AI’s Reality in Global Health: More Than Algorithms
AI tools are already deployed in clinics and labs across low- and middle-income countries. The conversation has moved from whether AI will arrive to how it can be deployed responsibly and sustainably. Shortages of specialists, such as radiologists in Malawi, create immediate demand for diagnostic models, but models alone cannot solve structural problems.
The Overlooked Compute Gap
Modern AI depends on physical infrastructure: data centers, cloud platforms, high-performance processors and steady energy. Many LMICs lack local compute capacity, so health projects rely on foreign hyperscalers. That reliance brings latency, higher costs, fragile operations when connectivity fails, and limited control over model life cycles.
Data Control: A Sovereignty Imperative
Where data is stored and who controls it shapes who benefits. Cross-border hosting and opaque contracts can expose sensitive health records and strip local authorities of oversight. Recent international agreements involving health data underline the legal and ethical risks when data sovereignty is not embedded from the start.
Building a Self-Reliant AI Future for LMICs
- Invest in regional data centers and renewable energy to support local compute and reduce dependence on distant clouds.
- Negotiate procurement with data residency, clear exit rights and guarantees of local ownership for models and updates.
- Form regional compute pools so health systems can share costs and scale training and inference capacity.
- Fund independent, locally led evaluation labs to validate models on representative data and monitor bias.
- Align national rules with continental frameworks, such as the African Union’s AI strategy, to boost governance and cooperation.
For AI to improve health equitably, policymakers, funders and implementers must treat compute and data governance as foundational priorities. Shifting investment from models alone to the infrastructure that runs them will determine whether AI serves local needs or locks countries into dependence.
