Shaping the Future AI Strategies for Jobs and Economic Development

20 Feb 2026 18:00h - 19:00h

Shaping the Future AI Strategies for Jobs and Economic Development

Session at a glance

Summary

This discussion focused on AI-driven strategies for workforce and economic growth, examining how artificial intelligence will impact society, jobs, and industries globally. The panel brought together experts from various sectors including government officials from ASEAN, healthcare professionals, technology infrastructure leaders, and AI company executives to address critical challenges facing both developed and emerging economies.


A central theme emerged around collaboration rather than displacement of human workers. Panelists emphasized that AI should enhance and augment human capabilities rather than completely replace jobs, particularly noting that white-collar positions may face more immediate impact than blue-collar roles. The discussion highlighted significant infrastructure challenges, including the massive energy requirements for AI deployment, with projections suggesting the world will need four times more energy in the next 10-12 years to support data center growth.


Several speakers addressed the unique needs of emerging economies, particularly the 70 million MSMEs in India that employ 230 million people and contribute significantly to GDP and exports. The conversation explored how to make AI accessible and affordable for smaller companies that cannot afford enterprise-level solutions. Infrastructure bottlenecks were identified as major obstacles, including power supply, cooling systems, skilled labor shortages, and the need for both large-scale cloud data centers and edge computing solutions.


Healthcare applications received particular attention, with examples from countries like Guyana demonstrating how telemedicine and AI diagnostics can serve remote populations while maintaining the essential human element in patient care. The panelists concluded that continuous learning and upskilling will be essential for all workers regardless of age, as the rapid pace of technological change demands constant adaptation. The discussion emphasized that successful AI implementation requires collaboration between government, private sector, and educational institutions to ensure inclusive and sustainable economic growth.


Keypoints

Overall Purpose/Goal

This discussion was a comprehensive panel at the India AI Impact Summit focused on “AI-driven strategies for workforce and economic growth.” The goal was to explore how AI can be implemented responsibly across different sectors and regions, particularly addressing the needs of emerging economies, MSMEs (Micro, Small & Medium Enterprises), and the Global South, while ensuring inclusive and sustainable development.


Major Discussion Points

Workforce Transformation and Job Impact: A central theme throughout both panels was whether AI will replace or enhance human jobs. Panelists consistently emphasized “collaboration not displacement” and “enhancement not replacement,” particularly noting that AI’s current impact is more on white-collar jobs through collaborative augmentation rather than full automation. The consensus was that continuous learning and upskilling will be essential for workforce adaptation.


Infrastructure and Energy Challenges: Significant discussion around the massive infrastructure requirements for AI deployment, including the need for 4x more energy in the next 10-12 years and four trillion dollars annually for the next decade. Panelists addressed challenges in power, cooling, data centers, and the potential for edge computing versus cloud-based solutions, with particular emphasis on India’s advantages in renewable energy costs.


Global South Leadership in AI Governance: The second panel focused heavily on how developing nations can be “co-authors” rather than “passive recipients” of AI governance norms. Countries like Maldives, Cambodia, Brazil, and Indonesia shared their national AI strategies, emphasizing the need for context-specific approaches that address local realities, resource constraints, and institutional strengths.


Trust and Safety as Prerequisites for Scale: A major theme was that trust is not an afterthought but a foundational requirement for AI adoption at scale. Panelists discussed the need for transparent, auditable systems with built-in grievance mechanisms, and how financial services have succeeded due to existing trust architectures that can be applied to AI deployment.


Practical Applications and Leapfrogging Opportunities: Discussion of specific use cases where AI can provide immediate value, particularly in healthcare (telemedicine), agriculture, climate adaptation, and urban planning. The concept of “leapfrogging” was emphasized, where developing countries can gain second-mover advantages by adopting cloud-based AI solutions without massive infrastructure investments.


Overall Tone

The discussion maintained an optimistic yet pragmatic tone throughout. While acknowledging significant challenges around infrastructure, energy, skills, and governance, speakers consistently emphasized opportunities and collaborative solutions. The tone was notably inclusive and solution-oriented, with government officials, private sector leaders, and international organizations working together to address practical implementation challenges rather than dwelling on theoretical concerns. There was a strong sense of urgency balanced with careful consideration of responsible deployment practices.


Speakers

Speakers from the provided list:


Tejpreet S Chopra – Founder and CEO of Industry.AI, moderator of the first panel on AI-driven strategies for workforce and economic growth


Satvinder Singh – Representative from ASEAN, discussing the Digital Economy Framework Agreement (DEFA)


Dr. Mahendra Karpan – Interventional cardiologist and presidential advisor to Guyana, expert in healthcare transformation and telemedicine


Nihar Shah – Director of global cooling program at Lawrence Berkeley National Lab, expert in energy and climate issues related to AI infrastructure


Vinod Jhawar – Representative from Nextra (subsidiary of Airtel), expert in data center infrastructure and AI vertical development


Narendra Singh – MD of RackBank and NeveCloud, expert in cloud computing and space-based data centers


Dipali Khanna – Senior VP and Head of Asia for the Rockefeller Foundation, expert in development and philanthropic approaches to AI


Mohamed Kinaanath – Minister of State for Homeland Security and Technology from the Maldives, government official leading digital transformation


Son Sokeng – Under Secretary of State from Cambodia, government official working on AI readiness and national strategy


Eugenio Vargas Garcia – Tech Ambassador for Brazil, diplomat specializing in technology and international cooperation


Aju Widya Sari – Director of AI and Emerging Technology Ecosystems, Ministry of Communications and Digital Affairs, Indonesia


Kip Wainscott – Executive Director of Global AI Policy from JPMorgan Chase, expert in financial services AI governance


Parag Khanna – Founder and CEO of AlphaGeo, expert in geospatial AI applications for climate and urbanization


Moderator – Host of the second panel “Trusted AI at Scale: A Global South Leadership Dialogue” (advisor to AI Safety Asia)


Audience – Various audience members asking questions, including Harsh Vartan (research fellow background) and CTO at MindEquity.ai/founder of AI Society


H.E. Sokeng – Same as Son Sokeng, referred to with diplomatic title


Additional speakers:


None identified beyond the provided speakers names list.


Full session report

This comprehensive discussion at the India AI Impact Summit brought together government officials, technology leaders, healthcare professionals, and international development experts across two panel sessions to examine AI-driven strategies for workforce transformation and governance in emerging economies. The panels addressed fundamental questions about how artificial intelligence will reshape employment, infrastructure requirements, and governance frameworks, particularly in the Global South.


Workforce Transformation: Collaboration Over Displacement

The first panel revealed nuanced perspectives on AI’s employment impact that move beyond simple replacement narratives. Satvinder Singh from ASEAN emphasized that current AI deployment primarily affects knowledge workers through “collaborative augmentation rather than full automation.” This distinction proved central to reframing workforce discussions from fear-based concerns to strategic planning approaches.


Dr. Mahendra Karpan, speaking as both an interventional cardiologist and presidential advisor to Guyana, illustrated this principle through healthcare applications. He shared an anecdote about treating an 18-year-old snake bite victim from a remote village who had never seen car headlights, demonstrating how AI can bridge critical service gaps in countries facing severe specialist shortages while maintaining essential human elements for patient care and emotional support.


Tejpreet Chopra, founder and CEO of Industry.AI, stressed that rapid technological change demands lifelong adaptation, making traditional career models obsolete. The consensus emerged that continuous learning and upskilling will become essential across all sectors, requiring fundamental changes in educational approaches and the development of entrepreneurial cultures.


Infrastructure Challenges and Energy Requirements

Perhaps the most striking discussion concerned massive infrastructure requirements for AI deployment. Nihar Shah from Lawrence Berkeley National Lab presented data showing that data center growth has tripled over the past decade and is forecast to triple again by 2028. Chopra shared insights from a recent gathering of global CEOs in Abu Dhabi, where he learned that “the world will need four times more energy in the next 10-12 years” to support AI growth, requiring approximately four trillion dollars annually for the next decade.


Shah highlighted critical “blind spots” in AI infrastructure planning, particularly cooling systems and water consumption, which could prove as constraining as energy supply for developing nations. However, the panel also identified significant opportunities for India. Chopra shared his personal experience in renewable energy development: his first solar farm generated revenue at 18 rupees per kilowatt hour eight years ago, compared to 2.20 rupees today, with similar cost reductions in wind energy (from 8.50 rupees to 2 rupees per kilowatt hour).


