Across sub-Saharan Africa (SSA), artificial intelligence is quietly transforming maternal healthcare delivery. In the most rural parts of Kenya, pregnant women can now receive AI-powered text messages in Swahili that detect warning signs and immediately connect mothers to qualified midwives through a system called Promoting Mothers in Pregnancy and Postpartum Through SMS (PROMPTS). The integration of AI comes at a critical moment: The region bears 70% of maternal deaths globally, yet smartphones with Short Message Service (SMS) are being transformed into lifelines that could fundamentally alter maternal and newborn care.

While maternal mortality rates have declined over recent decades, the current trajectory remains inadequate to achieve international targets by 2030. As AI reshapes sectors from finance to agriculture, it now also offers expansive potential for maternal health. The technology is capable of predicting fatal complications, extending specialized care to remote communities and supporting the shrinking health workforce across the region. However, unless deployed wisely, the inclusion of AI has the potential to widen rather than close inequalities.

The promise of AI in women’s health

Recent empirical evidence indicates that AI adoption significantly reduces maternal mortality, particularly in low- and middle-income countries, reducing annual maternal mortality trends by up to 27%.

Recent AI programs across SSA are moving from promise to proven practice, with new programs showing measurable progress on the ground. Malawi offers a striking example: Continuous AI fetal monitoring during labor has reduced stillbirth and neonatal deaths by 82%. Innovations extend beyond the delivery room in Ghana with an AI-enabled traffic prediction dashboard that maps travel times to emergency obstetric care to predict access gaps to help policymakers understand where access barriers persist. Meanwhile, across SSA, startups are using AI-powered ultrasound technology to help healthcare providers quickly identify pregnancy risk factors, and innovation hubs are piloting algorithms to predict miscarriages.

Is AI helping or hurting?

By creating systems of dependency that displace local knowledge in favor of externally endorsed solutions, these technological advances risk repeating the most damaging patterns of prior global health interventions. Broadly, the focus on technological solutions can divert attention and funding from addressing fundamental structural issues: poverty, inadequate health systems and a lack of trained personnel. These are the driving forces of maternal mortality in SSA.

AI maternal health solutions risk creating hierarchies of care based on digital access. Women with poor network coverage, those who can’t afford smartphones and those who have low digital literacy could become excluded from potentially life-saving interventions. Even more concerning is algorithmic bias. AI systems fail rural women and marginalized groups in the Global South when those systems train with Western datasets and linguistic frameworks; this can potentially produce harmful and biased guidance, even errors. The sustainability question looms equally large — even well-intentioned tech pilots can collapse when donor funds end, leaving local health systems dependent on outside vendors with dashed expectations.

Preventing AI from widening Africa’s maternal health gap

Medical technicians will inevitably integrate AI into maternal healthcare globally. When they do, will we allow AI to deepen divides or equip it to bridge them? If AI is to serve women and children rather than repeat the well-intentioned but misguided practices that have long characterized global health interventions, we must develop safeguards to reenvision how these systems are developed, deployed and governed.

To deploy AI equitably, we must set safeguards that include these four interconnected domains:

1. Infrastructure development must prioritize local data centers to maintain data sovereignty, ensuring health information generated by communities remains under their control rather than flowing to foreign tech companies.
2. It is critical that local innovation receives funding, which supports African developers, researchers and institutions to create homegrown AI tools and datasets. This way, the AI solutions are culturally and contextually relevant.
3. These technical investments must be paired with governance reforms that mandate local ownership and engagement. That ensures women and healthcare workers shape AI maternity tools and pilots from production to evaluation.
4. Finally, all AI systems must be designed to function effectively in low-connectivity, resource-constrained settings, ensuring that AI innovations strengthen rather than deepen the digital divide.

AI is not the silver bullet for solving the maternal health crises in SSA, but it carries undeniable potential for reshaping the health landscape and the technology’s enticing innovations. As recent research identifies, technology must strengthen rather than supplant health systems, amplifying rather than erasing the voices of local women and healthcare workers.

[Nikia Crollard contributed to this article in her personal capacity. The views expressed are her own and do not necessarily represent the views of the Department of Health & Human Services (HHS) or the United States Government.]

[Lee Thompson-Kolar edited this piece.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.