Artificial Intelligence to Support Debriefing in Simulation-based Healthcare Education: A Scoping Review

Background : Artificial intelligence (AI) is increasingly being integrated into healthcare education, including simulation-based education. While AI applications in simulation are expanding, its role in supporting the debriefing phase of simulation remains relatively underexplored and inconsistently described in the literature. Therefore, this review aimed to map and synthesise the existing literature on the use of artificial intelligence to support debriefing in simulation-based education. Methods : A scoping review was conducted in accordance with Arksey and O’Malley’s framework and Joanna Briggs Institute guidance and reported in line with PRISMA-ScR. Searches were conducted across MEDLINE, Scopus, Web of Science, and CINAHL without date restrictions. Eligible studies examined the use of artificial intelligence to support debriefing within simulation. Data were charted using a structured extraction form and synthesised descriptively and thematically. Results : Seven studies published between 2023 and 2026 met the inclusion criteria. Studies were conducted in the United States (n = 3), Switzerland (n = 2), Chile (n = 1), and South Korea (n = 1). AI applications clustered into three primary domains: (1) communication and performance analytics using speech recognition and natural language processing, (2) generative AI systems supporting facilitator feedback and structured report generation, and (3) learner-facing AI-driven reflective dialogue models. These findings suggest that artificial intelligence in simulation debriefing can be understood as functioning across three interrelated roles: as an analytical observer, a cognitive scaffold for facilitators, and a reflective partner for learners. Reported outcomes primarily focused on feasibility, usability, and perceived educational value, with limited evidence of objective performance improvement. Across studies, artificial intelligence was primarily used as a supportive tool alongside facilitators rather than replacing the role of the human facilitator. Conclusions : Artificial intelligence is emerging as a supportive tool for debriefing in simulation-based healthcare education, but evidence remains limited and largely single-institutional. This review offers a conceptual understanding of AI’s role in augmenting, rather than replacing, human facilitation. While AI shows promise for enhancing the structure, objectivity, and scalability of debriefing, further rigorous research is needed to evaluate effectiveness, address ethical considerations, and guide implementation.