Vinod Jhawar from Nextra detailed India’s infrastructure advantages, noting that data center construction costs 4-6 million dollars per megawatt in India versus 12 million dollars in markets like the US, Singapore, and Dubai. This cost advantage stems from India’s manufacturing capabilities, with 80-90% of required supply chain components produced domestically.


Digital Public Infrastructure and Regional Cooperation

Singh outlined ASEAN’s Digital Economy Framework Agreement (DEFA), which he described as “the largest regional digital agreement in the world,” connecting 700 million people across 11 countries. Significantly, he noted that data shows least developed countries within ASEAN will benefit most from this connectivity, challenging assumptions about digital transformation benefits.


This “leapfrogging” concept proved central to Global South AI strategy. Rather than replicating massive capital expenditure of developed nations, emerging economies can leverage cloud-based solutions and Digital Public Infrastructure models to achieve similar outcomes at lower costs. India’s approach, with over 50 countries building payment and identity systems on its DPI stack, provides a template for affordable, sovereign AI deployment.


The accessibility question extends to India’s 70 million Micro, Small & Medium Enterprises (MSMEs), which employ 230 million people. Chopra announced the development of what he called the world’s first AI supercomputer for manufacturing, priced at 6.5 lakh rupees, representing efforts to bring enterprise-grade AI capabilities to smaller companies.


Global South as AI Governance Co-Authors

The second panel session, moderated by an AI Safety Asia advisor, explicitly positioned Global South countries as “co-authors” rather than “passive recipients” of AI governance norms. This framing proved crucial in moving beyond imported templates to locally-relevant governance approaches.


Minister Mohamed Kinaanath from the Maldives provided a compelling case study of how small island developing states approach AI as a matter of “institutional resilience” and “survival.” The Maldives’ unique geography—1,200 islands spread across vast ocean distances—creates challenges that AI can uniquely address through their “Maldives 2.0” digital transformation agenda.


Cambodia’s Under Secretary Son Sokeng outlined their UNESCO-supported AI readiness assessment and national strategy development, emphasizing human-centric governance frameworks. Their ambitious goal includes developing 100,000 AI-ready talents over ten years alongside training 10,000 government officials in digital skills.


Brazil’s Tech Ambassador Eugenio Vargas Garcia emphasized the importance of “tech diplomacy” for Global South countries. He provided three practical recommendations: starting with small-scale projects, seeking international partnerships, and engaging actively in global discussions to ensure their voices are heard in international forums.


Trust as Foundational Infrastructure

A fundamental insight emerged that trust must be designed into AI systems from inception rather than retrofitted later. Dipali Khanna from the Rockefeller Foundation articulated this principle: “Trust must be designed from day one, not retrofitted after deployment. Transparency, auditability, grievance redress, open architecture are not compliance burdens. They’re adoption accelerators.”


Kip Wainscott from JPMorgan Chase provided the financial services perspective, noting that their industry’s early AI adoption success stems from existing trust architectures. As one of the world’s largest AI deployers with a $20 billion annual technology budget, JPMorgan Chase demonstrates how robust governance frameworks enable rather than constrain innovation.


Practical Applications and Development Impact

Dr. Parag Khanna from AlphaGeo introduced the concept of “second-mover advantage” for developing countries, arguing that later AI adoption can provide cost savings while delivering superior outcomes. His focus on geospatial AI applications for sustainable urbanization and climate adaptation highlighted practical use cases where AI addresses existential challenges facing the Global South.


Dr. Karpan’s experience in Guyana showcased telemedicine’s potential, with over 200 functional telemedicine sites equipped with Starlink connectivity demonstrating how AI-enabled healthcare can reach previously underserved communities while maintaining human oversight.


Economic Viability and Sustainability Challenges

The discussion revealed significant economic challenges in current AI deployment. Narendra Singh from NeveCloud highlighted a critical problem: “Today you spend $2 and you generate $1 because half of the 50% goes to the AI chip company.” This cost-revenue imbalance threatens AI viability, particularly for developing countries with limited resources.


Singh’s call for indigenous AI chip development addresses technological sovereignty concerns, while his mention of space-based data center initiatives represents innovative approaches to infrastructure challenges. The sustainability dimension emerged as crucial, with Jhawar committing to net-zero targets by 2030-2032 and 100% renewable energy sourcing for data centers.


Unresolved Challenges and Future Directions

Despite optimistic projections, several critical challenges remain. The talent shortage for AI infrastructure maintenance emerged as a significant bottleneck, with Chopra mentioning instances of substantial downtime due to lack of qualified personnel. The economic viability question persists, with current AI costs often exceeding returns, and dependence on expensive AI chips from limited suppliers creates vulnerability for developing countries seeking AI sovereignty.


The balance between rapid AI adoption and comprehensive governance frameworks remains contentious, reflecting broader questions about risk tolerance and institutional capacity in different contexts.


Strategic Implications and Conclusions

The discussions revealed that successful AI deployment in the Global South requires fundamentally different approaches from developed countries. Rather than competing on massive infrastructure investment, emerging economies can leverage second-mover advantages through cloud-based solutions, regional cooperation frameworks like DEFA, and DPI models.


The emphasis on collaboration over displacement provides a framework for managing workforce transitions while capturing AI benefits. The recognition that trust must be designed into systems from inception offers guidance for governance approaches that enable innovation rather than constrain it.


Most significantly, the positioning of Global South countries as co-authors of AI governance norms represents a shift from technology recipient to technology leader. The practical examples from India, the Maldives, Cambodia, Brazil, and other nations demonstrate that innovative approaches to AI deployment can emerge from resource constraints and unique local contexts, potentially offering more sustainable and equitable models than capital-intensive approaches of developed economies.


The path forward requires continued focus on infrastructure development, particularly renewable energy integration, talent development through continuous learning programs, and international cooperation through regional frameworks. Success in these efforts will determine whether AI becomes a tool for inclusive development or exacerbates existing inequalities within and between nations.


Session transcript

Tejpreet S Chopra

Hi, good morning everybody. I’ve got an incredible panel here this morning. The topic that we have is, I think, the most important topic at the summit. I think everywhere I’ve spoken or everywhere I’ve been, it all revolves around this critical topic around AI -driven strategies for workforce and economic growth. And I think the reason this topic is super important is the fact that if you are a government official anywhere in the world, I think this is their biggest concern, is that how is AI going to impact society? How is AI going to impact workforce? How is AI going to impact industries? So that’s going to be the most, you know, it’s the most important topic.

So I appreciate everybody who’s out here. My name is Tej Trikot Chopra, and I’m the founder and CEO of Industry .AI. So we are an AI company that focuses on driving productivity. productivity. passionate for me because I live and breathe this every day because we are trying to really do this is that how do you create the digital workforce or how do you empower the workforce across industries. A quick introduction of my colleagues on the call. We have Mr. Sathinder Singh from the ASEAN. Mr. Narendra Singh from Neve Cloud should be joining us any minute. Mr. Vinod Javar who is really the key in Nextra which is part of AIDA. Dr. Nihar Shah who is one of the best in the healthcare space and Dr. Mahendra Karpan who is a presidential advisor to Guyana.

Welcome everybody. Just one other key point. Just to put it in context. In India we have 70 million MSMEs. These MSMEs employ 230 million people. The MSME market in India produces 30 % of India’s GDP and 50 % of exports. The other big critical thing is how do we bring AI for all, how do we bring AI for all these companies that can’t afford what normally large companies do? And that’s the big challenge in front of us. And that’s what we’re going to talk about today. So in order to really kick this off, what I’d like to do is first really talk about three critical elements in today’s discussion, is that how do we redesign our workforce strategies given this new technology that’s coming up?

How do we build the digital and compute infrastructure? And I’ll request Vinod to talk about that. And how do we really ensure that economic growth driven by AI remains inclusive, responsible, and sustainable? So with that, I’m going to request Satvinder, if you don’t mind kicking it off, and it would be good to understand from your perspective, how is the Digital Economy Framework Agreement going to help governments around the world navigate the opportunities that exist? Over to you. Thank you.

