Lahore University of Management Sciences (LUMS) has been awarded a major multi-year grant from the Gates Foundation to establish Pakistan’s first nationally coordinated Artificial Intelligence (AI) Hub. The Hub will launch with a flagship focus on Maternal, Newborn, and Child Health (MNCH), one of the country’s most urgent public health priorities, while being designed as a long-term national platform that will progressively expand to address other critical development challenges facing Pakistan. The initiative is also supported by Mubarik Imam, member of the Advisory Board at the Syed Babar Ali School of Science and Engineering (SBASSE) at LUMS.
The National AI Hub is significant because it brings together two of Pakistan’s leading research universities, LUMS and Aga Khan University (AKU), to address the critical challenge of maternal, newborn, and child health. LUMS will build on its longstanding expertise in artificial intelligence, language technologies, gender and technology research, and digital public health innovation, while AKU will serve as a key technical and clinical partner, contributing to the development of large maternal health datasets, providing clinical expertise, and supporting evaluation and field testing of AI-enabled interventions across diverse care settings. The AI Hub will enable the development and scaling of AI-driven healthcare solutions tailored to Pakistan’s underserved populations, using timely predictive analytics to strengthen prevention, early diagnosis, and continuity of care. It is designed to deliver impact at a national scale.
The AI Hub will be led by Dr Maryam Mustafa, Associate Professor of Computer Science at SBASSE, LUMS, with Professor Fyezah Jehan, Chair of the Department of Paediatrics & Child Health at AKU, collaborating closely on clinical design and implementation. The Hub will also convene government partners, clinicians, AI researchers, policymakers, and innovators to strengthen early diagnosis, clinical decision-making, referral pathways, and continuity of care for women and newborns nationwide.
“This is a milestone moment for both LUMS and Pakistan,” said Dr Maryam Mustafa. “We are launching this Hub with maternal, newborn, and child health because this is where the need is most urgent and the opportunity for immediate impact is greatest. At the same time, our vision is to build a nationally anchored, responsible AI platform, one that can grow over time to support multiple sectors where data-driven intelligence can strengthen public systems and improve lives across the country.”
This national initiative builds on a successful earlier Grand Challenges grant led by Dr. Maryam Mustafa, titled Awaaz-e-Sehat: Empowering Maternal Healthcare with Voice-Enabled Electronic Record Management. The project demonstrated how voice technology and multilingual interfaces can support frontline health workers and improve continuity of care in low-resource settings.
Sharing her views, Ms Mubarik Imam stated, “Honoured to support Pakistan’s first AI hub, a pioneering partnership between LUMS & AKU. Limited access to specialist expertise continues to drive preventable loss of life and poor health outcomes among women and children; AI can change that by democratizing world-class medical knowledge for frontline healthcare workers from Astore to Ziarat. This hub is built for impact, equipping researchers, clinicians, and entrepreneurs to tackle Pakistan’s toughest challenges, starting with maternal, newborn, and child health, and creating scalable models for the Global South.”
Pakistan continues to face some of the highest maternal and neonatal mortality rates in the region. Maternal mortality currently stands at 186 deaths per 100,000 live births, driven by limited access to quality antenatal, delivery, and postnatal care; shortages of skilled health workers; weak referral systems; and delays in managing critical complications such as hemorrhage, eclampsia, and sepsis. These challenges are further compounded by language and literacy barriers, fragmented health data systems, and social and economic constraints that delay timely care.
The AI Hub will address these gaps by working within existing health systems to deploy ethical, evidence-based, and locally relevant AI tools and by bringing timely, life-saving support closer to the women and families who need it most. For a mother in a remote village, this could mean earlier identification of pregnancy-related risks and faster referrals in case of complications. These also include AI-enabled risk prediction and decision-support systems for frontline health workers; speech-based and multilingual tools to bridge literacy and language barriers; strengthened referral and follow-up mechanisms; and frameworks to enable interoperability across health data systems. The Hub is explicitly designed to move beyond proof-of-concept pilots by integrating AI tools into national care pathways and enabling sustainable, system-wide impact.
Beyond its initial focus on MNCH, the AI Hub is envisioned as a national platform for responsible AI innovation aligned with Pakistan’s public-interest priorities. As it matures, the Hub’s infrastructure, governance, and technical capabilities will be extended to additional nationally relevant areas. The initiative will also strengthen Pakistan’s AI ecosystem through capacity building, policy development, AI governance, and support for startups working at the intersection of AI and social impact, while advancing Pakistan’s commitments under the United Nations Sustainable Development Goals 2030, particularly in reducing maternal and neonatal mortality.
With this historic investment, Pakistan joins a small group of countries building nationally coordinated, responsible AI platforms to address maternal, newborn, and child health, while laying the foundation for broader, cross-sectoral impact. The initiative aligns with similar efforts supported by the Gates Foundation in Africa, where AI Scaling Hubs are being established in Rwanda, Nigeria, Senegal, and Kenya as national platforms to scale mature AI solutions across health, education, and agriculture by coordinating ecosystem actors, enabling access to data and compute, and embedding solutions into public systems.