AI), may reduce clinical documentation time while simultaneously enhancing work satisfaction. We looked to evaluate the impact of ambient AI on resident well-being, satisfaction, and documentation time. Methods: This prospective pilot study was conducted at two community-based family medicine residency programs. Sixteen third-year residents were invited to participate in the study. Residents used ambient AI software for outpatient clinical documentation. Pre- and postintervention data included objective EHR usage metrics and well-being assessments using the Mini ReZ survey. Primary outcomes included subjective well-being, changes in documentation time per patient, and total EHR time. Results: Fifteen residents enrolled in the study and 13 completed pre/postsurveys. The documentation time per patient decreased significantly postintervention (−3.09 min, P = .002). The overall EHR time also decreased though not significantly (P = .760). Survey data showed a significant improvement in the total Mini ReZ score (P = .012; Holm-adjusted P = .037), and improvements in subscales related to work pace/EHR stress (P = .0032; Holm-adjusted P = .013) and resident experience (P = 0.024; Holm-adjusted P = .048). Conclusion: The use of ambient AI software in a family medicine resident population was associated with improved well-being, satisfaction, and documentation efficiency. This study indicates that a larger study focused on resident efficiency and subsequent satisfaction is warranted.