Purpose of Review <p>This report describes an overview of current applications of artificial intelligence in healthcare with specific focus on uses within women’s health and menopause care. We aim to identify which tools and methods have been applied to menopause diagnosis, symptom management, and treatment personalization, while also reflecting upon the structural and data barriers that prevent equitable use of AI in this domain.</p> Recent Findings <p>As AI has continued to advanced rapidly within healthcare, mature applications such as in drug discovery and diagnostic imaging have shown promise to improve care. Despite this, advancements in menopuase care remain a significant gap: as of 2025, none of the 1,257 FDA-approved AI algorithms focus on menopause diagnosis or treatment. Existing maching learning approaches are limited by data issues such as sparse, inconsistently captured clinical data as well as underrepresentation of large groups of women, partricularly women of color, in research databases. Data missingness disproportionately affects already-underserved populations, meaning application of these AI tools risks amplifying these disparities further.</p> Summary <p>While menopause represents a potential space for development of artificial intelligence solutions, meaningful structural changes to data acquisition and interpretation are required to ensure accurate, impactful, and equitable care.</p>