The narrative review Artificial Intelligence and Gynecologic Surgery explores the role of artificial intelligence in obstetrics and gynecology, especially regarding surgeries. AI has shown early benefits in reproductive endocrinology for its diagnostics, imaging analysis, and predicting outcomes such as fertility and pregnancy complications. In gynecologic surgery, particularly robotic-assisted surgery, AI provides a way to interpret the datasets generated before, during, and after surgery. Applications include preoperative planning, intra-operative guidance, skills assessment, and outcome prediction.  Additionally machine learning models, including deep learning and natural language processing, have been used to enhance diagnoses, predict complications, and analyze surgical performance. Emerging tools are promising, especially for improving anatomic recognition, intra-operative safety, and efficiency. These advances also have implications for surgical education, allowing objective, data-driven training.  Nonetheless, some limitations must be taken into account. Concerns about transparency, explainability, and algorithmic bias continue to generate skepticism among clinicians. Hence, larger standardized datasets and explainable AI systems are needed to ensure safety, trust, and clinical applicability. Overall, AI represents a transformative but still early-stage tool for advancing this field of medicine.