Ovarian cancer is a leading cause of death among gynecological malignancies, it has a poor prognosis due to its early asymptomatic stage. Early and accurate diagnosis is critical for improving survival rates. While ultrasound is essential in ovarian cancer detection, its effectiveness is limited by operator subjectivity. Advances in artificial intelligence (AI), offer promising solutions for automated ultrasound image analysis, enhancing diagnostic accuracy and consistency. Multi-modal ultrasound provides comprehensive tumor insights. Combining AI with multi-modal ultrasound enables improved risk assessment, precise tumor classification, and individualized treatment planning. This review explores the applications, challenges, and prospects of integrating AI with multi-modal ultrasound, highlighting its potential to transform ovarian cancer diagnosis and advance precision medicine.