Polycystic ovary syndrome (PCOS) is a common yet complex endocrine disorder in women of reproductive age. It is associated with several metabolic complications necessitating personalized management approaches. However, current strategies fail to capture the heterogeneity in PCOS phenotypes. Nutritional therapy tailored to distinct metabolic profiles underlying PCOS subtypes has immense yet untapped potential. This chapter proposes an artificial intelligence (AI) based precision nutrition model to provide customized dietary recommendations for PCOS by systematically assimilating multi-domain data, utilizing explainable AI to decipher pathology, matching dietary components to outcomes via machine learning algorithms and continually updating recommendations. It also delineates opportunities and challenges around advancing adoption of such AI-enabled personalized nutrition prescriptions to transform care. In nutshell, AI-enabled, tailored nutritional therapy carries immense potential to transform PCOS care from one-size-fits-all strategies to individualized prescriptions effectively addressing the intricate metabolic heterogeneity underlying this complex disorder. The long-term impact on outcomes cannot be overstated given the alarming burden inflicted by this highly disruptive syndrome on women around the globe.