Building Scalable AI Through Global South Partnerships

20 Feb 2026 11:00h - 12:00h

Session at a glance

Summary

This discussion focused on leveraging artificial intelligence for social impact in the Global South, with particular emphasis on India’s AI initiatives and South-South collaboration. Sunil Wadhwani from the Wadhwani Institute for Artificial Intelligence shared how his organization transformed its approach to AI implementation after initially struggling to scale solutions. The key breakthrough came from working directly with government from day one, integrating AI solutions into existing digital public infrastructure platforms, and ensuring tools make life easier for frontline workers like health workers and teachers.

Wadhwani highlighted two major success stories: a tuberculosis detection system using smartphone-based cough analysis that increased TB detection rates by 25% nationally, and an AI-powered reading proficiency tool now mandatory for 3 million school children in one Indian state. The organization learned that sustainable impact requires government partnership, thinking about scale from the beginning, and leveraging existing digital infrastructure rather than building from scratch.

The panel discussion, moderated by Shalini Kapoor, explored pathways for South-South collaboration in AI diffusion. Lacina Kone from Smart Africa emphasized that collaboration is essential, noting Africa’s creation of an AI Council with 49 countries to avoid reinventing solutions already developed elsewhere. Shikoh Gitau from Kenya stressed the need to make AI a political and economic priority, introducing the concept of “collaboration tax” – the effort required to work together effectively.

Secretary Krishnan from India’s Ministry of Electronics highlighted the summit’s achievement in democratizing AI access and announced India’s commitment to sharing its AI infrastructure and models with other Global South nations. The discussion concluded with participants expressing optimism about multi-country collaboration in AI development, moving beyond a “two-horse race” to include diverse Global South perspectives and solutions.

Keypoints

Major Discussion Points:

– AI for Social Impact in India: Sunil Wadhwani detailed how the Wadhwani Institute developed AI solutions for critical challenges like tuberculosis detection (using cough analysis via smartphones) and early childhood reading proficiency, emphasizing the journey from innovation to scaled implementation affecting over 100 million people.

– Key Lessons for Scaling AI Solutions: The discussion highlighted essential learnings including the necessity of government partnership from day one, thinking about scale from the beginning, integrating with existing digital public infrastructure platforms, and ensuring solutions make life easier for frontline workers (teachers, health workers) to drive adoption.

– South-South Collaboration and Knowledge Transfer: The conversation explored how AI solutions and frameworks developed in India can be shared with other Global South countries, with specific examples of expansion to Rwanda, Ethiopia, and Kenya, emphasizing mutual learning rather than one-way technology transfer.

– Digital Public Infrastructure as an Enabler: Secretary Krishnan and other speakers emphasized India’s DPI model as a foundation for AI democratization, including compute infrastructure available at one-third global prices, sovereign AI models, and frameworks that can be shared with other nations.

– Building Collaborative Pathways: The panel discussed the “100 Pathways to 2030” initiative and the importance of reducing “collaboration tax” – the effort and resources needed for countries to work together effectively, with Smart Africa’s continental approach as a model for regional cooperation.

Overall Purpose:

The discussion aimed to showcase how India’s AI innovations and digital infrastructure can serve as a model for Global South collaboration, emphasizing practical pathways for scaling AI solutions across similar socio-economic contexts while fostering mutual learning and knowledge sharing.

Overall Tone:

The tone was consistently optimistic and collaborative throughout, with speakers expressing enthusiasm about successful implementations and future partnerships. There was a celebratory atmosphere reflecting on the week’s summit achievements, combined with practical, solution-oriented discussions about overcoming challenges. The conversation maintained a spirit of shared purpose and mutual respect among Global South nations, with occasional light moments (like jokes about traffic) that kept the discussion engaging and human-centered.

Speakers

Speakers from the provided list:

– Ankur Vora – Role/Title: Not explicitly mentioned, but appears to be moderating the discussion and mentions giving speeches about AI democratization

– Sunil Wadhwani – Co-founder of Wadhwani Institute for Artificial Intelligence in India (launched with his brother in 2018), former board member of Carnegie Mellon University, expertise in AI for social impact, healthcare, and education

– S. Krishnan – Secretary, Ministry of Electronics and Information Technology (MeitY), Government of India, expertise in digital public infrastructure and AI policy

– Shalini Kapoor – Chief Strategist, XSTEP Foundation, expertise in AI diffusion and South-South collaboration

– Lacina Kone – Director General and CEO of Smart Africa, expertise in digital transformation and AI governance across African countries

– Shikoh Gitau – CEO of Kala, expertise in AI applications and Global South collaboration

Additional speakers:

None – all speakers mentioned in the transcript are included in the provided speakers names list.

Full session report

This comprehensive discussion at the AI summit explored critical pathways for leveraging artificial intelligence to address social challenges across the Global South, with particular emphasis on India’s pioneering initiatives and the potential for South-South collaboration. The conversation brought together key stakeholders including Sunil Wadhwani from the Wadhwani Institute for Artificial Intelligence, Secretary Krishnan from India’s Ministry of Electronics, and representatives from African nations to examine both successes and challenges of scaling AI solutions for societal impact.

From Innovation to Impact: The Wadhwani Institute’s Journey

Sunil Wadhwani’s presentation provided a compelling case study of transformation in AI implementation. The Wadhwani Institute for Artificial Intelligence, co-founded by Sunil and his brother Ramesh and inaugurated by Prime Minister Modi, launched in 2018 when AI was not yet mainstream. Despite strong technical capabilities, the institute initially struggled to achieve meaningful scale, highlighting a fundamental truth: having excellent AI technology is merely the starting point for creating sustainable social change.

The institute’s breakthrough came through systematic re-evaluation, leading to three critical insights. First, government partnership from day one is essential for achieving scale. Rather than developing solutions in isolation, successful AI implementation requires deep collaboration with government stakeholders from initial problem identification. Second, integration with existing digital public infrastructure platforms is crucial for deployment. India’s robust digital infrastructure provided the foundation for scaling AI solutions. Third, AI solutions must genuinely make life easier for frontline workers to ensure sustainable adoption. As Wadhwani emphasized, “You can push all you want from the top that, oh, you must use this, but there’s got to be pull. They’ve got to want to use it.”

