Big challenges. Shared realities. Stronger solutions. Across health, agriculture, and education, the Global South is already building AI that works in real conditions and at real scale. This fireside conversation examines what happens when Global South leaders collaborate, and how partnerships can turn AI potential into tangible development outcomes. Join the conversation on building AI solutions together at the India AI Impact Summit 2026.
VIDEO RECORDING
Scaling AI Solutions Through South–South Collaboration
Abstract
The session examined how AI initiatives originating in the Global South can move from pilots to nationwide impact through government partnership, digital public infrastructure, and South‑South knowledge‑exchange. Sunil Wadhwani shared concrete Indian case studies in tuberculosis care and early‑grade reading, outlining the pitfalls of “tech‑first” approaches and the lessons that led to scalable solutions. The Gates Foundation highlighted its new “Advantage India for AI” pledge to fund AI for development across the Global South. Panelists from Smart Africa, Qhala, EkStep, and the Indian Ministry of Electronics & IT discussed collaborative frameworks, the creation of the Africa AI Council, the importance of “digital rails” such as Aadhaar and UPI, and the need for a shared “collaboration tax” to lower barriers to joint development. The conversation underscored the principle that AI must be built on government‑backed platforms, be user‑centric for frontline workers, and be openly shared across borders to accelerate inclusive development.
Detailed Summary
Ankur Vora (Gates Foundation) opened the session with a light‑hearted remark about how he was recruited (“they found a guy with two badges”).
He thanked the audience and introduced the theme: turning AI potential into tangible development outcomes through South‑South collaboration.
2. Fireside Conversation with Sunil Wadhwani
2.1 Background of Wadhwani AI
Sunil explained that he and his brother launched the Wadhwani Institute for Artificial Intelligence (Wadhwani AI) in 2018, when AI was still nascent in India and before ChatGPT.
Their motivation was a gap: billions of dollars poured into AI research globally, yet almost none directed toward societal development in low‑resource settings.
2.2 Early Challenges & Pivot
Initial years focused on building sophisticated models without a clear deployment path.
After two‑three years of limited impact, they realized the need to co‑design with government, plan for scale from day one, and embed solutions into existing public‑sector platforms.
2.3 Case Study 1: Tuberculosis (TB) Care
Challenge
AI‑enabled Solution
Impact
Diagnosis – lack of functional X‑ray & sputum labs in vulnerable communities
Cough‑based AI: a smartphone app that analyses cough audio and outputs a risk score for TB
Rolled out nationally; WHO calls it a “potential game‑changer.” TB detection rose 25 % in the first year.
Sputum analysis turnaround – 64 government labs, long delays
Automated AI model for sputum microscopy that delivers results within a day
Faster treatment initiation; integrates with NICSHAY (national TB case‑management system).
Medication adherence – toxic drug regimens cause high drop‑out, leading to drug‑resistant TB
Predictive adherence model that flags patients likely to stop medication, enabling targeted follow‑up by ~2,000 community health workers
Improves adherence, reduces emergence of drug‑resistant TB.
Sunil stressed that government platforms (NICSHAY) were essential for integration and scale.
2.4 Case Study 2: Early‑Grade Literacy
Problem: High dropout rates in primary school, especially grades 1‑5, driven largely by lack of reading proficiency in the mother‑tongue.
Solution: An AI‑driven suite that personalizes reading exercises and stories for each child, delivered via teachers’ tablets and home‑based mobile apps.
Scale: Pilot in Rajasthan; the state mandated the tool for 3 million children.
Lesson: Personalization + government endorsement = rapid adoption.
2.5 Key Lessons from Wadhwani AI
Government partnership is non‑negotiable – work with senior civil servants early, approach with humility, and make the government a co‑owner of deployment.
Design for scale from day‑one – consider training, distribution, and frontline‑worker workflows before finalizing the model.
Leverage existing digital public infrastructure (e.g., Aadhaar, UPI, NICSHAY, state education portals).
