Artificial intelligence technologies are playing an increasingly important role in the diagnosis, treatment, and patient management of gynecological cancers. Early diagnosis, accurate staging, and the development of personalized treatment plans are of great importance for patients’ survival and quality of life in cervical, ovarian, and endometrial cancers. Machine learning and deep learning-based systems support clinical decision-making processes by jointly evaluating radiological images, histopathological data, genomic analyses, and electronic health records. In particular, it is noted that artificial intelligence applications used in Pap smears and HPV screenings for cervical cancer improve diagnostic accuracy, reduce false-negative results, and ensure standardization in screening processes. In ovarian cancer, radiomic analyses make it possible to detect the disease at an early stage and assess prognosis. In endometrial cancer, the combined use of molecular classification systems and AI-supported analyses contributes to the development of personalized treatment approaches.  In addition, digital pathology, AI-powered imaging systems, and robotic surgery applications offer significant advantages in diagnostic evaluation, treatment planning, and improving surgical precision. Furthermore, it is emphasized that AI technologies can be effectively utilized in areas such as psychosocial support, quality of life management, and remote patient monitoring. However, it is noted that issues such as data security, ethical concerns, and algorithmic bias must be carefully evaluated.