Early gastrointestinal cancer (EGC) has subtle early symptoms and low screening rates, which leads to most patients being diagnosed at advanced stages, resulting in poor prognoses. Therefore, early diagnosis and timely treatment are crucial for improving patient outcomes. In recent years, artificial intelligence (AI) technology has been able to enhance the detection rate and diagnostic accuracy of early lesions through high-precision image analysis and data processing, thereby achieving early discovery, early diagnosis, and early treatment to improve patient prognoses. However, AI also faces challenges such as insufficient training data, algorithm bias, and uneven development across regions, which need to be addressed in future advancements. This review aims to provide a comprehensive overview of the current applications of AI in the diagnosis and treatment of EGC, exploring its advantages, challenges, and future directions to offer valuable references for researchers and clinicians in related fields.