Global health leaders have launched a major partnership with a US$60 million investment to assess how artificial intelligence (AI) can help improve health outcomes in low- and middle-income countries. The new programme, called Evidence for AI in Health (EVAH), was unveiled today at the ongoing AI Impact Summit in New Delhi. It aims to produce strong evidence on what AI tools can do in real-world health settings and how they can be used responsibly by health systems across Africa, South Asia and Southeast Asia, according to the Gates Foundation.
At its core, this initiative seeks to close a critical gap in what we know about the performance and usefulness of artificial intelligence technologies in everyday health care. Many artificial intelligence programmes have shown promise in labs and pilot projects, but few have been tested at scale in communities that are resource-constrained and historically underserved. EVAH hopes to change that trajectory by partnering with researchers on the ground to lead independent evaluations that answer key questions about safety, effectiveness, value and trust.
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Why Evidence Matters for Artificial Intelligence in Health
Artificial intelligence is often spoken about as a game-changer for health care, especially in places where health systems struggle with workforce shortages and limited infrastructure. From supporting diagnosis to triage and referral decisions, AI-driven tools such as machine learning models and language systems could help frontline health workers deliver more accurate and timely care. But without solid data from diverse settings, policymakers and health leaders have little basis for deciding which tools to adopt and how best to integrate them into public systems.
The EVAH initiative is the second major investment from a broader global health research partnership between the Bill & Melinda Gates Foundation, the Novo Nordisk Foundation, and Wellcome. It complements other efforts that seek to accelerate innovation in health while ensuring ethical and equitable implementation. Researchers involved in EVAH will include the Abdul Latif Jameel Poverty Action Lab (J-PAL) and the African Population and Health Research Center (APHRC), both of which bring experience in rigorous evaluation, evidence synthesis, and partnership with local research teams.
EVAH’s first call for proposals (RFP), launched today, specifically focuses on mature AI tools that are ready for real-world testing. These technologies are expected to assist health workers in clinical decision-making within primary care and community health settings. The research funded through this call will include implementation science studies, randomised controlled trials, economic analyses, and assessments of how well these tools are accepted by both health professionals and communities.
Local Insights, Global Learning
One of the initiative’s most important features is its emphasis on locally led research. Instead of imposing outside solutions, EVAH encourages health systems and researchers from within low- and middle-income countries to shape the studies based on their own local health problems, priorities and contexts. This approach reflects a growing consensus that meaningful health innovation must be rooted in local needs and knowledge, not simply imported from elsewhere.
This local empowerment also extends to the kinds of AI tools selected for evaluation. Priority is being given to technologies that are trained on representative and inclusive data, designed for resource-limited conditions, and aligned with public benefit goals. All findings from the evaluations will be made openly available, with safeguards for data privacy and scientific integrity. Health leaders hope that this transparent evidence base will help reduce wasted investments and prevent promising innovations from falling short of meaningful impact once deployed at scale.
Experts note that robust evidence is essential to prevent widening disparities in access to quality care. A recent analysis by The Lancet showed that although nearly 90 AI health trials were conducted globally between 2018 and 2023, only four took place in low- and middle-income countries. This lack of rigorous evaluation in the places that need it most has left governments and health systems without the information needed to make confident decisions about artificial intelligence technology.
What the Funders Are Saying
Nigeria’s Minister of Communications, Innovation and Digital Economy, Dr. Bosun Tijani, emphasised the importance of local evidence in driving policy decisions that improve health outcomes. He said that AI has the potential to transform care delivery but that its real success must be measured by tangible improvements in people’s lives, especially in African countries.
Similarly, representatives from Wellcome and the Novo Nordisk Foundation stressed that despite the hype around AI, the world still lacks clarity on how best to integrate these tools into health systems. They highlighted that the evaluations supported through the EVAH initiative will produce critical insights needed for evidence-based policymaking and stronger service delivery.
At the Gates Foundation, global health leaders said this initiative reflects a broader commitment to making sure innovations in AI not only reach the communities that need them most but also deliver measurable benefits that improve health outcomes. This includes economic value, safety, acceptability and trust among the people who use these technologies every day.
Looking Ahead
As the first round of evaluations begins, health officials and researchers will be paying close attention to the outcomes. If done well, these studies could lay the groundwork for smarter, more equitable use of AI tools in health care across the developing world. They may also provide a blueprint for how investment in digital health innovation can be more closely tied to evidence and measurable impact, reducing the risk of wasted resources and unintended harm.
The new evidence generated through this global partnership could come at a pivotal moment. Many countries in Africa and Asia are actively exploring ways to use AI for public health surveillance, diagnostics and clinical support. Data from rigorous studies will help ensure that these technologies are not adopted piecemeal, but rather integrated into health systems in ways that are safe, effective and aligned with national priorities.
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