This transformation has yielded remarkable results. The institute now impacts over 100 million people annually through more than 25 AI platforms in partnership with government, with a goal of reaching 500 million people by 2040. Operations are expanding internationally, starting this month in Rwanda, Ethiopia, and Kenya.

Transformative Applications in Healthcare and Education

The institute’s work on tuberculosis—the world’s largest infectious disease killer—demonstrates AI’s potential to address complex diagnostic and treatment challenges. Starting three years ago, the team developed a comprehensive approach targeting multiple pain points: smartphone-based cough analysis for instant diagnosis, automated sputum analysis reducing laboratory processing time, and predictive algorithms identifying patients at risk of discontinuing treatment.

The tuberculosis detection system using smartphone-based cough analysis represents a particularly innovative breakthrough, providing instant risk assessment without requiring expensive equipment. This technology has become the national standard in India and contributed to increased TB detection rates. The solution addresses a critical need in economically vulnerable communities where TB is most prevalent.

In education, the institute tackled high dropout rates among children in grades 1-5 throughout the Global South. Their research identified reading difficulties as the primary driver of educational failure. Children who struggle with reading face difficulties across all subjects, leading to frustration and eventual dropout. The AI-based reading proficiency tools provide personalized assessment and targeted interventions, with one state government making the solution mandatory for all 3 million school children in the relevant age group.

South-South Collaboration and Continental Frameworks

Lacina Kone from Smart Africa provided insights into continental-scale collaboration, emphasizing Africa’s strength in viewing the continent as a unified market of 1.4 billion people rather than fragmented countries. This perspective led to creation of the Africa AI Council, with 49 countries signing a declaration on April 4th, 2025, to coordinate AI development efforts. The council has 15 members, including seven ministers from different countries and eight private sector representatives.

The Smart Africa approach recognizes that Global South countries face similar challenges and share similar values, making collaboration both practical and philosophically aligned. The AI Council operates through six thematic groups covering computing infrastructure, data sets, skills development, regulation and governance, market development, and investment mechanisms.

Kone introduced a framework for understanding development challenges, arguing that “finance is not the issue” but rather ecosystem conditions that enable investment. Using the metaphor of rain and clouds, he explained that financing flows naturally when the right conditions exist—specifically, regulatory certainty and conducive business environments.

Shikoh Gitau from Kenya referenced the concept of “collaboration tax”—originally from CV Madoka from CBC—describing the effort, resources, and bureaucratic overhead required for countries to work together effectively. This framework helps quantify hidden costs of international cooperation and highlights the need for systematic approaches to reduce collaboration barriers. Gitau emphasized that AI must become a political and economic priority to achieve the political goodwill necessary for meaningful cooperation.

India’s Democratic AI Model and Global Commitments

Secretary Krishnan provided context about India’s broader AI strategy and commitment to Global South cooperation. The summit itself demonstrated “democratic AI”—opening access to diverse participants rather than limiting discussions to elite groups. This reflects India’s philosophy of making AI accessible and beneficial for all segments of society, embodying the summit’s theme of “people, planet, progress” with “manna” (people) at the heart of AI, as emphasized in Prime Minister Modi’s address.

India’s AI mission offers several innovations for global sharing. The country has created compute infrastructure available at one-third of global prices through government subsidization, developed sovereign AI models using taxpayer resources that can be freely shared, and established frameworks for data governance. These resources are being made available to other Global South countries as part of India’s South-South cooperation commitment. The National Institute of Smart Governance is creating a center for international cooperation to facilitate this sharing.

The summit showcased India’s vibrant AI ecosystem, with 900 startups represented in the expo halls, demonstrating the breadth of innovation occurring across the country with its 22 official languages and diverse contexts.

Systematic Scaling and Knowledge Transfer

Shalini Kapoor’s moderation introduced the concept of AI diffusion, drawing parallels to how electricity—another general-purpose technology—spread globally despite being invented in specific locations. The “100 Pathways to 2030” initiative represents an attempt to create systematic knowledge sharing, documenting successful AI implementation routes so other countries can learn from proven approaches.

The pathway concept recognizes that successful AI implementation involves much more than technical development. It requires understanding regulatory environments, building institutional capacity, training frontline workers, creating sustainable financing mechanisms, and developing governance frameworks. By documenting these comprehensive pathways, countries can accelerate AI adoption while avoiding common implementation challenges.

Challenges and Future Directions

Despite significant achievements, several challenges require ongoing attention. The collaboration tax highlights real costs and complexities of international cooperation, even among countries with shared interests. Regulatory harmonization across diverse legal systems remains challenging, particularly for initiatives like Smart Africa’s goal of creating a single digital market across 49 countries.

Investment mechanisms and funding structures for large-scale AI deployment in resource-constrained environments remain incompletely resolved. While India’s model of government-subsidized compute infrastructure offers one approach, replicating this requires significant public investment and technical capacity that may not be immediately available in all Global South countries.

Conclusion

The discussion concluded with optimism about AI’s potential to drive meaningful social change across the Global South, combined with realistic acknowledgment of the systematic work required. The conversation moved beyond celebrating technical achievements to examining institutional, political, and collaborative frameworks necessary for sustainable impact.

The speakers demonstrated consensus on key principles: the necessity of government partnership, the importance of user-centric design, the value of South-South collaboration, and the need to democratize AI access. Their shared vision positions the Global South not as a recipient of technology developed elsewhere, but as an active participant in shaping AI development to address developing nations’ challenges and priorities.

The summit’s achievement in bringing together diverse stakeholders represents a model for how AI development can be democratized and made more inclusive. This represents a shift from a “two-horse race” in AI development to a “multiple-horse race” that includes diverse Global South perspectives and solutions. The commitments made—from India’s pledge to share AI infrastructure and models, to expanding successful solutions to new countries, to launching collaborative initiatives—provide concrete next steps for translating insights into action.

Session transcript

Ankur Vora

The first question around India. One of the things you’ve done and your organization has done is you found ways of taking the power of AI, democratizing it, and making sure it solves problems that we all care about. In my speeches, I’ve talked about you. I’ve talked about oral reading fluency, the tool whereby for less than, and if I’m stealing your thunder, sorry, but he’ll tell you a little bit more. But I’ve been talking about it because it’s just amazing. I’ve been talking about the fact that your TB screening, you can do things that we couldn’t imagine being done before. So can you tell us more about your work in India?