Satvinder Singh

Thank you, Mr. Chopra. Very good afternoon to all of you. Great to be here with all of you. I think all of us are enjoying this momentous impact event, and it’s a great place to be here sharing ideas. And I’m here specifically Mr. Chopra, if I don’t mind, I’m giving the perspective of the ASEAN some of you may not know ASEAN is next door to India today we are the 5th largest economic bloc, 700 million people, most of it middle and upper middle income economies who are part of ASEAN and with India of course we are deeply connected, we have a free trade agreement and we also have a very strong trade economic ties with India and we have a lot of cooperation going on with India including in the area of digital connectivity Mr. Chopra talked about the digital economic framework agreement, let me just update you what is that, in short we call it DEFA DEFA is a digital agreement we are now negotiating in the midst of completing negotiations by March of this year last two years we have been negotiating it is the largest regional digital agreement in the world the only difference is also legally binding the only difference is also legally binding the only difference is also legally binding the only difference is also legally binding the only difference is also legally binding the only difference is also legally binding the only difference is also legally binding So we are actually negotiating with the 11 countries of ASEAN to come on board 700 million people to be digitally interconnected, interoperable So that we can do business better and so that we can grow our economies better Now the essence of DEFA came about post -COVID I think in COVID, like in India, in ASEAN too, it really changed us I think while COVID was not good for anyone, but COVID also had positive unintended consequence We saw the greatest transformation taking place in the way we live, work and play And that interpreted clearly into growth that took place post -COVID I think the leaders in my region saw the prospects And they also saw the numbers where huge chunk of economic growth is driven by digital And therefore there is a no regret move now to move the entire region into digital connectivity And that’s where the DEFA comes through I think the interesting thing in ASEAN I mean, well, India is one country in ASEAN Like I said, there are 11 countries.

We have LDCs there, least developed countries like Laos, Cambodia, Myanmar, and now Timor -Leste just joined us. And then we have advanced economies like Singapore, Malaysia, Thailand, Indonesia, who is like a middle -income economy. So it’s a mixed bag of economies, but the momentum of getting all of them together to do this, we were able to move the agenda because we were able to show very quickly through data that the biggest beneficiaries actually of the DEFA is not even advanced economies like Singapore, because they are already there, digitally connected, but actually are the LDCs. We were able to show that the impact of DEFA will be greatest in terms of jobs, prospects, economic growth, because they are really economies which are least developed, but they are going to be more developed.

We are moving into the latest of all kind of connectivity at the lowest cost. And they will be the ones who will be able to benefit on a per capita basis in a maximum way. So that is how we were able to get 700 million people from 11 countries. sitting on a common agenda of being integrated because you were able to show them the money. If you don’t show them the money, nobody is going to jump in and do any such agreement. Money here means jobs, economic growth, deeper depth in terms of growth of the people and communities. So DEFA, for example, already ASEAN is a very vibrant digital economy. Roughly it’s about 300 billion today and we are going to be moving to a trillion dollars in size by 2030 in the next couple of years.

But with DEFA, the numbers are showing that the region is going to double the size of digital economy. So I think this is where we are in terms of our ability to come together to be able to do business. And our idea is, of course, not to stop in ASEAN. The idea is that once DEFA is going to be in place, we want to be connecting to India. Economy to economy, I think this will really be fantastic. I think we can stop looking over the shoulder. I mean, basically global South India, Southeast Asia, there’s plenty of markets. demographics on our side. In fact, even the affinity of our people in wanting to embrace technology is on our side.

In fact, some of the studies that are showing that actually it’s economies like Southeast Asia and ASEAN as well as India is where people are seeing the translation of the use of AI in the most profitable way. The data is showing that it’s not in the West. It’s actually in our region where businesses are beginning to deploy small AI into their day -to -day business and making a big impact on productivity, on growth, and also in relevance. I’ll stop there. Maybe

Tejpreet S Chopra

Satyendra, you’re absolutely right because I think in our part of the world, I tell everybody that India is trying to lead and be the bridge between the advanced economies and the emerging economies. But I think the dynamics of technologies needed for our kind of part of the world is very very different from the West. So I think if we can get a good price point to provide these technologies, that will be great. Dr. Carpin, you’re an interventional cardiologist and you’re advising a lot of governments around the world. It would be great to get your perspective in terms of how you see AI and its impact in terms of transforming public health care. Now Dr. Carpin I was at a discussion two days ago with Vinod Khosla and he always says some really provocative things and one of the things he said was that in a few years from now AI, we won’t need doctors in the world and I know he said we won’t even need doctor surgeons in the world so you don’t need you’re the actual real person who does all this stuff so it would be good to get your perspective.

Dr. Mahendra Karpan

Thank you very much for having me here and I bring you greetings from our President Dr. Mohamed Irfan Ali and Vice President Dr. Bayard Jagdeo We are from a small country located in South America and we are here to help you just a population of 850 ,000 people. I believe on the way here I might have encountered 850 ,000 people on the road. So you can imagine the scale that we are dealing with. What is transformative about Guyana at this time in our history is that sometime 2015 we discovered oil offshore. And you know everything that comes with that transformative discovery. The oil and gas industry is now booming. And we are trying to learn all of the lessons from states that have walked this path before.

Those that have relied heavily only on oil and gas they have encountered tremendous difficulties that we are hoping to avoid. So one of the things, or a couple of the things that we are using these resources to do is to help us with our health care, our agriculture, and our digital transformation in the public service. One of the other important things about Guyana is that we have the majority of our population living on the coastal area, and most of the rest of the country is forest. So we actually are pioneers in selling carbon credits to the world. The sad and vulnerable part of this, however, is that the coastal area is on the sea level.

So using AI, predictive models, all of those things, it’s a survival tool for us, not just now, but for future generations. In recent times, we have, been fortunate to have visionary leadership to take us in the direction we’d like to go. and we have in our country several remote villages of indigenous populations and I’ll share an example, a personal example when I was more in hospital practice. There was an 18 -year -old boy who had to be flown out from an interior village by the military helicopter after a snake bite and when he came to the city it was the first time that he saw headlights on a car. That’s where we still are in some places.

So we have been able in recent times to use our resources to establish telemedicine in particular areas. We have now over 200 functional sites that can actually serve these remote communities. They can do simple things like this. EKGs, x -rays, blood pressure, blood sugar, all of the common things and respond. to trauma, etc. So a healthcare worker, not necessarily a doctor, a community health worker, somebody indigenous to that area, can assess these patients, they go on video conferencing and all 200 of these locations actually have Starlink or we’re trying to implement that now, so that they have connectivity. So the specialists on the coast and in larger centres actually can give real -time diagnosis, real -time advice.

I myself and the cardiac unit, my on -call team always will be able to review an EKG. Like in India, I suppose, our number one cause of mortality is still cardiovascular disease. Heart attack is a huge problem in our population. Historically, some of you may be familiar with the facts that most of our population at one time were indentured immigrants that left India. and the majority never returned. And they built homes and created generations of descendants from then in Guyana, Trinidad and Tobago, Suriname, in that entire region. So whatever is plaguing you in India from a healthcare perspective is the same thing that was transferred. Because we maintain the same lifestyle, we have the same foods, the same likes, the same dislikes, the same genetic predispositions.

So in our context, what we have been doing is to start at the basic primary level, because that’s where we are. We’re not yet at the Singapore level and the others, but we’re hoping to get there in a very rapid leapfrog type of strategy. So we’re using AI at this time to do primary healthcare, for inventory management, for surveillance. For surveillance. And we’re moving into areas like agriculture for soil management, food production, et cetera, and to help us in all aspects. So for those of you who are looking for opportunities where there are challenges, there’s always opportunities. So Guyana presents to you tremendous opportunity for investment, for development, and for long -term, multi -generational, sustainable involvement in our country.

And I am sure, and I bring you this message on behalf of the president, we welcome investors to Guyana.

