AI-Enabled automated feedback and debriefing in simulation-based healthcare education: a systematic review of educational effectiveness

Artificial intelligence is integrated into healthcare simulation to deliver individualized feedback and support reflective learning. Educational evaluations include procedural coaching, virtual patient encounters, and facilitator development. This review examined educational effectiveness while distinguishing observed performance from perceived competence and feedback feasibility. Original research published to May 2026 evaluating artificial intelligence enabled feedback or debriefing in healthcare simulation was reviewed. Comparative educational studies and complementary feedback validation or feasibility investigations were synthesized narratively. Outcomes included technical performance, clinical reasoning, communication, perceived competence, cognitive workload, and debriefing utility. Ten original reports comprised seven randomized trials and three prospective, pilot, or qualitative investigations. Surgical trials show improvements in selected performance measures, with benefits dependent on feedback timing, instructional design, and human participation. Personalized expert instruction informed by artificial intelligence exceeded artificial intelligence tutoring alone in practice and transfer tasks. Virtual patient feedback improved clinical reasoning in a small trial, while nursing simulations demonstrated gains in communication and perceived competence. Artificial intelligence enabled feedback offers benefits for simulation outcomes. Data for autonomous team debriefing is less developed than data for individualized coaching. Integration with educators, independent assessment, and longitudinal evaluation provides the strongest direction for educational implementation.