Artificial Intelligence (AI) is transforming medical education globally, offering solutions to challenges such as resource limitations and limited clinical exposure. However, its integration in resource-constrained settings like Palestine remains underexplored. This study evaluates the prevalence, impact, and challenges of AI use among Palestinian medical students, focusing on academic performance, clinical competence, and research productivity. A cross-sectional study was conducted among 590 medical students from Palestinian universities. Data were collected using a validated electronic questionnaire, covering demographics, AI usage patterns, and perceived impacts across academic, clinical, and research domains. Initial analysis was conducted using AI tools, specifically ChatGPT, to facilitate insights and structure the results effectively. Statistical analyses were performed using IBM SPSS v27 to validate findings. Statistical significance was set at p < 0.05. The draft underwent detailed reviews by the research team to confirm accuracy and validity. AI adoption was high, with 87% of students frequently using tools like ChatGPT (76%) and virtual simulators (26%). Students reported significant improvements in academic performance (mean score: 4.2, SD = 0.7) and research productivity (mean score: 4.5, SD = 0.6), particularly in literature reviews and data analysis. Clinical competence received moderate ratings (mean score: 3.6, SD = 0.8), reflecting AI's limited role in practical skill development. Time management was highly rated (mean score: 4.6, SD = 0.5), highlighting AI's ability to automate repetitive tasks. Challenges included ethical concerns, data accuracy, and limited AI literacy, with 91% lacking formal AI training. AI demonstrates significant potential to enhance medical education in resource-constrained settings by improving academic outcomes and research efficiency. ChatGPT played a critical role in this study, not only as a tool used by participants but also in the research process itself, including data analysis and manuscript drafting. These findings were cross-verified using SPSS to ensure robustness. Despite its promise, limitations in practical clinical applications and technical understanding highlight the need for targeted AI literacy programs and ethical guidelines. This study underscores the importance of integrating AI into medical curricula to address existing gaps and maximize its benefits in similar global contexts.