Tejpreet S Chopra

Dr. Carpin, thanks so much for that. I completely agree because I think the world is going to face exactly the same challenges, whether it’s in health care, whether it’s in agriculture, and I think there’s a lot of cross -sharing that we can actually learn from. Niyar, I’m going to pull you in, right? So just for everybody’s benefit, Niyar is with the Lawrence Berkeley National Labs, which is really one of the leading public research institutes. It’s in the world. But Niyar, I just want to share with you about four or five weeks ago. there was a majlis in Adnok in Abu Dhabi and they had a hundred CEOs in a room on a Sunday and everybody in the world showed up and there were four groups of people every major CEO of every major oil and gas company in the world the CEOs of every major energy utility in the world the CEOs of every AI company in the world and the CEOs of every large capital provider in the world and I was trying to figure out myself what’s the connect and at the end of the day what came out was that the world will need four times more energy in the next 10 -12 years to support the growth of data centers and all the other things that are going to happen and that’s going to require four trillion dollars every year for the next 10 years so Nir with those numbers would love to get your perspective from a technology perspective and how should the world react to that kind of growth that’s needed thank you

Nihar Shah

yeah so as mentioned my name is Nihar Shahab and I work at Lawrence Berkeley National Lab it’s one of the 17 Department of Energy National Labs If you also are Oppenheimer, you might know where the National Labs came from. And, of course, we have a very distinguished history with a lot of Nobel Prizes, so I won’t bore you with all that. But I’m very grateful, first of all, to CII for this opportunity to speak. And with respect to the question, obviously energy is one of the things that I think in, you know, I go to bed every night, I wake up every morning thinking about energy, being one of the energy labs of the United States.

Now, one of the other things that is also probably not as well -known, I direct the global cooling program at Berkeley Lab. And another blind spot with respect to kind of, you know, you mentioned energy, you mentioned the huge growth, you mentioned, you know, the huge investment needed. Another thing that’s needed is going to be cooling. And that’s another blind spot that I think we don’t really pay attention to. So that gathering of CEOs, I hope that there’s also a gathering of HVAC and data centers and other CEOs. and then in addition I think one more thing that we would probably need to think through in countries like India is the water consumption so you think about these kinds of things you also so we need to really think about this in a holistic sense and then you know in the bigger picture thing I think some of these things of course AI we are at the intersection of so many different things but if somebody tells you that they know exactly what’s going to happen in three years or five years or seven years they’re selling you something so you might want to take a second look at that.

I’ll say a couple of other things right related to what you mentioned Vinod Khosla just a month ago I was in Silicon Valley Berkeley Lab is based in Silicon Valley and Mr. Khosla was giving a keynote there and he said as usual he said some very provocative things. One of the things he said was by 2030 everything that needs human expertise will be free or nearly free. Second thing he said was everything that needs you know labor is going to be and this is coming to our topic here is going to be also very nearly free. The thing that I disagree with Mr. Khosla about is that, again, I mentioned the energy blind spot and the cooling blind spot.

So really, I think some of these things are going to be infrastructure bottlenecks, which I think some of our co -panelists are going to be able to address. And then also, I think, along with that, there’s probably also going to be a talent bottleneck. And when I say talent bottleneck, I don’t mean talent across the board. I think it’s going to be particular kinds of talent that we’re going to need. And just today, you might have heard the U.S. and India signed or India formally joined this PAC -Silica initiative by the United States. PAC -Silica is an initiative about the whole AI supply chain. So now you’re talking about not just, you know, kind of compute and not just, you know, the infrastructure, but you’re also talking about the whole supply chain that will allow that to happen.

And that’s an initiative that the U.S. government has started. So, you know, there’s a range of different things we could talk about. The workforce dimension, of course, is super important. And, of course, I can. Come back to any of those things. I’ll mention one last thing. Berkeley Lab, the Energy Act of 2020. requires Berkeley Lab to essentially report to the U.S. Congress on data center growth. And they found that over the last decade, data center growth has tripled. So, again, some of these numbers bear out even if you look at history. And the forecast is that by 2028, triple again. So, you know, these things are, again, not very well known. But I do think that, you know, that these blind spots need to be addressed by all of us and all of you all.

And we’re at a very interesting point with the, you know, I would say industrial revolution. So let’s see what

Tejpreet S Chopra

Thanks for that, Nir. I think you’re absolutely right. I think the people are underestimating the challenges of developing all this infrastructure, whether it’s in terms of cooling, whether it’s in terms of power, whether it’s in terms of communication, fiber optics. So I think that’s going to be a huge challenge. And with that, I’m going to turn it over to Vinod. Vinod’s with Nextra. They’re building some of the largest data center networks in India. But just before this panel, I was actually talking to Vinod because I think there are going to be two parts of the world. There are going to be large cloud data centers, which Vinod is building, but I also think there’s going to be another parallel world that’s going to be on the edge.

We at Industry .ai this week launched the world’s first AI supercomputer for manufacturing, which can go on every factory floor of the world, especially at a price point for 70 million MSMEs to transform productivity. So two things, Vinod. One would be good to get your perspective on how the world’s going to pan out of cloud versus edge, number one. And number two, all the challenges or bottlenecks that Nir was talking about, whether it’s in terms of cooling, capital, technology, skill labor, would be good to get your perspective.

Vinod Jhawar

Sure. Thank you. Thank you very much. I represent Nextra. It’s a subsidy of Airtel. We are in this business of building infrastructure for data centers. So that’s it. That’s our bread and butter from Nextra point. So we’ve been doing this for the last 20 years. We’ve seen the evolution from a normal. server room racks to small enterprise customers to now hyperscalers. Now, we’ve got the expert also over here. We’ve got now the new, what do you say, elephant in the room called the AI requirement of data center. So much is the demand now which is coming through to build large infrastructure for data center that Nextra has decided to carve out a separate vertical called AI VC on that.

So that’s the vertical which I represent. We are here to develop large scale gigawatt kind of campuses to that to cater to the fast requirements of some of our customers to grow primarily in the Indian subcontinent areas here on that. Yeah, the right is said that the challenges are there. Power is the challenge. Land is a challenge and getting the right kind of skill set still remains a challenge. We come from 20 years of experience, so we have understood the ways to work on this, on that. So being one of the pioneers in the home ground industry in the data center here, so we have been doing that. Few of the challenges have been pushing us to go beyond certain areas, look at new areas to build data centers.

Some of them are very close to the coastal area so that it can also accommodate cable landing stations for us, so that takes care of a lot of data required requirements. Plus we are also putting sites which are close to national grids now. There were places where we used to source voltage at 33 kV, now we are looking at 700 kV volts and all. So this is the thing, thoughts, which has now evolved and all, and it requires a separate thought process and the… Obviously the large amount of capital is required to get into that. So we are in this and we are well prepared. The demand obviously is quite high. The expansions of Nextra is quite aggressive also.

And we got something going on in the south. We thought something the best going forward on that. So your second question of how do you do the power and sustainably portion of it? Obviously most of the power we are going to source from renewable energy. That’s the key strength in the Indian regions here. Luckily for some of the good policies which have been put across a few decades back by the government, we have got plenty of renewable energy generators here. The government is pushing for upgrading the infrastructure to evacuate this energy also. So once we are at this high voltage, we are also connected to the central grid. So it makes it very, very reliable for us.

We are aiming to be what we said net zero by 30, 20, 30, 32, something is what. And there is a big pool of renewable energy for us to tap into that. We are at present, we have contracted close to 400 odd megawatt of renewable energy. So no longer we are looking at just 50 % resource for energy. That percentage is going almost close to almost 100 % now. This is how the whole sustainably portion of data center. And India and Nextra are well positioned to tap into this. I think that’s the interest level in trying to do a green data center evolves for us on that. The other challenge which has been told about how do you do the skill set.

Yeah, skill set is a challenge. Probably it requires a lot of debate on that. It’s something which needs. To be handled both at the fundamental level at the schooling level. and at the university level and right at the immediate level of training the existing engineers to adapt. So by the time the next generation come in, we probably would have missed the bus. So there are three, four approaches we are looking at how we can build an immediate kind of skill upgrade to make them suitable to develop the data center on that. So this is some of the things which we are doing, and I think we are, as an extra, very, very well positioned to meet the demands of whatever the customer is looking at.

Tejpreet S Chopra

Thanks for that, Varun. I think one of the things that came out of that session in Abu Dhabi was the fact that the world that’s going to win the AI arms war is the country that has the cheapest energy. And I really do believe that in India we have an incredible opportunity. I come from a renewable space. My first solar farm eight years ago, my revenue was 18 rupees a kilowatt hour. Today we get 2 rupees 20. My first wind farm was 8 rupees 50. Today we are in 2 rupees again. So I think we have an incredible opportunity in India to really win this AI arms war because the cost of producing energy is quite cheap.

So, Narendra, first of all, welcome. Narendra is the MD of RackBank and NeveCloud. Narendra, you’ve heard all the challenges in terms of the cloud. It would be good to get your perspective in terms of, one, cost of compute in India. How do you really make it affordable for everybody? And two is, how do you ensure adoption across the country?

