We bring advisory, development, and capacity-building together
to help countries institutionalize AI across public systems.
We help governments translate national priorities into actionable AI strategies that balance innovation with ethics, governance, and public value.
We co-build AI systems grounded in local realities, designing and deploying solutions that deliver lasting public impact for the communities they serve.
We equip people and institutions with the skills and knowledge needed to sustain AI progress and build resilient public systems.
Focus Areas
WAIG works to strengthen public health systems by applying AI to critical challenges in screening, surveillance, and decision-making. Our focus is on enabling earlier detection, improving information synthesis for policymakers and clinicians, and supporting evidence-based responses across population and care-delivery levels.
AI tools that support early disease detection, improve maternal and child health outcomes, and strengthen public health systems.
WAIG supports education systems by using AI to improve learning outcomes and strengthen system-level planning. We focus on addressing foundational learning gaps while enabling governments to anticipate risks, allocate resources more effectively, and design responsive education policies.
AI-based learning platforms and employment-matching systems that promote access and inclusion.
WAIG applies AI to strengthen agricultural systems by supporting farmers, improving productivity, and enabling data-driven national planning. Our work bridges farm-level decision-making with system-level intelligence to enhance resilience, sustainability, along with economic and food security.
Predictive models that help farmers make informed decisions, improve yields, and reduce losses.
WAIG strengthens public institutions by enabling responsible adoption of AI through capacity building, governance frameworks, and cross-regional collaboration. We focus on ensuring that AI deployment in the public sector is effective, ethical, and aligned with national priorities.
AI-based learning platforms and employment-matching systems that promote access and inclusion.
Our Services
We help governments translate national priorities into actionable AI strategies that balance innovation with ethics, governance, and public value.
AI tools that support early disease detection, improve maternal and child health outcomes, and strengthen public health systems.
We co-build AI systems grounded in local realities, designing and deploying solutions that deliver lasting public impact for the communities they serve.
Predictive models that help farmers make informed decisions, improve yields, and reduce losses.
We equip people and institutions with the skills and knowledge needed to sustain AI progress and build resilient public systems.
AI-based learning platforms and employment-matching systems that promote access and inclusion.
Focus Areas
AI tools that support early disease detection, improve maternal and child health outcomes, and strengthen public health systems.
AI tools that support early disease detection, improve maternal and child health outcomes, and strengthen public health systems.
Predictive models and front-line support that helps farmers make informed decisions, improve yields, and reduce losses.
Predictive models that help farmers make informed decisions, improve yields, and reduce losses.
AI-based learning platforms and employment-matching systems that promote educational access and inclusion.
AI-based learning platforms and employment-matching systems that promote access and inclusion.
WAIG strengthens public institutions by enabling responsible adoption of AI through capacity building, governance frameworks, and cross-regional collaboration.
AI-based learning platforms and employment-matching systems that promote access and inclusion.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.
We meet countries where they are and guide them across the full journey from advisory to deployment to scale tailored to readiness, budget, and ambition
Build cross-stakeholder alignment (gov, donor, local); secure access, legitimacy, and buy-in
Landscape existing systems, assess digital/data readiness, plan architecture
Identify hardware, compute, devices, and edge-readiness gaps; recommend enablement pathways
Shape national strategies, governance frameworks, and implementation guidelines
Develop or adapt AI solutions to country-specific needs and constraints
Coordinate government, donor, and vendor-led implementation
Build long-term institutional capacity and local fluency
Measure effectiveness, generate evidence for donors, refine solutions
We help countries think about Al strategically, develop Al responsibly, deploy Al at scale, and evaluate Al for impact.
AI tools that support early disease detection, improve maternal and child health outcomes, and strengthen public health systems.
Unites policy, people, platforms, and proof into one architecture for national transformation.
Predictive models that help farmers make informed decisions, improve yields, and reduce losses.
Evolved from real-world deployments; built for governments, donors, and ecosystems that demand results, not reports.
AI-based learning platforms and employment-matching systems that promote access and inclusion.
Foundational elements create the conditions for AI to succeed across sectors and contexts
Leaders who are engaged with frontline challenges and understand how technology can both enable and block development are essential. Such leaders can champion interventions where they add value and build support for tools that are appropriate, effective, and scalable.
Clear policy frameworks guide AI deployment while building public trust. In East Africa, national digital strategies with privacy safeguards, interoperability standards, and accountability benchmarks aligned multiple pilots with shared objectives, fostering coherence and credibility.
Assessing digital readiness is essential to understanding whether technology can reach and benefit its intended users. In India, decades of investment in infrastructure and standards enabled the creation of the UPI system, which now serves as a foundation for ongoing financial innovation.
Once foundations exist, governments can innovate strategically
Sustainable AI ecosystems require deliberate multi-stakeholder engagement. In several African nations, governments balanced partnerships with academia, donors, private vendors, and civil society, avoiding both over-centralization and over-reliance on external expertise.
Solutions must address clearly defined development challenges. In India, AI models predicting malnutrition hotspots were adapted locally to account for regional dietary patterns and infrastructure limitations, demonstrating how design thinking ensures relevance and usability.
Hardware, devices, and computational resources are essential to bring AI solutions to end users. In Southeast Asia, last-mile digital kiosks and edge devices enabled remote communities to access AI-driven health diagnostics, highlighting the importance of matching technology to infrastructure realities.
The final cluster ensures that pilots translate into lasting benefits
Integrating AI solutions into existing national systems institutionalizes innovation. For instance, India’s digital learning initiatives were embedded into state education management structures, ensuring continuity beyond initial donor support or pilot timelines.
Systematic evidence collection lets governments track whether innovations are delivering on their promises, ensure alignment with public interest priorities, and feed insights back into national systems to adapt and improve over time.
Alongside technical and operational insights, our work underscores principles of responsible AI: fostering collaboration, enabling local entrepreneurship, and avoiding one-size-fits-all approaches. Sustainable adoption emerges from trust, shared accountability, and context-sensitive design rather than hype-driven technology pushes.
Scaling AI in public systems is less about the sophistication of technology and more about the capacity of institutions to absorb, adapt, and sustain it. By focusing on foundational readiness, deliberate innovation, and impact-oriented integration, governments and development partners can move beyond isolated pilots toward AI that genuinely serves citizens. The lessons extend beyond AI itself, offering a blueprint for technology-driven development in diverse national contexts.