Sunil Wadhwani

Sure. Hi, everyone. Thank you. Welcome. Thanks for being here. Thank you for having me. I suspect the way I got over here was they needed, Gates Foundation needed someone for this chat. They looked around. They found this guy wandering around with two badges. They figured that means he’s important. Let’s get him. And next thing I’m sitting over here. But thank you so much, Ankur. So, you know, my brother and I launched the Badwani Institute for Artificial Intelligence here in India about eight years ago, 2018. Back then, AI wasn’t a thing. ChatGPT hadn’t come out. But I happened to be serving on the board of trustees of Carnegie Mellon University in the U.S., where I had studied, gotten my master’s.

So and CMU was ranked then as ranked number one in the world for artificial intelligence research and teaching. So being on the board, I could see all the billions of dollars coming into AI from Google and so on and so forth, even in those days. And it always pained me that none of this money was going into AI for society. You know, three, four billion people in the world out of eight billion don’t have access to decent health care, decent education. AI could be transformative. And that’s what we’re talking about today. But at that time, nothing was going on. So I spoke to my brother Ramesh. We decided, let’s launch this Institute for AI in India.

Prime Minister Modi came, inaugurated it, etc. So we hired a really good team of AI machine learning people, spoke to government, identified use cases, started working, and nothing happened. A couple of years went by, we were developing this, what we thought was really neat stuff, but it wasn’t scaling up. So we took a look at the issues, etc. And then we started realizing, look, we’re not approaching it quite right. We’ve got great AI solutions, but there is a lot more, a lot more to actually having impact than just having a nice technical solution. So I’ll, in a couple of minutes, tell you what we’re doing. So the key lessons that we’ve learned. But once we started figuring out, OK, what we were not doing and that we needed to be doing, then things started happening.

So just to give you two or three examples, as Ankur mentioned, we identify our problems, our challenges that we want to focus AI on by working directly with government. We talk to the health ministry about their national priorities for the next three, four, five years. What should we do? We talk to the education ministry and so on. So three years ago, the health ministry told us that tuberculosis is a very high priority for us. It’s the largest infectious disease killer in the world, kills close to two million people a year. Largest infectious disease killer in India kills close to half a million people over here. And for each person that dies, there are 20 others that don’t die, but they live miserable lives and they are infecting lots of other people as they go on.

So the government, the health ministry said, can you help? So we took a look at the whole. cascade of care in tuberculosis? What’s the patient journey like? Where are the three or four or five key pain points? And we identified, okay, diagnosis is number one, because in these economically vulnerable communities where TB happens, you need x -ray machines, you need sputum analysis, and in these communities, you don’t have all this stuff. You don’t have x -ray machines that work and are calibrated and so on. Problem number one. Problem number two, sputum analysis is another way of diagnosing TB, but these samples go to 64 government labs around India where they are ranulized, et cetera, and it takes time for the results to come back to the patient.

And for those that have TB, you’ve lost a lot of valuable time. Third big challenge is there’s a number of patients with TB who are on the medication regimen, but these are very toxic medicines. They really destroy your body while they’re trying to cure you of TB. So a lot of people stop taking these medicines. and they developed drug -resistant TB, which is much worse, 50 % mortality rate, etc. So we started applying AI to each of these issues. On the diagnosis, we’ve come up with a way of detecting tuberculosis from the sound of a cough into a smartphone. It’s instant. It’s quick. We don’t just say yes or no. We give the risk of this person having TB, what’s the probability, etc.

That is now rolling out nationally, and it is becoming the national standard. And by the way, we’re the only country that has this. It doesn’t exist anywhere. World Health Organization has told us this could be a game changer globally. For the sputum analysis, we’ve developed an AI model. So now the sputum analysis in the 64 government labs, totally automated. Results come out within a day, go back to the patient, treatment starts. Perhaps the most challenging thing. These patients who will fall off their medication. We’ve developed AI algorithms that predict well ahead of time which TB patients are likely to fall off the medication. So then the 2 ,000 TB caseworkers in India, which is a very limited number for 4 million TB patients, they can focus on the right people.

This is impacting now tens of millions of people. Just in the last year, the rate of TB detection, thanks to our cough against TB, has gone up by 25%. You may think that’s bad news, you know, higher numbers, but now we can treat these patients. We can get them on the right, you know, clinical care protocols. That’s one example. Education. Throughout the global south, there is a very high dropout rate of young children from schools, very high, in grades 1 through 5. Problem in India, problem everywhere. We got a call from a very large state government in India that said, we’ve got this issue, can you help? We sent a team in. We’ve got a call from a very large state government in India that said, we’ve got this issue, can you help?

and we had to analyze what’s causing this high dropout rate. We learned that the single biggest reason for this high dropout rate is an inability of these very young children, 7, 8, 9 years old, to be able to read If you can’t read, it affects how you do in every subject, right? Science, history, geography, you struggle, you start failing, you get frustrated, and these are, again, poor communities. Your parents say, forget school, what’s the point? Come work in the field or work in the kitchen, and that affects the rest of their lives. We’ve come up with an AI -based suite of tools that… …and for the child that goes to the teacher, and for the child, we come up with personalized exercises… stories that they can read at home, but which help them to get better at their specific area of weakness.

Each child is different. We were in pilot with the state. They were so impressed, they made it mandatory for all 3 million school kids in that state, in that age group. State of Rajasthan saw it recently. Here, in that age group. So that’s the kind of scale one can get. What’s the difference between what we were not doing in our first 2 or 3 years versus what we’re doing now? What we learned is, number one, the only way to scale is government. You have to work with government from day one. Working with government isn’t easy, right? It’s easy to say it’s challenging, it can be frustrating at times. but you have to understand how to navigate it.

How do you work with senior civil servants? You know, start with an, you know, approach them with humility, not like you have the answers. You’re trying to understand the problem. You want to work with them. Secondly, think scale from day one. You can’t develop an AI solution and then say, oh, I want to use it on one million people. There are issues you have to think in right in the beginning as to how will the scale out? How will large scale training happen in the field? How will frontline health workers or, you know, teachers or other governments? How will they use this? So thinking that way is very upfront. And in fact, with government, what we do now is once we identify a problem, even before we work on the technical solution, we plan that deployment to scale as to what will happen.

