The incorporation of artificial intelligence (AI) in medical education has revolutionized traditional teaching methodologies by enhancing learning efficiency and knowledge retention. This study investigates the effectiveness of AI-assisted learning in medical education through a randomized controlled trial. A total of 240 medical students were randomly assigned to an AI-assisted learning group (n=120) or a conventional teaching group (n=120). AI-assisted learning was implemented using an adaptive AI-based platform integrating real-time feedback, case-based simulations, and interactive modules. The primary outcome measure was the improvement in test scores assessed through a standardized pre-test and post-test evaluation. The AI-assisted group demonstrated a statistically significant improvement in mean test scores (pre-test: 62.3±8.4, post-test: 87.6±6.1, p<0.001) compared to the conventional group (pre-test: 61.8±7.9, post-test: 79.2±7.3, p<0.001). Student engagement and satisfaction levels were significantly higher in the AI-assisted cohort (p=0.003). These findings indicate that AI-assisted learning significantly enhances knowledge acquisition, engagement, and performance in medical students. The study presents new evidence supporting AI-driven educational paradigms, emphasizing their role in modernizing medical curricula. Future studies should explore AI’s long-term impact on clinical decision-making and critical thinking skills.