Can AI Bridge or Widen Maternal Health Inequities?

Abstract

Artificial intelligence (AI) is rapidly transforming maternal healthcare through tools like risk prediction algorithms, telemedicine platforms, and postpartum support chatbots. Although these innovations offer promise, particularly in low- and middle-income countries (LMICs), their impact on health equity remains contested. This commentary explores how AI can either bridge or widen maternal health inequities, depending on how it is designed, governed, and implemented. We introduce a conceptual framework comprising four interdependent domains that shape equity outcomes in maternal health: inclusive data practices, equitable governance, participatory design, and local capacity-building. Drawing from interdisciplinary literature, we situate AI within broader health and social systems and argue for equity-oriented approaches that foreground representation, accountability, and community engagement. By examining both opportunities and risks, this commentary offers practical, context-sensitive recommendations for LMICs to ensure AI serves as a tool for justice in maternal healthcare.

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