Can AI Bridge the Gaps in Women’s Healthcare? A Responsible Path Forward

Women’s experience with the healthcare system is too often marked by delayed diagnoses, fragmented care, limited research and insufficient access to specialized expertise – challenges that persist from adolescence through older age. Access and answers often depend on a woman’s socioeconomic status or the availability of clinicians trained in women’s health, which often falls short, particularly for women in rural or underserved communities. Against this backdrop, artificial intelligence (AI) has emerged as a tool with the potential to provide timely information, surface emerging clinical evidence and support clinical decision-making regardless of these barriers.

Of course, AI alone is not a cure-all. Its value hinges on responsible, clinically grounded use and keeping expert oversight at the center. The question is no longer whether AI will influence women’s health, but how it can help, under what guardrails, and with what expectations for safety, transparency and impact.

A long-standing gap in women’s health

Shockingly, it wasn’t until the early 1990s that the National Institutes of Health required women to be included in clinical trials – leaving us with a massive debt in knowledge about how to safely and effectively treat women’s health conditions. Research shows that women are impacted by disease differently than men, are disproportionately affected by serious health conditions such as autoimmune disorders and cancer and are, on average, diagnosed later than men across nearly 700 conditions. Women with low income and women of color face even greater disparities, including accessibility to quality healthcare resources and programs.

Compounding these disparities is the chronic underinvestment in women’s health research: as of 2025, only 7% of biopharma innovation is invested in women’s health, and just 1% of this is invested in non-cancerous conditions. This means clinicians often lack evidence-based guidance, and women often lack timely answers and effective treatment options. 

As AI continues to evolve, it offers a reason for optimism in women’s healthcare. Advanced technologies can help bring long-overdue attention to women’s health, provide access to more resources and surface the latest research faster than ever before. By enabling better detection, personalized insights and evidence-based decision support, AI has the potential to disrupt traditional care models and create pathways for more equitable, informed and timely care for women.

Ways AI is advancing women’s healthcare

AI is poised to transform various systems and specialties within the medical field, and is already showing promise in addressing the gaps in women’s healthcare: 

• Enhanced detection and diagnosis: This is particularly relevant for both diseases that are specific to women and diseases where women present differently than men, such as CVD.  AI can help close the gap when used to analyze ECG results, for example serving as a tool for personalized cardiovascular risk prediction. Cervical cancer is another area where there is high impact to patient outcomes when  diagnosed early. Screenings are based on human papillomavirus (HPV) testing and cytological examination, but depend on pathologists to identify abnormalities. AI can enhance cervical cancer diagnosis by improving accuracy and efficiency of image analysis, and deep learning models are being deployed to detect and classify abnormal cells or lesions with high sensitivity and specificity. AI-assisted systems can also help triage patients more effectively, guide biopsy decisions and provide prognostic insights to support personalized treatment planning. Similar approaches are emerging for endometrial, ovarian and breast cancers, where early detection has historically been challenging. Clinicians and experts would always be in the loop, but AI would provide the co-intelligence to add speed and increase accuracy and insights.  

• Expanded access to specialized care: AI-powered tools for reproductive planning, pregnancy monitoring, menstrual health and menopause support can offer structured guidance where specialty services are limited. When rigorously validated and designed with privacy and safety in mind, these tools can complement (not replace!) clinician oversight and self-tracking. The value of these patient-centric and often patient-selected tools lies in giving women access to real-time insights about their own bodies — information that was impossible to observe or track in daily life before — helping them recognize patterns, compile questions, and feel more prepared for medical visits. These tools can meaningfully guide decision-making and strengthen how and when patients engage with healthcare. 

• Enabling clinical education: Generative AI and medically trained models can scan and summarize complex literature, identify consensus and uncertainty and translate emerging evidence into usable insights. In women’s health, where evidence is often fragmented, purpose-built AI can help providers stay current on evolving research and create more accessible patient education materials. Careful oversight is essential to ensure that AI outputs remain accurate, unbiased and clinically appropriate.

Building trust: Responsible AI implementation

Technology alone, no matter how promising, won’t close gaps in women’s health. To make real progress, AI and accompanying tech must be introduced with oversight and clear guardrails. That means starting with practical steps that build confidence and monitor accuracy, such as expert review, phased adoption and continuous feedback. These principles form the foundation for responsible implementation and help ensure AI earns trust as it becomes part of care delivery:

• Human-in-the-loop by design: Women’s health conditions are often complex, multi-factorial and sensitive to social determinants. Therefore, AI tools must include mandatory clinical review points, ensuring that model outputs support, rather than supplant, expert judgement. This safeguards against misinterpretation of outputs and ensures that AI augments clinical reasoning in nuanced scenarios.
  
• Privacy, equity and bias mitigation: Given women’s underrepresentation in clinical research, any AI system will need to proactively address algorithmic bias and leverage inclusive, representative datasets. Gender bias in healthcare AI is already being demonstrated in real world applications. Strong privacy safeguards and transparent data practices are essential to protect sensitive information – particularly related to reproductive health and genetics. Ensuring equitable access and performance across socioeconomic and geographic contexts, as well as continuous bias monitoring and legal/regulatory oversight, is imperative.
  
• Continuous feedback loops grounded in real-world performance: Women’s health challenges vary across age, ethnicity, reproductive status and comorbidities. AI systems must therefore be continuously evaluated in real-world clinical settings to ensure models remain accurate for the populations they are meant to serve. Feedback loops should integrate clinician reported issues, patient experience and routine monitoring to ensure the technology evolves responsibly and transparently over time. 

A powerful equalizer – if we build it responsibly

We are only beginning to see how AI can impact women’s health. As these technologies advance and become more integrated into healthcare workflows, we can expect more personalized care pathways that address women’s needs across different life stages. AI tools, serving as co-intelligence for researchers and practitioners, can help expand knowledge and, perhaps, invigorate funding and investment with the ultimate goal of driving better treatments, impactful evidence, more equitable care and better patient outcomes.  

This promise is far from guaranteed. Closing the gaps that have persisted for generations requires thoughtful guardrails, scientific rigor and collaboration between engineers, clinicians and patients. If developed responsibly, AI can become a powerful tool to progress women’s healthcare, supporting clinicians, empowering women and helping deliver care that has been long overdue.

Photo: asnidamarwani, Getty Images

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