And we make government accountable for a lot of it. Just as we’re accountable for the technical side. The other really key learning has been. And that government, and this relates, Ankur, to what you were just saying, has developed a lot of digital public infrastructure. Aadhaar is like the great example that we’re all aware of, right? UPI, United Payment Interface, incredible example of that. So there are lots of things in health care, in education and agriculture where the government has developed this digital public infrastructure. And it’s critical. We didn’t know this. This was probably our key finding. It’s critical to find a government platform that you can integrate into. So the examples I’ve given of TB, government has a wonderful platform called Nikshay.

It’s like a case management system for tuberculosis patients. We’ve integrated everything. We developed algorithms into that platform. The education, this early childhood reading proficiency, each state has a platform. Rajasthan, as an example, has a platform called Rakshak. Rakshak for 70 ,000 schools, 400 ,000 teachers, 8 million students. we plugged our algorithms into that platform. So if these platforms hadn’t been there, we’d be struggling to scale any of this up. The final learning that we’ve had, and maybe this is the most important, is all these technical solutions are great at a macro level to bring down TB, to improve reading proficiency, etc. But at the end of the day, if the person using this tool, the frontline health worker, the teacher, if it doesn’t make life easier for them, in addition to improving education for the child or healthcare for the patient, it won’t happen.

You can push all you want from the top that, oh, you must use this, but there’s got to be pull. They’ve got to want to use it, and that happens only when you make life easier for them.

Ankur Vora

Thank you very much, Sunil. We’ll do the next question a little bit quickly. But I do want to just… acknowledge a few things, call out a few things. One is this journey between innovation and impact. I love what the learnings you talked about, because we keep on sometimes focusing on the innovation part, and we think that the road from innovation to impact is a straight road, and it’s not. It’s possible, it’s probable, but it’s not guaranteed, and we need to work hard at it. And so your learnings get to it. It’s also one of the reasons why we love our seven -year partnership, and hopefully it’ll be much more as we think about, as some of you know, the Gates Foundation yesterday announced a new initiative, a new pledge around AI for AI, which is Advantage India for AI.

And the idea is to make investments in India for the global south, and we’re looking forward to partnering with you. So, Sunil, one of the places where we do partner, and we’re talking about things, in fact, earlier today, we were talking about work in Ethiopia and Rwanda and Kenya. Can you talk a little bit more about… how you think about your work in the context of South -South partnership and how do you take the learnings you have from one place to the other place?

Sunil Wadhwani

Sure. So when we got started, our goal was only India, right? My brother and I, we are from India, our hearts are still here. So we weren’t thinking about any place else. But what’s happened is as our AI solutions have been scaling up in India quite dramatically, and we are today impacting over 100 million people a year, we’ve developed over 25 AI platforms in partnership with government. We’ve started over the last year getting a lot of inquiries from governments around the world in the global South saying what you’re doing in India, we need in Kenya or in Rwanda or in Indonesia or Egypt or Mexico. By the way, in India, we don’t just develop these solutions.

We also do a lot of capacity building, meaning training of senior civil servants on how you can use AI. What it’s good for, not good for, etc. We help ministries develop data governance standards, use case frameworks and so on. Then we do the actual solutions development. That’s the biggest chunk of what we do. But then we have a big deployment team. We have close to 100 people making sure that these things get deployed. So we were thinking only India. But over the last year, we started getting all these inquiries. And we finally said, look, we set up this foundation to have impact globally. So now we’ve we’ve have we sent a team out to Africa to meet with several countries.

We are starting operations this month in Rwanda, Ethiopia and Kenya. And I’m glad to see a colleague over here from Smart Africa. We will be partnering in this work. We’re very excited about that. And then beyond that, we expect to be going to a number of other places today. As I said, we’re impacting maybe 100 million people in India. Our goal is by the year 2040. To be impacting 500 million people. We are very excited about our partnership with you at the Gates Foundation. So the Prime Minister Modi, if you heard him yesterday in his speech, he gave a brilliant speech. As part of that, he said he said for the last several years, I’ve been saying make in India for the world.

He said, no, I want to add to that in this age of AI design in India for the world, develop in India for the world and then deliver these solutions to the world. And that is what we’re trying to do. That’s the evolution now thinking. And again, we’re excited, very excited about the partnership with you.

Ankur Vora

Thank you, Sunil. Are we I think we have a change of plans. Thank you so much. And Sunil, if you could please stay on stage and if I could invite our panel up. Shalini Kapoor, Chief Strategist from the XSTEP Foundation. Lacina Kone, Director General and CEO of Smart Africa. And Shikoh Gitau, CEO of Kala. Thank you.

Shalini Kapoor

yeah good good to start okay thank you so much thank you anchor. Thanks for your time uh and here we are and thanks uh Sunil for you know spending some more time with us, uh thanks Shikoh we have been meeting bumping into each other and thanks thanks Lacina thanks for being here So we’ll get into some of the discussions on the South -South collaboration that is spurring innovation and that is diffusing AI into all the sectors. AI diffusion is about the routes and the rails which need to be laid in AI the similar way digital rails were laid in the DPI time. And now they can be shared. They are playbooks. They can be shared.

And AI diffusion actually concept came from it started with generation. Jeffrey Hinton talking about it. He’s a professor in Georgetown in D.C. When he talked about that, how actually electricity was created in. Germany, but it was diffused across India, across the USA, where USA made so much of strides into it. So like electricity, AI is a general purpose technology. It’s a GPT, which is there. And between invention and impact, there’s a big layer of adoption and diffusion, which needs to be there so that AI gets diffused into society. And when it gets diffused into society, something which can be built in Kenya can come to India, something which is built in India can go to Kenya, because there are playbooks which could be leveraged.

Not everybody needs to build everything. Not everybody needs to build the entire stack. How do we learn from each other? And how does that South -South collaboration happen? That’s what is the focus. So I’ll start with the pathways. What are the pathways to scale? and I’ll start with Lesina, that you are leading Smart Africa and you help coordinate across a lot of nations, different stages of AI, somebody in pilot, somebody in production, somebody has solved data, somebody has solved language, somebody has solved voice AI. What do you think are the opportunities for the South -South collaboration in building these pathways together?

