The administrative burden of clinical documentation contributes to #healthcare practitioner burnout and diverts valuable time away from direct #patient care. Ambient artificial intelligence (#AI) (AI) scribes, also called #digital scribes or AI scribes, are emerging as one promising solution, given their potential to automate clinical note generation and reduce clinician workload. Ambient AI scribes, specifically those built on a large language model (LLM), are emerging as one technology to facilitate real-time clinical documentation tasks. This potentially transformative development has a foundation on longer-standing AI-based transcription software, which use automated speech recognition and/or natural language processing. Recent studies have highlighted the potential impact of ambient AI scribes on clinician well-being, workflow efficiency, documentation quality, user experience, and #patient interaction. Limited evidence so far indicates that ambient AI scribes are associated with reduced clinician burnout, lower cognitive task load, and significant time savings in documentation, particularly in after-hours #ehr (EHR) work. One consistently reported benefit is the improvement in the #patient-physician interaction, as physicians feel more present during a clinical encounter. However, these benefits are counterbalanced by persisting concerns regarding the accuracy, consistency, language use, and style of AI-generated notes. Studies noting errors, omissions, or hallucinations, caution that diligent clinician oversight will be necessary. The user experience is also heterogeneous, with benefits varying by specialty and individual workflow. Also, there are concerns about ethical and legal issues, algorithmic bias, the potential for long-term "cognitive debt" from over-reliance on AI, and even the potential loss of physician autonomy. Additional pragmatic concerns include security, privacy, integration and interoperability, user acceptance and training, and the cost-effectiveness of adoption at scale. Finally, limited studies describe adoption or evaluations of these technologies by non-physician clinicians and #health professionals. While ambient AI scribes and AI-driven documentation technologies are promising as a potentially practice-changing tool, there are many questions remaining. Key issues persist, including responsible deployment with the goal of ensuring ambient AI scribes produce clinical documentation that supports more efficient, equitable, and #patient-centered care. To advance our collective understanding and address key issues, JMIR #medical #informatics is launching a call for papers for a new section on “Ambient AI Scribes and AI-driven Documentation Technologies.” As editors, we look forward to the opportunity to advance the science and understanding of these fields through publishing high-quality and rigorous scholarly work in this new section of JMIR #medical #informatics.