While modest advancements have been made in designing applications for women’s healthcare, a structured approach to designing AI applications for women in menopause transition represents a notable gap. This critical life stage impacts over 75 million women in the U.S., yet these women remain underserved by evidence-based research, clinician knowledge, and personalized products. Health disparities across race and ethnicity are also contributing to these challenges. This study uses the Jobs-To-Be-Done (JTBD) framework to better understand the diverse and unique experiences of women in menopause transition with a focus on their functional, emotional, and social contexts. We conducted in-depth interviews with eight participants through purposive sampling from a beta test group. The qualitative research identified a “purpose-driven” segment that is motivated by the functional outcomes of feeling healthy with preference to focus on their health goals rather than perimenopause. These participants demonstrate stronger motivation when their health goals align with emotional and social benefits. The JTBD framework provides an actionable blueprint for designing women-centered AI applications with key considerations on the challenges (trust in AI technology) and benefits (potential to reduce bias) of the use of AI. This approach offers a pathway to design AI applications that help women in menopause transition accomplish their health goals while providing emotional and social support throughout their journey.