Lacina Kone

Yeah, thank you very much for inviting me. In fact, that collaboration, first of all, before we even talk about South -South, the collaboration is a sense of the creation of a Smart Africa. Because if you look at Africa through just on the Kenya, which is 50 million, Ghana, which is 30 million, or Nigeria, which is 240 million, you’re missing the point. But if you look at Africa as a 1 .4 billion people, but be able to leverage that 1 .4, you need a collaboration. and the scale. So coming from that, when you look at the continent of Africa, which is technically speaking the global south, I don’t want to get there, in the global south, and the south -south collaboration is very important because we do not need to reinvent the wheel.

India has shown the world what the DPI actually means for 1 .4 billion people. It’s working digital ID, a country which is able to organize an election for 850 million people to vote. You have to actually kudos. So we don’t need to reinvent the wheel. Africa can learn a lot from India, even with the use cases. But why use cases particularly? Because there’s a lot of similarity between India and Africa in terms of culture, in terms of value, that we all know we are into the AI, we are into digital transformation. It’s not just… You create a… But the luxury of the luxury of the society is to be able to have a population, inclusion of the population, ethical of the technology, exactly.

So coming from that, that’s one of the reasons to reboost, actually, Smart Africa Initiative. The creations of the Africa AI Council came into play where last April, on April 4th, 2025, 49 countries came together to actually sign the declaration. And subsequent to that, the AI Council came to life on November 12th, 2025 in Guinea after our board of directors, which are represented by the head of the state, announced that, accepted that we could. We had a first meeting already. Then the council consists of 15 members. is not only driven by public, but it has seven ministers coming from seven different countries and eight private sector members. Why? Because in our constitution of Smart Africa, private sector first.

We do believe that the government should be creating a conducive environment for the private sector to excel. It cannot be dominated by public sector. And underneath of the council, we have, of course, six thematic groups, mainly computing, so we can look at the collaboration of South Asian computing power. We can look at it in the data set. We can look at the skills. We can look at the regulation, which is the governance. We can look into the market and we can look at investment. And when it comes in terms of investment, something we need to know. The investments in the prior technologies, the investment cycle is too slow for the AI. Just look back 12 months ago.

Where were we? And where we are today? So this is something we need to look at carefully. We are looking at the three aspects. One, the government needs to be creating a conducive environment for private sector to chip in. The private sector needs to be executing, but they can only execute, as I said, everyone’s cry because they said finance is the issue. I always said finance is not the issue. Finance is the last thing you should think about. You know why? Because I said financing is like the rain. For rain to fall, you need certain condition of the cloud. Those clouds are the regulatory environment, the conducive environment for business private sector because private sector does not like unpredictability.

So the third thing, the philanthropics. The reason why I want to speak about it, the philanthropics need to serve as a 2D risk area because these are some of the things government is the last thing to invest in a technology because they want to make sure it’s going to work. But if you don’t throw business, it’s time for them to accelerate, to use that as a de -risking while the private sector can chip in and so on and so forth. Thank you.

Shalini Kapoor

Yeah, thank you so much. And you talked about DPI, you talked about the private sector, public coming together. It’s the entire ecosystem. And on 18th, actually, Mr. Nandan Hillikini actually announced 100 Pathways to 2030, which is a clarion call. If you ask me, it’s a clarion call for people to join to create pathways simply because, you know, if you climb Mount Everest, suppose Edmund Hillary has climbed Mount Everest. And do you think he’ll come back and he’ll say, I’m not going to tell you how I climbed? What is the route I took? Where did I go? Where did I go? Where did I not go? What did I see? He will talk about, right? He will talk about them so that it is easy for other travelers to come in.

So pathway is like that. that if someone has done the AI pathway, others should learn from it, benefit from it. So, Shiko, you were with us on the stage when you joined and you said that, you know, from the Global South, 100 Pathways to Scale, you would like to join us. Please tell us, how can that diffusion help? How can this, you know, we can work, collaborate to, you know, to get the AI use cases from pilot to production?

Shikoh Gitau

I can finish? Okay. It’s that collaboration. As I was saying, this idea of how do we bring this multiplicity of thinking together, given that we have the same exact challenges. We have challenges around, we have multiple languages. We have culture and diversity. We have things that we need to be able to work together. How do we collaborate together? And for us, the biggest takeaway is how do we make AI not just a technology, but a political and economical issue? Yeah? That was the biggest one, because the people are there. The builders were there. The researchers were there. The policy makers were there. But we need that political goodwill to be able to make this work together.

And something that CV Madoka from I’ve forgotten the organization. CBC said that struck really a chord to everybody including myself is we need to start having a conversation on what is called the collaboration tax and it’s something DG when we were coming in we were talking about I’ll define collaboration tax as this effort resources and things that you need to put together to be able to collaborate with each other. It’s what the government should be doing it’s what that political part of AI should be doing to bring the collaboration together and how do we make these people come together without the effort of I mean not the effort, the pain of collaboration and that’s what we need to be talking about because the resources, the people are there people are willing to collaborate and work together we saw it this week and as the minister said I said while you’re chasing the Guinness World Record of having the most number of people also chase for the diversity that these countries are seeing thank you so much for bringing Africa and the world to India Yeah.

Shalini Kapoor

Thank you, Shikoh. Thank you so much. We’ll take a small break in the panel discussion and we’ll have Mr. Krishnan come here and talk about how scale and collaboration can help in the South -South and what is transferable from India. I know he’s like busy and across all. So over to you, Mr. Krishnan.

Ankur Vora

I was just going to do one more thing, which is thank you, Shalini, and thank you to the panel for allowing us this small break. For those of you who don’t know, Secretary Krishnan from the Ministry of Métis is over here. He’s had probably one of the most amazing, successful weeks this week. So please join me and give him a big round of applause for. Secretary Krishnan, thank you so much for being here. As a proud Indian, I’m quite excited about the fact what happened this week. I’m also, as somebody who cares about the agenda of this global South. everything that happened in India this week put the Global South agenda right front and center.

