JMIR Publications

ABSTRACT

Background:

Artificial intelligence has the potential to transform healthcare in low- and middle-income countries, where access to quality care remains limited. Maternal, sexual, and reproductive health (MSRH) outcomes are especially poor due to resource shortages, financial barriers, and geographic inequities. With thoughtful implementation, AI could help address these gaps through innovations in diagnostics, health education chatbots, and telemedicine. However, responsible use is essential to ensure AI reduces—rather than exacerbates—health disparities between high- and low-income regions.

Objective:

To explore the early experiences, perceptions of health workers, policymakers and general population, as well as AI researchers and implementers around the opportunities, risks, limitations, and best practices for responsible artificial intelligence applications in maternal, sexual and reproductive health (MSRH) in sub-Saharan Africa.

Methods:

We conducted a cross-sectional qualitative study to explore perceptions of health workers, policymakers, AI researchers and implementers, as well as seven community Advisory Board (CAB) members. We delved into the opportunities, risks, limitations, and best practices for responsible AI in maternal, sexual and reproductive health (MSRH) in sub-Saharan Africa (SSA).

Results:

Across the participant groups and data collection methods, we found a high level of diversity in the experiences and perceptions of AI in MSRH in sub-Saharan Africa. AI for MSRH has potential to improve quality and efficiency of MSRH health care delivery in Africa and to widen the reach of health services. For the AI innovations to be disseminated equitably, increase in awareness of the characteristics of AI innovations, their layered complexities, capacity to understand and use them fairly and improving infrastructure will all be critical. Co-creation of AI tools with communities, heath workers and technologists and rigorous evaluation may help to create safe, trustworthy and easily adopted AI tools for MSRH.

Conclusions:

Our findings inform the development of a continent-wide AI hub for MSRH, highlighting barriers and opportunities for improving health care access. We aim to support policymakers, researchers, and implementers in using AI to promote equitable maternal and sexual and reproductive healthcare delivery across Africa.