Narendra Singh

kilometers away from Earth. We partner with Agni Cool, which is a space tech company, and the space ecosystem has evolved in the country from the last seven years. And the government has given a lot of open up space for everyone, for the private player. The first mission we are sending before the end of this year, and we believe that this is for critical workload which can protect the borders, unmanned vehicles, and all those things. So we started exploring beyond Earth and that’s what it is needed. And we can lead as India because the ecosystem, today look at the cost of building data center in India is 4, 5, 6 million dollars per megawatt versus 12 million dollars in US, in Singapore and Dubai.

Any market you go, you get a cost of 12 million dollars. Why? Because the 80 to 90 percent product which required in supply chain is manufactured in India. And we have to strengthen that. As government announced the 200 billion, I believe this is only for data center infrastructure, not for chips. So chips cost is on top of it. It’s like 5x or 10x. It depends on what chips you are using. so opportunity is huge, it’s a trillion dollar opportunity for the country thank you

Tejpreet S Chopra

I met Narendra about 2021 at the JW Marriott Hotel in Mumbai and that time he was still putting together this whole strategy and I was thinking to myself in 2021 what’s going to happen about data centres and now he’s talking about data centres in space so it’s good to see the kind of progress that’s happening before I go, I have lots of questions to ask but any questions from the audience that they want to ask go ahead go ahead

Audience

Sir, I am Harsh Vartan basically from HDI industry but before that I was working as a research fellow in CSIRC so my question to Mr. Shah is we have seen hydrogen fuel cells being used at experimental level in railways and buses but it has not been implemented at a large scale neither in India nor abroad so what are the… Thanks.

Nihar Shah

Yeah, I have many colleagues at Berkeley Lab. Actually, they have been collaborating with India’s National Hydrogen Mission. So, you know, I think, and thanks for the question. You know, when you come to fuel cells, I think there are a few bottlenecks. You know, some of them have to do with also just even having the hydrogen infrastructure in the country, right? Right. So I’m not necessarily the right person to address like all of these issues in terms of why hydrogen fuels have not taken off. But I do think that some of these things are still, you know, kind of an R &D challenge. And I think many of these governments are looking at hydrogen to see whether or not you can actually, you know, eventually do the R &D to deploy it.

And there is collaboration going on. So, you know, stay tuned. I think it will obviously India is also doing a lot on that and other countries also.

Narendra Singh

I can add to this that. The bottleneck as an operator is the cost should not be higher than what we are getting today from the grid. innovation should like lower down the cost then the adoption will happen rapidly so that’s what we think and that’s why I believe the adoption is not happening because people don’t want to pay premium for that and I think India can take the lead in that in terms of cost adoption and price points the supercomputer for manufacturing we are seeing 6 .5 lakhs so I think that’s the kind of speed at which we are going to change the way things are going

Tejpreet S Chopra

so Tindra I want to pull you in and the ultimate question that everybody is asking impact on jobs at the ASEAN how are you thinking about it because huge concern for governments is AI going to replace jobs is it going to enhance jobs so it would be good to get your perspective and what you are going to say out here is going to drive policy all over the world

Satvinder Singh

so I am also going to say it perspectively from also how data is being collected already on impact on jobs and actually I have taken this from the studies that actually were done by Entropic Entropic it’s a massive study on AI jobs and security and one thing is clear. I think right now, while there’s quite a major hype on AI, but when you actually study the impact that it has globally and even in Southeast Asia, in ASEAN, it’s really impacting certain segments of the economy. I think the biggest impact is actually more on white -collar jobs rather than blue -collar jobs. And it’s true because a lot of it, I think even in the white -collar jobs, a lot of it has got to do with collaborative augmentation rather than full automation and handing over to the AI to do everything.

So I think that’s at this stage where we are in terms of the technologies on AI that we have and how we’re deploying them. Of course, when you are watching Elon Musk and you watch all these technologies and what’s to come in two, three years’ time, they are saying, now this is going to move from collaboration to totally replacing the human factor. In fact, the takeover part is, I think, that’s what… scares most societies. And I must tell you this is now becoming front and centre of conversations in government, in policy makers. I’m actually quite certain that the governments are not going to hand over this ability of replacements of all important jobs at the high echelons of society to the machine.

That I can assure you is not going to happen. There will be a lot of effort and conversations going on and it’s happening in closed doors where policy will have to come in to determine what can or cannot happen. And those barometers are going to be there and I think that’s where you see this impact event. You saw the largest conglomerate of decision makers from the private sector sitting with governments in this one location. You can see that momentum is there. There will have to be an ability for us to differentiate and also collaborate with what the change is going to come. and otherwise I think you’re going to see societies breaking up, the contract of governments with people is going to break up, people won’t have jobs, and if we are saying that the impact is not so much on the blue collar I think then a lot of the farming community is probably sighing with relief but I think we all know that in the cities where there are millions of people, I think this is where it’s going to be quite critical for us to get this contract properly sorted out I think in the coming years you’re going to see a lot of ethical rules regulations set up in order to ensure that actually whatever change that we embrace coming from the latest of AI, it has to improve, not take away the quality of life I think collaboration is going to be the name of the game not displacement of the human the use of people and population and I think that is something in conversation it’s not something that in this room we can decide, but clearly you can see that the momentum is here for that kind of difficult conversations to take place

Tejpreet S Chopra

you’re right and I like what you just said and first of all I’m hearing that one collaboration not displacement because the word I’ve been using is enhancement not displacement but I think it’s going to be all of the above so I think you’re absolutely right Dr. Karpen it would be good to get your perspective especially of healthcare you talked about telemedicine right technically I guess a doctor in the United States or India could be providing advice to somebody sitting in Guyana so how are you seeing this whole world panning out in terms of the impact on healthcare jobs

Dr. Mahendra Karpan

thank you so I’m glad that you mentioned the collaboration of these services yes indeed we have in the telemedicine space we have doctors from India we have doctors from New York the Apollo hospitals here the Northwell group in New York they collaborate they are able to help us with patients in terms of displacement of human capital or human skill set though I think for most of the countries like ours, we’re starting out at a severe deficit. There is not a surplus of radiologists. There’s not a surplus of cancer diagnostic technicians. All of these skill sets are extremely limited. So AI actually comes in to help us with diagnosis, accuracy, speed of diagnosis, as well as the economic aspect of achieving all of those outcomes.

But I tell you one thing, as a physician, that we are not too concerned for some things. In the emergency room, when there’s a child who can’t breathe from asthma and they’re scared parents, an AI can make an accurate diagnosis. They can tell you exactly what to give, what mixtures to nebulize, but to comfort and reassure those parents. that’s a human function at difficult stages of life when you’re facing terminal situations end stage of cancer you want somebody with warmth to hold your hand that cannot and can never be replaced by AI so all of this we have to bear in mind the complementary aspect of this new era that we are entering into we rely on the AI to give us the accuracy of the diagnosis in fact in Guyana we just purchased software to help us with CT scan interpretations and the world is going towards more imaging earlier diagnosis and that will be used effectively to reduce cost to have better access to specialists there was a time when we could not even contemplate getting for the right treatment for the right treatment and we were just waiting and we were just waiting the top guys from Apollo to give us an opinion, or the top guys from Mount Sinai.

Now they’re willing and they’re able to, despite the time difference. Actually, it’s like quarter to five in my morning time, so if I’m a little sleepy, please forgive me. But this is how we’re using it. But that human touch, I don’t believe it will be replaced at all.

Tejpreet S Chopra

Glad to hear that. And also, I sometimes think that when you go and search something on the internet, you get hallucinations, you get false answers, so the last thing I want is a doctor to be searching and getting the wrong answer and suggesting the wrong medicine. Any other questions? Otherwise, go ahead.

Audience

Hello, I’m the CTO at MindEquity .ai and I’m also the founder of AI Society. I have two questions, actually. My first question is that if I am starting an AI pilot company, and to have a full -time impact, what is the biggest challenge? technical barriers that I think have value in both that.

Tejpreet S Chopra

Do you want to take that? Do you want to go ahead?

Narendra Singh

So scale and AI. Today you spend $2 and you generate $1 because half of the 50 % goes to the AI chip company and this problem can be only solved through enabling indigenous AI chips which has a better performance and the lower cost and maybe in the big guys who is enabling the entire ecosystem, they have to reduce the cost. That’s the best way because once you build the agents, we have billion users. It’s the largest market in the world. Scaling, when you do the scale, people will not pay for the value. $20 is not enough or $10 is not enough for the subscription but your cost is higher so I think this will take some time.

