Every two minutes, a woman dies somewhere in the world from preventable complications related to pregnancy or childbirth, according to figures cited by UNICEF. In India, a platform called CareMother, built by the health technology company Doto Health and supported by UNICEF’s innovation arm, is using AI to try to catch the warning signs of high-risk pregnancies early enough for intervention, before those complications become fatal.
The Preventable Tragedy at the Heart of Maternal Health
Maternal mortality remains stubbornly high across much of the developing world despite the fact that most of the leading causes of pregnancy-related death, including preeclampsia, hemorrhage, and infection, are preventable or treatable when identified early enough. The core barrier is often not medical knowledge but access and monitoring: in many rural and underserved parts of India, pregnant women see a clinician only intermittently, leaving long gaps during which warning signs can develop undetected between appointments.
How CareMother Tracks Risk Over Time
CareMother’s platform tracks maternal and fetal vital signs over the course of a pregnancy and uses algorithms to flag risk factors early, rather than relying solely on the snapshot assessment a single clinical visit provides. By aggregating data across multiple touchpoints, the system is designed to catch deteriorating trends, a gradual rise in blood pressure, for instance, that might not trigger concern at any single visit but becomes clinically significant when tracked over weeks.
Building Toward a Single Clinical View
Beyond risk flagging, Doto Health is also developing AI case summarization tools intended to consolidate a single patient’s visits, test results, and scans into one unified view for clinicians, addressing a common problem in fragmented health systems where a patient’s history is scattered across different providers, paper records, and facilities. For overworked clinicians managing large caseloads of pregnant patients, a consolidated summary could meaningfully reduce the chance that an important risk factor buried in an earlier visit’s notes gets overlooked.
Why UNICEF Is Backing This Kind of Technology
UNICEF’s involvement reflects the organization’s broader interest in scalable, technology-driven approaches to reducing maternal and child mortality in resource-constrained settings, where building enough traditional clinical infrastructure, more hospitals, more trained obstetricians, more specialist equipment, would take decades and enormous capital that many health systems don’t have. AI-driven monitoring tools like CareMother are pitched as a way to extend the reach of the clinical expertise that does exist, rather than as a replacement for it.
The Caution That Comes With AI in Maternal Care
Researchers publishing peer-reviewed reviews of AI in maternity care, including one in the International Journal of Gynaecology and Obstetrics, have stressed that AI-powered technologies should complement rather than replace human clinical expertise, calling for explainable AI systems, transparent validation studies, and governance frameworks that address patient safety and consent directly. Maternal health carries exceptionally high stakes for both patient and child, meaning errors or overreliance on an unproven algorithm could cause serious harm, a concern that applies with particular force in lower-resource settings where there may be fewer clinicians available to catch an AI system’s mistakes.
What Scaling CareMother Would Mean
If CareMother’s approach continues to demonstrate measurable improvements in catching high-risk pregnancies earlier, the platform could offer a template for similar maternal health monitoring efforts across other countries facing comparable gaps between clinical visits and the need for continuous risk tracking. The broader test, as with much of AI in global health, will be whether a tool developed and validated in one health system’s specific context can be adapted responsibly to the vastly different clinical infrastructures and patient populations found across India’s diverse states and beyond, without losing the reliability that makes it useful in the first place.
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