Surgical education faces challenges such as limited clinical experience, inconsistent teaching quality, and risks to patient safety during training. Artificial intelligence-based educational technologies (AIET) promise to improve the effectiveness and personalization of training, but there is virtually no data on the use of such technologies in surgical education for students in Central Asia. The aim of this study was to evaluate the impact of the first implementation of an AI-based learning system in an educational institution on the theoretical knowledge, practical skills, and satisfaction of surgical students at Samarkand State Medical University. This prospective randomized controlled trial (parallel-group design), conducted among the 120 fourth-year medical students. Participants were randomized into an AI-based training group (n = 60) or a control group receiving traditional training (n = 60). A 12-week intervention. Standardized multiple-choice tests, objective structured clinical examinations (OSCE), and student satisfaction questionnaire. Statistical tests were used to compare pre- and post-intervention outcomes within each group and between groups. The AI group demonstrated significantly higher results in theoretical and clinical skills compared to the control group (p < 0.001). After the intervention, OSCE results were significantly higher in clinical reasoning and decision-making stations. Students` satisfaction levels were significantly higher in the AI group. The use of AI-assisted learning improved educational outcomes in surgical training. These results show that AI is a viable and useful addition to existing surgical education.