The integration of Artificial Intelligence (AI) and Large Language Models (LLMs) into simulation-based education is transforming healthcare training by enhancing scalability, adaptability, and accessibility. AI‑driven technologies, including LLMs such as GPT models, enable the creation of dynamic, realistic scenarios and personalized learning experiences, offering learners real-time feedback and tailored pathways. These advancements optimize skill development in communication, diagnostic reasoning, and decision-making.

Applications of AI and LLMs in simulation include automated debriefing systems that analyze performance and provide individualized insights, virtual patients for realistic conversational training, and culturally sensitive scenario generation by adapting content to diverse demographics. AI-driven analytics further enable educators to refine curricula based on learner performance trends, addressing specific gaps.

While these technologies hold immense promise, challenges such as ethical concerns, algorithmic bias, and data security require attention. This abstract explores the transformative potential and challenges of AI and LLMs in simulation‑based education, emphasizing their role in advancing healthcare outcomes globally.