Frontline usability matters – tools must make life easier for health workers/teachers; otherwise adoption stalls.
2.6 Q & A: South‑South Transferability
Ankur prompted Sunil to discuss how Wadhwani AI’s Indian experience could be exported.
Sunil described inquiries from Kenya, Rwanda, Ethiopia, Indonesia, Egypt, Mexico; his organization has begun capacity‑building (training civil servants, data‑governance workshops) and deployment teams (~100 staff).
Goal: impact 500 million people globally by 2030, building on the 100 million currently served in India.
3. Gates Foundation Perspective
Ankur announced the “Advantage India for AI” pledge: a new funding stream that invests in AI solutions originating in the Global South and supports their diffusion to other low‑resource regions.
He highlighted recent Gates‑funded projects in Ethiopia, Rwanda, Kenya, underscoring a commitment to South‑South partnership.
Sovereign AI models trained on Indian data, openly shareable with Global South partners.
Data Ecosystem
Standards for data governance, pipelines, and sharing across ministries.
Digital Public Infrastructure (DPI)
Aadhaar, UPI, NICSHAY, state education portals – act as “rails” for AI applications.
Startup & Innovation Hub
~900 AI‑focused startups showcased at the summit; African Village exhibit highlighted cross‑border use cases.
7.3 International Cooperation
Announced the National Institute of Smart Governance’s International Cooperation Centre, dedicated to helping other nations replicate India’s DPI‑based AI roll‑outs.
Confirmed willingness to share models, datasets, and compute platforms with partners in Africa, Latin America, and elsewhere.
7.4 Closing Remarks
Emphasised that democratizing AI—opening the “rooms” to youth, researchers, and civil society—was a core summit achievement.
Re‑iterated commitment to ongoing collaboration with the Gates Foundation, Smart Africa, Qhala, EkStep, and other partners.
8. Closing Reflections from Panelists
Sunil Wadhwani: AI’s rapid pace mirrors traffic in Delhi; patience and persistence are required.
Shikoh Gitau: The diverse audience in India reinforced the belief that the Global South can shape the AI narrative, moving from a “two‑horse race” to a “multiple‑horse race.”
Lacina Koné: Envisioned a single digital market for Africa, inspired by India’s multilingual, multicultural regulatory environment.
Shalini Kapoor: Highlighted the “100 pathways to 2030” coalition as a visual of collaboration over competition.
Ankur Vora: Thanked all participants and underscored the summit’s role as a launchpad for South‑South AI partnerships.
Key Takeaways
Government partnership is the cornerstone of scalable AI: All successful Indian case studies (TB, early‑grade reading) were embedded in national platforms (NICSHAY, state education portals).
Design for scale from day one: Front‑line usability, training, and integration pathways must be planned before model finalisation.
Digital public infrastructure (DPI) acts as “AI rails”: Aadhaar, UPI, NICSHAY, and state education systems enable rapid, low‑cost deployment across billions of users.
South‑South collaboration converts “pilot” into “policy”: Shared challenges (multilingualism, data scarcity, financing) make knowledge‑exchange between India, Africa, and other regions highly synergistic.
The Africa AI Council and Smart Africa illustrate continent‑wide governance: A blend of government ministers and private sector leaders ensures policy alignment and investment mobilization.
Funding models must de‑risk early‑stage AI: Philanthropy should back the “collaboration tax” (coordination costs) while private capital scales proven solutions.
The Gates Foundation’s “Advantage India for AI” pledge will channel resources to AI projects that originate in the Global South and are ready for cross‑regional diffusion.
India’s AI Mission offers a replicable, low‑cost model (compute, sovereign models, datasets) that can be exported to partner nations under the new International Cooperation Centre.
Inclusive, open‑access AI ecosystems empower youth and civil society: The summit’s emphasis on open rooms and diverse participation signals a shift from elite‑only AI to democratized AI for development.
Future vision: By 2030, the Global South aims to impact 500 million lives through AI, leveraging the “100 pathways” framework, shared DPI, and robust South‑South networks.