A significant funding initiative aims to address a critical gap in the deployment of artificial intelligence in global healthcare: a lack of localized evidence. The Evidence for AI in Health (EVAH) initiative is offering up to $60 million to evaluate AI-enabled clinical decision support tools already in use by frontline health workers in Sub-Saharan Africa, South Asia, and Southeast Asia.
Despite the growing potential of AI to improve healthcare access and outcomes, particularly in resource-constrained settings, rigorous testing within local contexts has been limited. A recent analysis revealed that of 86 randomized clinical trials on AI health tools conducted globally between 2018 and 2023, only four took place in low- and middle-income countries (LMICs). This disparity highlights the urgent need for evaluations that consider the unique challenges and realities of these regions, where overburdened healthcare systems could benefit most from effective decision support.
The EVAH initiative, backed by Wellcome Trust, the Gates Foundation, and the Novo Nordisk Foundation, recognizes that governments are hesitant to widely adopt AI tools without evidence of their effectiveness within their own clinical environments, languages, and workflows. Without such validation, promising technologies risk failing to translate into real-world impact, potentially wasting investments and exacerbating existing health disparities.
Funding Pathways for AI Evaluation
The initiative offers two distinct pathways for funding, designed to support AI tools at different stages of deployment. Pathway A, offering grants of up to $1 million USD over 3–12 months, is geared towards tools that are early in real-world deployment. These evaluations will focus on usability, workflow integration, adoption rates, safety, and preliminary cost-effectiveness. Pathway B, with grants of up to $3 million USD over 12–24 months, is intended for tools that are ready for broader scaling. Evaluations under this pathway will assess measurable effects on health outcomes, system efficiency, and equity across diverse populations.
Pathway A: Early Deployment Evaluation
- Grant Amount: Up to $1 million USD
- Duration: 3–12 months
- Focus: Usability, workflow integration, adoption, safety, and early cost-effectiveness
Pathway B: Scaling Evaluation
- Grant Amount: Up to $3 million USD
- Duration: 12–24 months
- Focus: Measurable effects on health outcomes, system efficiency, and equity
Both pathways require that proposed AI tools have moved beyond the proof-of-concept stage and have established partnerships with facilities for deployment. Eligible applicants include nonprofits, for-profit organizations, academic institutions, government agencies, and multi-actor consortia. A key requirement is that proposals must be led by organizations registered and operational in Sub-Saharan Africa, South Asia, or Southeast Asia, with at least 80% of the funds flowing to regional entities.
The initiative underscores the importance of locally-led research and development in AI for healthcare. By prioritizing funding for organizations based in the regions where these tools will be deployed, EVAH aims to foster sustainable innovation and ensure that AI solutions are tailored to the specific needs and contexts of the communities they serve.
The deadline to apply for funding is April 1, 2026. Interested organizations are encouraged to learn more and submit proposals through the initiative’s application portal.
This funding represents a crucial step towards responsible and equitable AI implementation in global health. By prioritizing rigorous evaluation and local ownership, the Evidence for AI in Health initiative aims to unlock the full potential of AI to improve healthcare for those who need it most.
As AI continues to rapidly evolve, the need for ongoing evaluation and adaptation will remain paramount. The outcomes of these funded evaluations will provide valuable insights for policymakers, healthcare providers, and technology developers, shaping the future of AI-driven healthcare solutions in low- and middle-income countries.
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Disclaimer: This article provides informational content and should not be considered medical or financial advice. Consult with qualified professionals for personalized guidance.
