Algorithmic systems based on artificial intelligence(AI)and machine learning(ML)have undergone rapid advancement in recent years, demonstrating extensive application across diverse ophthalmic disorders. Owing to the public availability of multiple global databases, significant progress has been achieved in the training and development of AI-integrated algorithms utilizing multimodal ophthalmic imaging modalities, including fundus photography and optical coherence tomography(OCT). These advancements have established a foundation for precision medicine and efficient healthcare delivery. The diagnosis of macular diseases relies on the identification of subtle alterations in tissue anatomy, where AI demonstrated exceptional performance in detecting intraocular biomarkers and evaluating anatomical changes during disease progression, with particularly prominent utility in the field of macular pathologies. This article provides a comprehensive review of the current applications of AI in macular diseases, aiming to synthesize existing research achievements and current challenges, while proposing visionary prospects for the broader implementation of AI in ophthalmology and even systemic medicine in the future.