Geneva , May 19 : Artificial Intelligence can advance global health and bring tangible benefits to billions, but most countries still lack a road map to build the systems needed to bring its benefits to scale. That’s according to Foundations & Futures: Reimagining Public Health in the Artificial Intelligence Era Across the Global South, a new report launched by Vital Strategies at the 79th World Health Assembly.
”AI is moving faster than the systems meant to support it. But across the Global South, accelerated progress is possible,” said Dr. Mary-Ann Etiebet, President and CEO of Vital Strategies. “Billions of people live in data deserts, in countries or regions without the foundational data and digital systems that enable promising AI innovations to scale up.
The result is a widening gap between AI ambition and country preparedness. Foundations and Futures provides a shared understanding of AI readiness, supporting countries as they create their road maps for success, exchange learnings and approaches, and fast-track the actions needed to strengthen public health data systems, interconnectivity, governance and workforce capacity so that AI can help us close health equity gap not widen them.
The Data: A Widening Gap Between Ambition and AI Readiness Drawing on publicly available data from sources including the International Telecommunication Union, the WHO SCORE technical package and the Global Digital Health Monitor, the report found that while many countries are rapidly adopting AI tools, the underlying systems needed to translate AI into better health outcomes remain fragmented, incomplete or underfunded. Among the report’s findings:
- National AI policies that explicitly address health exist in fewer than one-third of the 83 countries reviewed.
- While nearly 70% of South and Southeast Asian countries have adopted AI policies, the infrastructure to sustain implementation remains uneven.
- Connectivity gaps remain significant. Internet connectivity and affordability scores range on average from 59 in Africa, 74 in South and Southeast Asia, 80 in South America to 88 in the Middle East. Higher scores (75+) indicate stronger progress toward universal and meaningful connectivity.
- Interoperability, the ability for digital health systems to exchange and use data across platforms, remains partial or weak in many countries. Only 15 of 59 countries that reported data on interoperability have reached Phase 4 or 5, reflecting more mature systems.
- Health data availability for priority indicators remains incomplete across many settings. In Africa, countries have recent data available for an average of only 62% of health-related SDG indicators, with only 15% having over 80% available data, limiting the completeness of the evidence base that AI tools rely on.
- Digital health workforce capacity remains nascent across most regions. According to the Global Digital Health Monitor, only 8% of African countries and 8% of South and Southeast Asian countries have reached Phase 4 or higher in digital health training integration meaning most health workers lack the skills to implement, govern or improve AI tools in practice. In South America all four countries with available data reached Phase 3 or higher, and two reached Phase 4 or higher.
Among the insights gathered through interviews with more than two dozen ministers of health, intergovernmental organizations, and global thought leaders across Africa, Asia and Latin America, governance and data sovereignty also emerged as a consistent theme: AI risks deepening dependency on external vendors and donors unless governments retain ownership of the systems and data beneath it.
“Countries in this report are already using AI to save lives, but they didn’t get there by chasing the latest tool. They got there by investing in unglamorous foundations: data systems, governance, connectivity and workforce capacity,” said Pedro de Paula, Senior Vice President, Global Innovation, Vital Strategies.
“What we’re asking of governments, funders and partners is a shift in mindset from project financing to infrastructure financing. Using Foundations and Futures, every country in the Global South can now find out where they stand on AI readiness, learn from peers who have solved similar problems, and make deliberate choices about which use cases are right for their context. The future of AI in health will not be determined by technical innovation alone. It will be determined by how well countries prepare their local systems and institutions to integrate AI and the work starts now.” The report sets out three principles to guide governments, funders and partners. AI adoption in the health sector must be:
- Guided by strategies for sustainable public health integration—with financing and workforce capacity that extends beyond initial build to maintenance, integration and institutionalization.
- Responsive to local governance structures—institutionalizing public governance and oversight that protect sovereignty, maintain accountability to the public interest, and earn public trust. Countries cannot govern what they do not control.
- Advanced with public health data systems that are inclusive and connected—prioritizing investment in foundational public health data systems and digital public infrastructure as the basis for scalable, equitable health impact.
Methodology
The report draws on three complementary approaches developed for this analysis. A Foundational Readiness Scan assessed 83 countries across Africa, South and Southeast Asia, Latin America and the Middle East against five dimensions: AI policy, connectivity, interoperability, health data availability, and digital health workforce capacity. A Rapid Use-Case Landscape Scan identified and analyzed 264 AI-related public health applications across the Global South. Regional Spotlights on Africa, South and Southeast Asia, and Latin America draw on country-level examples from Rwanda, India, Rio de Janeiro and Recife to illustrate what becomes possible when foundations and use cases align. Together these inputs ground a Discussion and Framework that organizes AI readiness as a set of foundational capabilities at two levels—within the public health system and across the wider national digital ecosystem—and sets out three principles for governments, funders and partners.