So thank you for doing that. There were so many announcements made this week about how we’re going to make progress in the months and years to come together. Would love to welcome you to give a little bit more context of the announcements that were made and the achievements that were achieved this week. Thank you. Welcome.

S. Krishnan

Let me first apologize to the panel for having sort of stepped in abruptly, but between juggling many things going on across the summit, I think this is a very important session as far as I was concerned, because if this particular summit was about one thing, it was about the Global South. The fact that… India representing the Global South… could actually dare to host this event and also dare to host it on this scale. The one thing we were very clear about is summits thus far have basically been about country leaders. It’s been about CEOs and it’s been about some experts getting together in closed rooms and not really having the opportunity to do what or to actually showcase to people as to what the possibility of the technology is.

And this particular event gave us that opportunity. I think we were very clear that what we wanted to do was to let people into the rooms. We wanted to make sure that people, especially youth, had this opportunity to come and listen to the best minds, there are on artificial intelligence as technology. and to every possible perspective on how this technology can work for everybody. And the second thing, of course, as you’re well aware, we said people, planet, progress. And two aspects of it were very important. One was, or three, if I can. One is democratizing access to AI, all the AI infrastructure and resources. That was one key aspect. The second key aspect was including those who are not ordinarily given access to this, those who are excluded.

And the third key aspect is putting humans at the center of this process to make sure that this is a technology that works for people. And I think the prime minister was very clear and emphatic in his address yesterday where he put people, or manna, right at the heart of AI. So to enable this to happen, of course, multiple things have to happen. We have to find frugal ways to innovate. In order to make these resources available, we have to make sure that we have the resources. We believe that our own AI mission model, the India AI mission model, is one of those frugal ways in which both the compute infrastructure and the model infrastructure and the data set infrastructure can be created for each country because some of this needs to be on a specific basis for regions and for countries.

In India, we are a subcontinental scale. There are 22 official languages and many other languages which need to be taught or which need to be understood. And we understand this cultural and linguistic diversity better than any other region in the world. And we can, at a continental scale, we can contribute in that effort. That is one key element. The second key element, of course, is to create compute in a way so that it doesn’t, I mean, people are not enabled. I mean, people are not able to build moats. around it. That, you know, the implication that you need the kind of resources to do this, that nobody else can do it and only we can do it is not an approach we wanted to take.

So we created this model where the private sector is encouraged to invest. We created this model where access to it is something which the government subsidizes. In the process today, AI compute in India is available at a third of the price that it is available in the rest of the world. I think that has been the significant achievement. The United Nations asked us saying, would it be possible to, once you build it out on scale, would it be possible to share with the rest of the world? This is something that we have committed to them saying, as in when the size is adequate so that we can meet other requirements, we will be happy to share them.

We are happy to share the model even now. And the AI Kosh model, as we call it, the AI treasury is something that we are happy to share even now. we are happy to share the fact that the models that we have supported in India and which have been built out as sovereign models in India that again is technology that we are happy to share with the global south it’s something we can enable some of it is something we’ve built with our own resources so it is in a sense completely sovereign unlike in many other places it’s something that the government has paid for from taxpayer resources and we can use and the third element of course is the data sets and how they are shared now that framework is again something we can certainly share the most important thing and I think that’s what is also showcased so eloquently in the expo is the range of applications which have been created out of this and there are close to 900 startups across all those halls who have done a variety of things even in the main hall we with the Gates Foundation we have set up a lot of applications and we have set up a lot of applications and we have set up the African village which is such a showcase even to the leaders fundamentally about applications which can work there and fundamentally for people to see applications which have worked in different parts of the world which can be taken elsewhere.

So all of those are available. Those are resources which we want to share. These are resources we want to actually give. And most importantly, as I said, I think if there is one thing that this summit reflects, for the first time, we’ve actually democratized AI. We’ve shown you what democratic AI looks like when people are let into the rooms, when people are let into the halls and they can see for themselves as to how this would work. So it gives me immense pleasure that, you know, and a very, very key partner for us in all of this has been the Gates Foundation right from the very outset, right from the planning stage of how we wanted to do this.

This particular part of the set of sessions on the Global South is something, that we work closely with, curated carefully. We have put together sessions which will be relevant to this group, and we have always made sure that in addition to this, of course, on every occasion, whether it is in the space of DPI or whether it is in the space of any of the other applications, we are in a position to support it. Under one of our organizations, the National Institute of Smart Governance, we have now put in a center which is fundamentally focused on international cooperation so that they can actually provide support to other countries where DPIs are to be actually implemented, how to ground them.

And we believe that probably the most effective way of dealing with this is to actually be able to cooperate amongst ourselves. So. So that we are able to take it out. We are able to learn from each other. We are able to contribute to each other. And that is something we are now really ready to do. India knows what it is to be deprived of or denied technology. India knows what it is to actually try and work your way past it. We have managed to do that. We have managed to democratize it. We have managed to make it available to people at scale. We have tried to keep it open source. We have tried to protect it in a number of ways from cyber attacks in each of those areas.

So in this entire technology stack, there is experience. There is the way that we leapfrog different stages. So I think if we work together in the AI space, likewise, there is so much that can be accomplished. And we undertake as a nation, I think I can say with responsibility that we will have devices and we will have structures through which we can sort of deepen this cooperation. We can deepen the support. We can enable this in a number of ways and continue to stay engaged through the Gates Foundation, through the other institutions to actually make this happen. So thank you very much. Thank you to Gates Foundation for curating this particular event. And thanks to all of you for participating in this.

I mean, it’s one thing to arrange it, one thing to organize it. But another thing for all of you to actually come up here, put up with some of the inconvenience which would have been caused. India is not a very convenient country at best of times. but India is a country with spirit and India is a country which fixes things

Shalini Kapoor

Okay, we have some time with us. How much? Five minutes. And we need to have a question to Sunil. He has been working at, you know, so many interesting, I mean, I listened to the stories of Wadwaning AI. and they inspire you thoroughly. So Sunil, I’ll give it to you. I want people to hear your message that how can these work that has been done in India, how can it help Global South?