The new chips is coming and that’s where the job questions related to that, if I answer this. The job is the AI voice is fairly usage happen in the country and we are losing even government is adopting AI. They are signing all the MU with foundation companies. What I believe that they should not remove the call center. They should come up with a policy because AI is costing 7 rupees per call versus call center is only 1 rupees per call. So adopting AI in this and you are firing millions of jobs and what happened after that. So I think in some area government has to restrict the AI and those are the challenges because we have to wait for some time to figure out what these people are going to do next.

Upskill their thing.

Tejpreet S Chopra

Thank you. Can I give somebody else a chance? Thanks so much. Somebody at the back. Sorry. Just give me one minute. Go ahead.

Audience

Question to Mr. Sathinder. As you are taking the topic of job in securities, say upskilling or reskilling, how can these strategies can help preserve the jobs and still the human in the loop and in the end, the relationship between these two, more better, more human friendly.

Satvinder Singh

So clearly the efforts in most countries in the world is to really start upskilling their populations. It’s really beginning. It’s starting from schools but it’s going out to the workforce because the workforce that’s actually today actively under siege with all this AI implementation. And obviously there are countries who can afford the upskilling. The more developed countries are quite generous in terms of capacity building and coming out with programs even empowering employers and workers to help themselves in order to do the upskilling. But I’m also worried sometimes, what are they upskilling with? what they sometimes upskill with may not be enough in two years time so I think this upskilling is going to be really an upskill task for all of us so ultimately I think you have to continue learning upskilling is the word but continuous learning to adapt is going to be the name of the game but you know it’s going to be harder for my generation and some of us in the panel, not all of you and for some of us in the audience but not for some of the younger ones and some of you who are just starting work right now and when I talk to some of them, the younger people they are less worried about this they are less worried because they have already grown up in the universe where things are moving in that speed and they are not talking about lifelong careers they are talking about lifelong skills that they will keep adapting to the new change so I think that is the name of the game to survive

Tejpreet S Chopra

go ahead

Audience

basically you told that the solar revolution came in India When it was A to be 30 kilowatt per hour, and now it’s to be 20. There were little, little catalysts which were involved to boost up the solar revolution in India. So, one of the revolution was subsidy and the information to people. Basically, I am in favor that AI should come and boost up because it won’t affect the jobs. It will fit the people at the particular level where they should be and it will increase the literacy. And are we also planning to give subsidy on various AI projects which are into development or subsidy level because it will play a catalyst to boost up the AI model as solar revolution came in India.

Tejpreet S Chopra

I think the government is doing a lot already. The government has already given 10 ,300 crores for the India AI mission for sovereign AI. They are giving GPUs available at 65 rupees per month. Yes. Right, per month. Not per year. Per hour. Per hour. So, we are already the cheapest in the world. So, the government has a whole slew of incentives and subsidies that they have announced and they keep on adding more. I don’t know if anybody else wants to add.

Narendra Singh

so there are quite a few no no it’s public it’s all public the event is all about India if you forget our global missions so the India is bring us together and build this entire ecosystem two years back Sam Altman was in India and talking about you can’t do this this is not part of now look at 12 foundation models country has launched so this is only possible when you democratize the AI access or GPU access to the innovators like you so that’s what government has already done you just request you will get the allocation of the GPU with one of the providers like us and you can get half of the prices paid by government by the way it’s not subsidy they are paying full price and subsidizing the end user like you the innovators thanks

Satvinder Singh

So, I think when it comes to the higher education, the challenge is worldwide. So, I can tell you in dinner conversations of some of the most established people I’ve sat with, with their children who are all in higher education, you can see that the value system is changing. The focus today of some of the most influential people who can make a difference is to actually encourage their kids to become more enterprising. So, I think the culture of being enterprising has to be given prioritization in order for the ability for us to adapt to what’s coming. And I think if we change that, if we create that and inculcate that in the universities even more, and bring it up front, I think that that will be the way we can overcome some of the challenges you face.

At least, I’m trying to address this first part.

Narendra Singh

Yeah, I think I can adopt on top of it. Set up AI like you can get the GPUs from there. But now, you don’t need to learn code today. You can code through AI, right? So you can build this. We have a billion users, billion problems. So you can solve those problems. You can make them entrepreneurial, like solve one problem at home or a college related or school related. And that’s what we also encourage people should come. Our students should come and go to industry visit. Because if they see that, they will do that. And the physical world has a lot of opportunity than the digital world. Because digital world is now concentrated with, imagine how many apps you guys are using in your phone.

Now this will go to one app, which is open AI or cloud. So the money is going to one company. And that’s dangerous than anything else.

Nihar Shah

I’ll just add on the energy part, right? So you heard also, Narendra talk about putting data centers in space, right? So. And free cooling, free energy. So that’s one part of it. But the other part I think that’s interesting about this whole energy question is that you really, I think, with AI are able to imagine potential. I mean, we don’t know what we don’t know and we don’t know what we know even, right? So one of the examples I’ll give you on that is, you know, with respect to like designing better chips, right? It’s like when they gave the, you know, Google DeepMind, when they gave the problem to AI to actually design better chips, they found a 30 % improvement in the performance of chips because AI was able to design better chips.

And so you can think about AI designing better data centers, AI designing, you know, many different parts of the whole chain. And we don’t know all of the different things that AI, you know, even mathematical computational efficiency, these kinds of things. So there are many different domains that we haven’t even touched that potentially can also have a transformative impact. And so this is a very, like I said, a very exciting time in our lives where we get to really see what the impact is going to be. Thanks.

Tejpreet S Chopra

Vin, do you want to add? Do you want to add something? No, okay.

Vinod Jhawar

Just to add to that, what we expect AI tools probably to do is to give an opportunity to grassroots. so when these tools are being employed and they learn through that and now a lot of language barriers are also being broken up so English is no longer a barrier with all the AI tools so you will have some set of people who will be using that and qualification is not a driver for that so this is what AI will do and we will see a trend where you will have a lot of blue collar upskilling by themselves no need to link it to degrees it is the self learn module assisted by AI tools which will make them competent for the market they could be either a specialist advising or they could be entrepreneurs or they could be a coach on that need not be sitting in a desk and doing something which is written there I think this is how we feel the education system also will change with the tools being available there

Dr. Mahendra Karpan

Thank you. So obviously we are the newest, particularly in consideration of this room. We’re new to the AI game, but one of the things that we’ve been able to do in Guyana is to create a digital school at the primary level. And it started working. In fact, it’s now being requested by other countries in the region. That’s the Caribbean region. And part of our objective is to use this to get kids kind of hooked on technology, AI type of education. Hopefully it can be tailored to each individual child to identify strengths, weaknesses, to strengthen the areas that are weak, whether it’s literacy, numeracy, anything, and tailored to that particular child. And so that their interests can be peaked, their interests can be exploited and expanded.

and ultimately they may be able to condense eight hours of school time, maybe three hours, and then they can go outside and play like normal kids, the way we used to play kids as kids. So the digital schooling, the digital era, is not necessarily to take all their time behind a computer and a desk, but to give them more time and more freedom and to create a habit so that that could follow them, not just at the primary level, but when they get to university and all the way up to adulthood.

Tejpreet S Chopra

Thanks very much. I know we only have, we’re out of time right now, and I’ll quickly wrap this up in about 45 seconds just so that everybody, I think it’s been an incredible discussion. Boy, it’s going two times now, so I really have to wrap it up. But I think I just want to quickly wrap up. Six or seven key takeaways from today’s discussion that we all had. The first one is the fact that I think jobs are going to be key. It’s going to be collaboration, not replacement. I think the way we do our job, that’s critical. I think Dr. Carpin talked about agriculture and health and medicine. I think there’s going to be a huge transformation.

But the good thing is humans want touch. So that’s good. But, you know, there will be a lot of revolution in terms of telemedicine, et cetera. Nihar, you talked about cooling and bottlenecks. I think those are things that we all have to think about in our countries. How do we provide the infrastructure for cooling, et cetera, and something that you all can work on and let us know how to make it more efficient. I think that’s great. You talked about in terms of NEXTRA, in terms of the talent challenges we’re going to have and how we’re going to have to manage all these data centers. Somebody mentioned recently that some of the big data centers in India, for 30 percent of the time it’s down because of the lack of talent to maintain these data centers.

