Polycystic ovary syndrome (PCOS) causes a worldwide disturbance in hormonal equilibrium, leading to a growing need for individualized, non-pharmaceutical therapies. Studies on AI-driven technologies in PCOS have uncovered a groundbreaking approach to regulating hormones through dietary changes. AI algorithms examine individual data, integrating genetics, biomarkers, and dietary habits to provide a distinct metabolic and hormonal profile. Suggested options consist of adaptable meal plans that can adapt to immediate fluctuations in blood sugar and hormones, maximizing nutrition to regulate hormones, reduce inflammation, and enhance general well-being. Additionally, these recommendations provide predictive insights to enable proactive alterations to one’s diet. The comprehensive evaluation of limitations and moral considerations about AI highlights the necessity for human expertise and safeguarding of data privacy. Concrete instances from reality and current scientific investigation demonstrate the capacity of AI to enhance the capabilities of women suffering from polycystic ovary syndrome (PCOS). Proposing the integration of AI into evidence-based dietary practices anticipates a future in PCOS care that is tailored, proactive, and data-driven, with the ability to maximize hormonal equilibrium and improve women’s well-being. This concise investigation provides significant perspectives for healthcare practitioners engaged in the treatment of PCOS and associated endocrine problems.