Sunil Wadhwani

So as Mr. Kone of Smart Africa said 15 minutes ago, the challenges that we have in the Global South generally, really Africa, India, other countries are similar. The values we have, more importantly, are very similar. The strengths that we bring to the table in terms of our talent, our youth, et cetera, are similar. So I think it’s mutual learning. It’s not one way. It’s not that we’ve developed great stuff in India that can just be, you know, taken over. It’s mutual learning on both sides. It’s a mutual sharing of ideas. There are lots of very good things happening in Africa and Asia. There are lots of things happening in Africa and Asia that we can learn from over here.

On the technology side, as you were saying, Shalini, we’ve been fortunate. We’ve had a government that is very pro -technology. There’s a tremendous range of digital public infrastructure that we can access in India that enables, that provides data pipelines. It provides digital distribution systems without which none of this AI can scale. There’s been a very clear regulatory framework for AI that’s been developed in India that really helps. And most important, there’s an openness in government. And I think it’s driven by the prime minister’s vision and belief that technology and AI can truly transform societal development. So those, to me, are the big things, more than individual AI solutions that really make a difference. And I see that happening in Africa in many countries.

Shalini Kapoor

Sure. Thank you so much. I think we are literally… We are literally at the eve of the summit getting over. It’s been a fantastic week. meeting the best of the people, listening to the best of the sessions, navigating the traffic, yes. But like Secretary Krishnan said that, you know, we fix everything. So I just want to have one last question to each of the panelists. What’s the best thing you liked of the summit? And to you, Sunil, first. I mean, one moment, one feeling that you will carry forward.

Sunil Wadhwani

I will give you a counterintuitive answer. AI is making the world move faster and faster and faster. And all the traffic challenges we’ve had over here are teaching us patience. You will get there. Things will happen. Life will go on.

Shalini Kapoor

Thank you so much. Shikol, what’s the one feeling you’ll travel back with, back to Africa?

Shikoh Gitau

I think my best moment is, and I’m going to pick and be selfish, in the moment in Oberoi when I stood and saw this diverse sea of faces, I think about 300 people, and we’re all celebrating like, we can do this as the Global South. This is happening in our TAF, and this belief that the Global South has something to offer into this AI conversation. So it’s no longer a two -horse race, it’s a multiple -horse race. Thank you.

Lacina Kone

For me, it’s, you know, our vision is to transform Africa into a single digital market. Coming here this time, it shows me already our future. Having 1 .4 billion people on the one regulation. How does it feel like? So you know what I’m talking about. That’s one of our obstacles, says regulatory harmonization in India, you do not have that. multicultural, you have a multicultural multilingual, you have multicultural what does it feel like, including the traffic in the morning as well of course thank you

Shalini Kapoor

And my best moment for the summit was that back in Oberoi on 18th evening, several partners across Italy, Kenya Anthropic, Google Carnegie ORF, Gates Aikstep stood next to Nandini, Kenya and we all came together for 100 pathways till 2030 and we all were together and we were not doing non -collaboration pictures which is going on in Insta, we were all together so it was AI is about collaboration not competition, that’s the theme thank you thank you really enjoyed thank you thank you thank you you are the best man you are the best it’s a pleasure more photos more photos Thank you. Thank you.

Sunil Wadhwani

Speech speed

162 words per minute

Speech length

Summit Reflections and Future Outlook

Topics

Social and economic development | Capacity development

Ankur Vora

Speech speed

92 words per minute

Speech length

584 words

Speech time

377 seconds

Innovation‑to‑impact journey is non‑linear

Explanation

Ankur points out that moving from an innovative AI solution to real‑world impact does not follow a straight line and requires sustained effort.

Evidence

“One is this journey between innovation and impact” [43]. “I love what the learnings you talked about, because we keep on sometimes focusing on the innovation part, and we think that the road from innovation to impact is a straight road, and it’s not” [44]. “It’s not one way” [45].

Major discussion point

Scaling AI for Social Impact in India

Topics

Artificial intelligence | Capacity development | Social and economic development

Shalini Kapoor

Speech speed

113 words per minute

Speech length

Summit Reflections and Future Outlook

Topics

Artificial intelligence | Social and economic development

Lacina Kone

Speech speed

159 words per minute

Speech length

Summit Reflections and Future Outlook

Topics

Digital economy | Closing all digital divides

Shikoh Gitau

Speech speed

152 words per minute

Speech length

South‑South Collaboration and AI Diffusion

Topics

The enabling environment for digital development | Capacity development

S. Krishnan

Speech speed

170 words per minute

Speech length

Government Partnership, Regulation, and Digital Public Infrastructure

Topics

Artificial intelligence | The enabling environment for digital development

Agreements

Agreement points

Government partnership is essential for scaling AI solutions

Speakers

– Sunil Wadhwani
– Lacina Kone
– S. Krishnan

Arguments

Government partnership from day one is essential for scaling AI solutions effectively

Private sector leadership is essential with government creating conducive environments for innovation

India’s AI mission provides compute infrastructure at one-third the global price through government subsidization

Summary

All speakers agree that effective AI scaling requires strong government involvement, whether through direct partnership, creating enabling environments, or providing subsidized infrastructure

Topics

Artificial intelligence | The enabling environment for digital development

South-South collaboration is crucial for AI development and deployment

Speakers

– Sunil Wadhwani
– Lacina Kone
– Shikoh Gitau
– S. Krishnan

Arguments

India’s AI solutions are expanding to Rwanda, Ethiopia, and Kenya with goal of impacting 500 million people by 2040

Africa needs collaboration to leverage its 1.4 billion population scale rather than viewing individual countries separately

AI must become a political and economic issue, not just a technological one, to achieve meaningful collaboration

India’s sovereign AI models and data frameworks are available for sharing with the Global South

Summary

All speakers emphasize the importance of collaboration between Global South countries, sharing resources, knowledge, and solutions rather than developing everything independently

Topics

Artificial intelligence | Information and communication technologies for development | The enabling environment for digital development

Digital public infrastructure is fundamental for AI deployment

Speakers

– Sunil Wadhwani
– S. Krishnan
– Shalini Kapoor

Arguments

Integration with existing digital public infrastructure platforms is critical for successful deployment

India’s sovereign AI models and data frameworks are available for sharing with the Global South

AI diffusion requires building routes and rails similar to digital public infrastructure development

Summary

Speakers agree that robust digital public infrastructure serves as the foundation for successful AI implementation and scaling

Topics

Artificial intelligence | Information and communication technologies for development | The enabling environment for digital development

