In recent years, artificial intelligence(AI),a branch of computer science based on deep learning and machine learning, has advanced rapidly in the screening and clinical management of ophthalmic diseases. Its application scope has gradually expanded from the posterior segment to the anterior segment of the eye. Automated detection and interpretation frameworks incorporating multimodal imaging modalities, including slit-lamp photography and anterior and posterior segment optical coherence tomography(OCT), have demonstrated considerable potential in the identification, early diagnosis, and clinical decision support of common anterior segment diseases such as keratitis, dry eye disease, pterygium, and glaucoma. As a fundamental instrument for anterior segment examination, the slit-lamp microscope remains indispensable in routine ophthalmic practice. This review summarizes recent progress in AI-assisted anterior segment research and discusses the prospects of integrating AI with slit-lamp imaging in clinical ophthalmology.