Received August 02, 2025
Accepted September 24, 2025

Menopause signifies a crucial transition in a woman's life, often bringing about physical and psychological changes that can negatively impact mental health. Conditions like depression, anxiety, cognitive decline, and sleep issues are common during menopause, yet they frequently go undiagnosed and poorly managed, particularly in low- and middle-income countries. New technologies, especially artificial intelligence (AI), present innovative ways to address this care gap. While AI has demonstrated considerable potential in identifying physical health issues related to menopause, such as osteoporosis and endometrial cancer, its application in managing mental health during this phase is still limited. We examine the possibilities of AI-driven tools—including machine learning algorithms, digital therapeutics, symptom trackers, and large language models—to transform the diagnosis, monitoring, and personalized treatment of mental health disorders associated with menopause. AI systems can combine data from genetic, clinical, lifestyle, and wearable sources to forecast mental health risks, identify symptom patterns, and facilitate tailored interventions. These technologies promise scalable, accessible, and cost-effective mental health care, which can help reduce stigma and address service gaps. Utilizing AI in this area presents a significant opportunity to enhance the quality of life for millions of women experiencing menopausal transition globally.