Background: The integration of artificial intelligence (AI) into surgical education has introduced transformative tools to enhance training and assessment. This study aims to synthesise evidence on the applications, benefits, and challenges of AI in surgical education. Methods: A systematic search was conducted across PubMed, Embase, Scopus, and Web of Science for peer-reviewed studies published between January 2010 and December 2024. Search terms included "artificial intelligence," "surgical education," "machine learning," and "virtual reality." Eligibility criteria encompassed studies addressing AI applications in surgical training, including technical skill assessment, decision-making, and simulation-based education. Two independent reviewers screened titles, abstracts, and full texts, with discrepancies resolved by consensus. Data were extracted on study characteristics, AI methodologies, and outcomes, and results were synthesized narratively. Results: Thirty-eight studies met inclusion criteria, comprising randomised controlled trials, cohort studies, and technical reports. AI applications included automated performance analysis, adaptive learning systems, and virtual or augmented reality simulations. AI demonstrated effectiveness in providing objective skill assessments, personalized training pathways, and enhanced procedural competence. However, challenges such as model interpretability, data bias, and ethical concerns were frequently cited. Conclusions: AI offers significant potential to enhance surgical education by improving training precision and efficiency. However, its adoption requires addressing methodological and ethical barriers.