Polycystic ovary syndrome (PCOS) is a multifaceted endocrine condition identified by cycles of menstruation that are irregular, polycystic ovaries and hormonal abnormalities, with symptoms including hirsutism, acne, and reproductive difficulties. Treatment usually includes lifestyle changes such as exercise, dietary changes, and vitamin supplementation, which is especially important for overweight people or those with metabolic issues. Natural supplements such as inositol, curcumin, vitamin D, N-acetylcysteine, D-chiro-inositol, omega-3 fatty acids, folate, and tocopherol have emerged as intriguing components in PCOS treatment, with possible therapeutic effects. Despite the success of traditional medications, many PCOS patients prefer alternative therapies owing to their perceived efficacy and fewer side effects. Phytochemicals derived from plants such as aloe vera, chamomile, cinnamon, ginseng, fennel, and licorice have received attention for their involvement in PCOS therapy and are frequently seen as a cost-effective and well-tolerated option. Furthermore, AI and machine learning (ML) techniques have demonstrated significant potential for improving PCOS diagnosis and classification accuracy. AI/ML models can help with early detection and personalized treatment methods by following standardized diagnostic criteria. AI-driven research must adhere to reporting criteria and maintain scientific rigor to achieve clinical relevance and diagnostic precision.