Ovarian cancer, with its high fatality rate, continues to pose a major challenge in cancer treatment, primarily because it is often diagnosed at advanced stages and there are no dependable methods for early detection. Current diagnostic approaches, such as imaging and biomarker analysis, often time consuming to provide the necessary specificity and sensitivity, leading to delayed interventions. Artificial Intelligence (AI), utilizing advanced Machine Learning (ML) and Deep Learning (DL) techniques, is transforming the diagnosis and prognosis of ovarian cancer. This overview examines the significant impact of AI in boosting early detection, increasing diagnostic accuracy, and personalizing treatment approaches. AIdriven algorithms, especially Convolutional Neural Networks (CNNs), have demonstrated great potential in processing complex medical data, such as imaging, genomic information, and clinical records. In early detection, AI integrates biomarkers such as CA-125 levels with imaging findings to stratify patients into risk categories, minimizing false positives and negatives. In diagnostic imaging, AI enhances the interpretation of ultrasound, CT, and MRI scans by identifying subtle features that distinguish malignant from benign masses, significantly improving radiological accuracy. In addition to diagnosis, AI is crucial in forecasting patient outcomes by evaluating multi-dimensional data to determine tumor aggressiveness, recurrence risks, and treatment responses. This helps in creating personalized treatment strategies tailored to tumor genomics and individual patient profiles. Furthermore, AI-driven drug discovery speeds up the identification of new therapeutic agents, further enhancing precision oncology. However, despite its potential, AI faces challenges, including the need for high-quality datasets, transparency in algorithms, and addressing ethical issues like data privacy and bias. However, with continued technological advancements and interdisciplinary collaboration, AI has the potential to transform ovarian cancer management, ultimately improving survival rates and patient well-being. This abstract highlights the significance of AI as an essential resource in the fight against ovarian cancer.