Empowering women through intelligent care: a narrative review of AI-driven digital innovations for endometriosis diagnosis, education, and equity

Abstract Background Endometriosis is a chronic, inflammatory, and multifactorial gynecological disorder affecting approximately 10% of women of reproductive age worldwide. It is associated with debilitating pelvic pain, infertility, and significant socioeconomic burden. Despite its impact, diagnosis is often delayed due to nonspecific symptoms and the absence of non-invasive biomarkers. Objective This narrative review critically examines the current landscape of artificial intelligence (AI) applications in endometriosis diagnosis, education, and management, identifies existing barriers to clinical integration, and proposes a strategic framework for the development of inclusive and ethical digital health ecosystems. Methods A narrative synthesis of peer-reviewed literature and technical reports was conducted, focusing on AI-enabled tools in reproductive health, endometriosis-specific applications, ethical guidelines for AI in healthcare, and regulatory frameworks. Comparative analysis of current FemTech solutions was also included. Results Despite promising developments in AI-based symptom-tracking, imaging analysis, and decision support, significant barriers persist. These include technical limitations (small and biased datasets), clinical misalignment, ethical concerns (privacy risks, bias amplification), and sociocultural challenges (digital divide, stigma). Current FemTech platforms demonstrate limited readiness to address the complex needs of endometriosis patients. Conclusions To fully realize AI’s transformative potential in endometriosis care, future efforts must prioritize participatory design, real-world data integration, transparency, inclusivity, and regulatory compliance. Endometriosis must be elevated within digital health equity agendas to ensure that technological innovations effectively address the lived experiences of women affected by this condition.