In gene editing, CRISPR-Cas9 has revolutionized the field and led to advancements such as base editing and prime editing. This decade's most significant advancement was the creative convergence of these technologies with artificial intelligence (AI) techniques, particularly deep learning and large language models. The goal of this comprehensive review article is to review the key aspects of accelerated integration, including how to design sgRNA, predict off-target effects, engineer Cas proteins, and discover new genomic editors designed with generative artificial intelligence. In addition, it explores practical therapeutic applications, including regulatory-approved treatments like Casgevy for sickle cell anemia, as well as the ethical and regulatory issues related to this convergence. Accumulating evidence suggests that AI is no longer merely an aid but a fundamental pillar in the entire gene editing development cycle, with promising prospects for virtual cell models and the complete automation of gene editing experiments.