Ghanshyam S. Yadav, M.D., and Christopher A. Longhurst, M.D., M.S.
Electronic health records (EHRs) have become nearly universal in the United States, enhancing care coordination and patient access to health data. However, these advancements have introduced numerous challenges for providers and health care systems. This editorial explores the potential of artificial intelligence (AI) to enhance EHR efficiency, focusing on recent advancements in machine learning-based message classification and AI-generated clinical documentation. A recent study has demonstrated that AI-driven message routing can significantly reduce response times and streamline workflows. Similarly, AI-generated draft responses and ambient AI scribes offer promising, albeit mixed, results in alleviating administrative burdens. While AI holds immense potential to reduce administrative inefficiencies and improve clinician experience, its success hinges on robust infrastructure, transparency with patients, and continuous iteration to align with evolving clinical workflows. Strategic investments and thoughtful integration will be crucial in realizing AI’s full impact on EHR efficiency.