Artificial Intelligence to Improve Maternal Health in Low-Resource Settings

Introduction: Maternal health inequality is a global challenge, especially in low- and middle-income countries (LMICs), where access to skilled care is limited. Artificial intelligence (AI) is advancing as a tool in healthcare, with potential to reduce maternal health inequities by improving early risk detection, guiding clinical decisions, and optimizing resource allocation. This study explores the role of AI-driven technologies in enhancing maternal health outcomes in under-resourced settings. Method: A was conducted, synthesizing peer-reviewed literature, pilot studies, and global health reports from 2018–2024. Key themes included AI applications in antenatal risk screening, remote monitoring, triage systems, and maternal health data analytics. Results: AI has been successfully integrated into maternal health platforms for predicting high-risk pregnancies (e.g., preeclampsia, hemorrhage), automating ultrasound image analysis, and supporting virtual consultations in rural areas. In countries like India, Kenya, and Ethiopia, AI-assisted chatbots and mobile apps improved antenatal follow-up and patient education. However, barriers such as data privacy concerns, algorithm bias, lack of infrastructure, and digital literacy remain significant, especially in remote or conflict-affected regions. Conclusion: AI offers promising pathways to improve maternal health equity by enabling proactive, personalized, and effective care models. To fully benefit from its potential, ethical frameworks, local capacity-building, and inclusive technology design must be prioritized. Collaborative efforts between governments, tech developers, and communities are essential for sustainable integration.