You talked about supply chain. It’s fantastic that India is also thinking about putting data centers in space, which is fascinating. There’s going to be a big debate about, you know, more data centers versus the edge. Like I mentioned to you, you know, there’s one school of thought that we can actually bring the big AI to every factory in India by bringing it on the edge. And the computing power that’s developing is going to make that happen. And the last point I want to say is the point that you mentioned. And I think this is going to be the key takeaway for all of us, is that the speed at which technology is changing is so rapid that we’re all going to require continuous learning going ahead.

And it doesn’t matter how old you are, but that’s going to be the biggest takeaway for me, that that continuous learning and upskilling is going to be the key for all of us. So with that, really, thank you very much to all my panelists. And to everybody. And hopefully we can all make an impact around the world. Thank you very much.

Mohamed Kinaanath

Thank you. Thank you. Thank you. Thank you. I’ll be here. Thank you. Thank you. Thank you. Mr. Cana Dipali will sit at the front please take a seat at the front Ambassador Garcia Ambassador Garcia and if anybody wants to Ibu Ayub okay, thank you very much everyone oh, do you want I’m getting my cues from the photographer it’s not my show yet until I start okay it’s the photographer Can we please, and you’d like us to stand up for a group photo? Okay. Thank you very much. It’s very Asia. It’s not an event unless there’s a photo, so thank you very much. All right. Thank you very much. Good afternoon, everyone, and welcome. It’s a real privilege for me to host and moderate this session, Trusted AI at Scale, a Global South Leadership Dialogue, here at the India AI Impact Summit.

Now, this session hits squarely within the summit’s trusted AI pillar, and deliberately so. Because trust is no longer a downstream concern, it is now the condition for scale. Across governments, enterprises, and societies, we are moving past the question of whether AI will be adopted. The real question is whether it will be trusted by citizens, by institutions, and across borders. So why this session, and why did ISA host this session? The framing for today’s conversation is very intentional. Much of the global AI governance debate is still shaped by frameworks emerging from the Global North, the US, Europe, and China. Those frameworks are important, but they are not sufficient for the lived realities of the Global South, where AI is often deployed at population scale, under real resource constraints.

and in context where the cost of failure is not abstract, it is social, economic, and political. This is precisely the gap that AI Safety Asia was created to address. I am one of the advisors of ISA, and our mandate is straightforward but ambitious to bridge the global north and the global south on AI governance, not by importing templates wholesale, but by co -designing governance approaches that are interoperable, pragmatic, and grounded in local institutional strengths. And we do this through the three pillars, collaboration, capacity building, and policy -relevant research. And what makes this session different? That brings me to expectations. This session is not about abstract principles or ideal end states. We are here to surface operational blueprints, how trust is built in practice, and we have an amazing panel that will hopefully be able to really bring that to the table.

Thank you. and how safety is governed under real constraints, how AI systems actually reach the people and states often struggle to serve. The speakers you will hear from today are not theorizing from a distance. They are governing, financing, regulating, and deploying AI in the real world, from small island states to large democracies, from welfare delivery to financial systems, from regional cooperation to enterprise risk management. So one final framing point before we begin. The goal of today’s dialogue is not to position the Global South as a passive recipient of AI governance norms, and we’ll hear definitely from Cambodia, from the Maldives, and Indonesia, and Brazil. It is to position the Global South as a co -author of those norms, contributing models of governance that are population -scale, institution -aware, and grounded in lived social reality.

That is the through line of this session, from why trusted AI matters to who it must reach to how it is enabled, governed, and ultimately operationalized. With that, I’m delighted to open this dialogue, and we’ll begin with opening remarks that set the stakes why trusted AI is existential and not abstract. And then we’ll move through discussion. I realize that time is very short, so I think one of the reasons Ed put me here is because I’m known to crack a whip a bit. So with all due respect, I know you’re all very important people, but I will let you know when the time is up. So with that, I would like to invite His Excellency Professor Mohamed Kinanath, Minister of State for Homeland Security and Technology from the Maldives.

Your Excellency. Your Excellencies, Distinguished Head Supporters. Delegations, Honorable Ministers. esteemed leaders. It is both a privilege and profound responsibility to stand here before not merely a representative from Republic of Maldives, but a voice for many CIDs, small island developing states. I extend my warmest gratitude to the organizations of this forum for creating a platform where the aspirations of nations regardless of their geographical size can be heard alongside the strategies of those leading the frontier of innovation. Ladies and gentlemen, if the global disclosure turns to AI, it is often centered on the ambition of large economies on the computing scale or on a trillion dollar geopolitical competition. And while these dimensions significant, this represents only part of the narrative for seeds like the Maldives.

Nations defined by geographical dispersal of small islands, 1 ,200 islands, narrow economy base, and acute exposure to climate change. AI is not a matter of competitive advantage alone. It is a matter of institutional resilience. It is a matter of sovereign capacity, and increasingly, it’s a matter of survival. The Maldives comprises nearly 1 ,200 remote islands, which is spread across 850 square kilometers. Our economy has been mainly based on tourism. Our exposure to sea -level rise remains among the highest of any nation on Earth. These realities do not diminish our ambitions, and they demand we adopt technologies that can deliver public services efficiently across vast distances, strengthening governance and diversifying the economic foundation. The government of the Maldives, under the leadership of our current president, launched a Digital Transformation Agenda, a comprehensive national vision to transform the Maldives into a digital first nation within the coming three years.

The technology vision is called Maldives 2 .0. It is not a technology initiative in isolation. It is a fundamental reimagination of how these states serve its people and how the economy grows and how opportunity reaches every citizen of the Maldives. We have already begun the implementation. Maldives have good technology infrastructure if you look at the region. We have the highest – we have one of the highest internet penetration networks in the region. We have the highest number of mobile subscribers in the region. Our population is half a million. We have mobile subscribers, 1 million. 4G coverage is 100%. 5G is 80%, one of the highest in the region. Six subsea cables. And also fiber to each household is 100%.

So maybe some of the European countries have not even achieved these statistics. So considering the delivery of the AI and also considering the geography of the Maldives, AI is very important for us when it comes to the health sector, education sector, since our islands are very remote. So AI intelligence also offers the Maldives a pathway to economic diversification, enabling us to develop a knowledge economy. To cultivate local technology enterprises and to position our youth. Thank you. digitally. The Maldives is not approaching AI without preparation. We are building governance structures to ensure that this technology serves our people ethically. In July 2025, Maldives launched the AI Readiness Assessment Methodology Report, which was developed with assistance from UNESCO.

And this landmark assessment, the first of its kind in South Asia. So building on this assessment, the government is now advancing to develop a national AI master plan and also an AI Act, which is also underway. So the UNESCO Readiness Assessment has further recommended the establishment of an independent AI governance body and multi -stakeholder advisory council. So these are some of the recommendations. The UNESCO Readiness Assessment has further recommended the establishment of an independent AI governance body and multi -stakeholder advisory council. So these are some of the of the report. So as I told you, Maldives is getting ready for the AI and also since we have this Maldives 2 .0 transformation mission, we are working very hard in the next three years to get digitalization complete in the Maldives.

So excellencies, the Maldives may be small in land, but we are vast in determination. We are a nation that has built its identity upon resilience, resilience against the tides that shape our shores. So Maldives 2 .0, I have said that the vision is our commitment to the future. AI deployed responsibilities governed ethically is central to this vision. We do not seek to replicate the digital trajectories of large nations. We seek to chart a course that is authentically ours. On that reflection, our values, address our vulnerabilities. As the world convinced to deliberate on the governance of AI, let us build on AI future, which is inclusive, intelligent, equitable, and as human as the technology is powerful.

So thank you so much. Thank you

Moderator

so much, Your Excellency, Minister Kananath. I’d now like to invite Dipali K hanna, Senior VP and Head of Asia for the Rockefeller Foundation for her remarks. Just before

Dipali Khanna

I start, we were talking about global north, global south. What struck me in this panel is the women are at the periphery, right? So anything and everything that we’re going to do in this space, we’ll have to get women back in the center. But I was also excited that we have strong women who can manage these men. So anyway. Good afternoon, Ministers, Excellencies, colleagues, and partners. Let me begin by thanking AI Safety Asia for convening this dialogue and JPMorgan Chase for co -hosting. The fact that this conversation is happening here in this region with this leadership really matters. PM Modi in his keynote yesterday laid out the vision for Manav, building AI that is safe, ethical, and centered on people, ensuring technology serves humanity responsibly and benefits everyone, including women, right?