AI should address societal challenges and be democratized

Speakers

– Sunil Wadhwani
– S. Krishnan
– Shalini Kapoor

Arguments

AI can be transformative for healthcare and education challenges affecting billions globally

The summit demonstrated democratic AI by opening access to diverse participants rather than limiting to elites

AI diffusion requires building routes and rails similar to digital public infrastructure development

Summary

All speakers advocate for AI that serves societal needs and is accessible to broader populations rather than being limited to elite groups or commercial applications

Topics

Artificial intelligence | Social and economic development | Closing all digital divides

Artificial intelligence | Financial mechanisms | The enabling environment for digital development

Unexpected consensus

Arguments

Private sector leadership is essential with government creating conducive environments for innovation

AI must become a political and economic issue, not just a technological one, to achieve meaningful collaboration

Summary

Kone emphasizes private sector leadership with government in a supporting role, while Gitau argues for stronger political engagement and leadership to drive AI collaboration

Topics

Artificial intelligence | The enabling environment for digital development

Unexpected differences

Approach to international collaboration mechanisms

Speakers

– S. Krishnan
– Shikoh Gitau

Arguments

The summit demonstrated democratic AI by opening access to diverse participants rather than limiting to elites

AI must become a political and economic issue, not just a technological one, to achieve meaningful collaboration

Explanation

While both support inclusive approaches, Krishnan focuses on democratizing access to AI knowledge and showcasing solutions, while Gitau argues this is insufficient without addressing the political dimensions and structural barriers to collaboration

Topics

Artificial intelligence | Capacity development | The enabling environment for digital development

Overall assessment

Summary

The discussion shows broad consensus on the importance of AI for Global South development and the need for collaboration, but reveals nuanced disagreements about implementation approaches, particularly regarding the balance between government, private sector, and political leadership roles

Disagreement level

Low to moderate disagreement level with high potential for convergence, as differences appear to be more about emphasis and sequencing rather than fundamental conflicts. The implications suggest need for integrated approaches that combine technical solutions, government partnership, private sector innovation, and political commitment to achieve effective AI collaboration in the Global South

Partial agreements

Both agree government involvement is crucial for AI scaling, but disagree on the nature of that involvement – Wadhwani emphasizes direct government partnership and integration, while Kone advocates for government creating enabling environments for private sector leadership

Speakers

– Sunil Wadhwani
– Lacina Kone

Arguments

Government partnership from day one is essential for scaling AI solutions effectively

Private sector leadership is essential with government creating conducive environments for innovation

Topics

Artificial intelligence | The enabling environment for digital development

Both recognize structural barriers to collaboration need addressing, but focus on different solutions – Kone emphasizes philanthropic de-risking while Gitau focuses on reducing collaboration overhead through political action

Speakers

– Lacina Kone
– Shikoh Gitau

Arguments

Philanthropic organizations should serve as de-risking mechanisms to accelerate AI adoption

Global South collaboration requires addressing ‘collaboration tax’ – the effort and resources needed for effective partnership

Topics

Artificial intelligence | Financial mechanisms | The enabling environment for digital development

Artificial intelligence | Financial mechanisms | The enabling environment for digital development

Takeaways

Key takeaways

AI solutions for social impact require government partnership from day one and integration with existing digital public infrastructure to achieve scale effectively

Successful AI implementation depends on making tools easier for frontline workers to use, creating pull rather than just push adoption

South-South collaboration offers significant opportunities as Global South countries face similar challenges and share similar values, enabling mutual learning rather than one-way technology transfer

India’s AI infrastructure model provides compute resources at one-third global prices and can be shared with other developing nations

The summit demonstrated ‘democratic AI’ by opening access to diverse participants rather than limiting discussions to elites in closed rooms

AI diffusion requires systematic pathway development and knowledge sharing, similar to how digital public infrastructure was built and scaled

Private sector leadership combined with government-created conducive environments and philanthropic de-risking mechanisms is essential for AI adoption

AI must be treated as a political and economic issue, not just a technological one, to achieve meaningful global collaboration

Resolutions and action items

India committed to sharing its AI mission model, compute infrastructure, and sovereign AI models with Global South countries

Wadhwani Institute expanding operations to Rwanda, Ethiopia, and Kenya starting immediately with goal of impacting 500 million people by 2040

Gates Foundation announced new ‘Advantage India for AI’ initiative for investments in India targeting Global South applications

India established National Institute of Smart Governance center focused on international cooperation for DPI implementation support

Launch of ‘100 Pathways to 2030’ initiative for collaborative AI implementation knowledge sharing

Africa AI Council with 49 countries committed to continental coordination through six thematic groups covering computing, data, skills, regulation, market, and investment

Unresolved issues

How to effectively address ‘collaboration tax’ – the effort and resources required for meaningful South-South partnerships

Specific mechanisms for regulatory harmonization across diverse Global South countries with different legal frameworks

Detailed implementation timeline and resource allocation for scaling AI solutions from pilot to production across multiple countries

How to balance sovereign AI model development with collaborative sharing and knowledge transfer

Specific funding mechanisms and investment structures needed to support large-scale AI deployment in resource-constrained environments

Suggested compromises

Mutual learning approach rather than one-way technology transfer, recognizing that all Global South countries have valuable contributions

Phased sharing of India’s compute infrastructure – meeting domestic requirements first, then expanding access to other countries as capacity grows

This analogy is intellectually valuable because it provides a historical framework for understanding AI adoption, drawing parallels to how transformative technologies have spread globally in the past. It emphasizes that the technical breakthrough is just the beginning of a longer societal transformation process.

Impact

This comment provided the conceptual foundation for the entire panel discussion on AI diffusion and South-South collaboration. It established the framework for thinking about AI as infrastructure rather than just applications, influencing how panelists discussed pathways, collaboration, and the systematic approach needed for global AI adoption.

Overall assessment

Explanation

While the initiative was announced, the specific implementation strategies, governance structures, and success metrics need further development

Disclaimer: This is not an official session record. DiploAI generates these resources from audiovisual recordings, and they are presented as-is, including potential errors. Due to logistical challenges, such as discrepancies in audio/video or transcripts, names may be misspelled. We strive for accuracy to the best of our ability.