We’ve just heard powerful perspectives that bring the point to life. From the Maldives that AI is not abstract policy, it is a survival tool. I know a colleague from Togo couldn’t join, but I’m sure she would have mentioned that trusted AI can make the invisible visible. So the question before us is not why AI matters or who should benefit. It is how we build it responsibly, at scale, and with legitimacy. For over 100 years, the Rockefeller Foundation has leveraged, advanced technologies for betterment of society, and we believe that there are learnings from that work also to apply trusted AI. partnership, patient capital and institutional strength. What distinguishes success stories like Togo’s Novici and India’s Coven is not just technological sophistication, it is alignment.

Governments willing to move decisively, private sector actors willing to collaborate, technologists willing to design for public systems and catalytic capital willing to absorb early risk. Novici reached nearly a million informal workers, not in months, just in days. Coven delivered at population scale with transparency and interoperability built in. This was not mere luck. These were examples of ecosystems working together. That’s partnership. For adoption, users must trust both that AI will deliver the benefits without harm. Much like early vaccine development, we need to invest in both supporting users, to adopt the technology, as well as building robust evidence and systems that ensure safety. And scaling this trusted AI in the global south requires more than venture timelines.

It requires risk tolerance. It requires capital that understands that building sovereign AI capacity involves experimentation, regulatory iteration, and institutional learning. Philanthropy can truly play a catalytic role here, not by replacing markets, not by dictating governance, but by re -risking what some leaders have described as the smart adopter model. The smart adopter does not wait for perfect consensus. It adapts responsibly. It pilots with guardrails. It builds local institutional muscle alongside technical capability. Catalytic capital can support regulatory sandboxes, independent safety assessments, talent pipelines, and interoperable standards so that adoption is both fast, nimble, and short -lived. That’s the power of patient capital. And finally, institutional strength. Digital public infrastructure has shown us something profound. Trust must be designed from day one, not retrofitted after deployment.

Transparency, auditability, grievance redress, open architecture are not compliance burdens. They’re adoption accelerators. If our AI systems are to scale in health, climate resilience, food systems and financial inclusion, they must be built on institutional foundations that citizens recognize and most importantly trust. Businesses have a critical role here. Responsible innovation is not simply about internal governance frameworks. It is about long -term partnership with governments and societies. It is about seeing trust as a strategic infrastructure, not friction, because trusted systems scale, untrusted systems stall. The Global South is demonstrating that it does not need to choose between speed and safety. It can design both. The opportunity now is to align partnerships and patient capital behind that leadership. So that trusted AI at scale is not a slogan.

It is operational. The Rockefeller Foundation stands ready to continue playing a catalytic role in that journey because trusted AI is not simply a governance aspiration. It is a development imperative. Thank you

Moderator

Thank you so much to both your Excellency Minister Kananath and Diwali for the… I thought, again, it’s a great way to start us off for the discussion today. You’re welcome to stay in front, sitting in front, but we’ll start the discussion. Actually, I think it’s set the tone for what we really wanted. I think it’s set the tone for what we really wanted. I think it’s set the tone for what we really wanted. I think it’s set the tone for what we really wanted. I think it’s set the tone for what we really wanted. I think it’s set the tone for what we really wanted. I think it’s set the tone for what we really wanted.

I think it’s set the tone for what we really wanted. I think it’s set the tone for what we really wanted. so everyone that you see in front brings a very specific experience, skills and coming either from private sector or their government so I would love to in particular as Dipali mentioned, building trust starts from the beginning, it’s not an afterthought so I’d like to start with Under Secretary of State Your Excellency Sokeng I guess the question I’m going to have for everyone is what is the single biggest obstacle to operationalizing trust in your context based on your experience and what is it that this room that’s filled with quite a lot of people from different sectors what can we do about it as well and what you’ve heard as well in these past couple of days as you’ve been here in the summit

Son Sokeng

First, thank you Imah for for the very good set of tones of these discussions and I’d like to thank Asia AI Safety Asia for having me on these panel discussions from Cambodia perspective I would say a short answer to that is how to get the people familiar with that AI and that would start off with the people user the leader and the regulator and aside from that I can talk a little bit about the Cambodia experience on that similar to what Excellency Minister from ADEA mentioned Cambodia has began to back the journey of conducting the AI readiness assessment supported by UNESCO we completed last year in July 2025 and from that perspective we can understand rely on the recommendations and starting to think about what is the strategy for Cambodia to move forward in terms of AI adoption in Cambodia.

So based on the recommendation, the national AI strategy has been drafted and currently we are in the process of finalizing the national AI strategy. At the same time we are also drafting the national AI governance framework, keeping the national strategy in mind. And one of the key strategic priorities that we have in the national strategy is people, which is the first priority of our national strategy ranking from the user like I mentioned earlier, user the leader, regulator and also government official. The second priority is the infrastructure and data. The third and the first one is AI adoption in government and the private sector. The fifth strategic priority is the governance and the last one is cooperation and the research.

So based on this priority we can see that human is still the first and the key priority action for Cambodia. Building on that our draft AI governance framework also very much human centric so we believe that the governance should be aligned with the risk of AI. So context of our governance framework would be based on the risk assessment and to understand the risk people have to know the impact of the AI. So government has very clear intention is that we need to educate people, let people understand what is the AI tool and the implication of that. So since 2024 government introduced because Cambodia Digital Skills Roadmap, which we outline what is the plan for the next 10 years for Cambodia in terms of human development.

And our goal is that in the next 10 years, we will have 100 ,000 talents who are AI -ready. And in addition to that, we also introduced various programs to educate government officials. As of now, we have trained more than 10 ,000 government officials. Basic digital skills, and also part of it is the AI skill as well. And so based on what we have right now, if one thing that you ask me what we can do in this room is that I would like to say is to increase the capacity of humans to understand the risk of

Moderator

Thank you so much. I have so many questions but I’m going to hold them for now I’m going to move to Ambassador Garcia as a tech ambassador for Brazil as a G20 country leaving BRICS and all of these along with Indonesia as well for G20 as I mentioned the global south must be architects and not observers and I believe Brazil is at the forefront of this can you say a little bit more about that and what obstacles do you find

Eugenio Vargas Garcia

capabilities to harness the power of the technology so somehow we need to enhance our one national capabilities but in cooperation with other partners overseas and finally we only had COP30 as you remember last November and we included digital technologies and climate change as a sustainability problem because now we have been discussing in terms of data centers energy efficiency so sustainability is key in a way that we are always trying to send this message in terms of AI development oriented strategy and I think for the global south it’s important that we engage in tech diplomacy because otherwise we will not get hurt to do what we are doing and we will not be able to do what we are doing to do what we are doing heard and we need to speak up and our voice be heard where it matters Thank you so much

Moderator

So moving from one great nation in the south to another one, Ibu Ayu Ibu Ayu is the director of AI and Emerging Technology Ecosystems of the Ministry of Communications in Indonesia Ibu Ayu, can you tell us a little bit more about Indonesia’s national strategies, basically where do you find the obstacles as well and as Ambassador Garcia mentioned in the ecosystem of BRICS where does Indonesia or where is ASEAN sitting on this as well

Aju Widya Sari

Thank you Ima It’s an honor for me to sit here from Ministry of Communications and Digital Affairs I cannot say it is an obstacle, I say it’s challenging once you know mentioning about the challenging one Indonesia has many things to be resolved. One is the infrastructure, because you know that our penetration of broadband, especially for mobile broadband, even though it is above 95%, but it is still based on 4G coverage. You know that AI, we need more coverage for 5G. And then the penetration of fixed broadband and backbone is quite low, because you know Indonesia has hundreds of district area and 10 ,000 of sub -district area. Today, the penetration is still 70 % by sub -district area.

That’s why we need to push the penetration of the backbone. Regarding of the data center, today our providers of data center… We have many data centers, but the GPU basis is still limited. So I think we need to invest more regarding the processing for AI. And then this is relating to the infrastructure. And relating with this framework of regulation, right now in Indonesia we have set up the roadmap of AI, national roadmap AI, and also we are preparing the guideline ethical of AI. Talking about the national AI roadmap, we are sure that we need to have strategies that are real, not just theoretically. Because, you know, when we explain, execute our vision in national roadmap, We have four strategic directions.

One is governance collaborative, and the second is encouraging innovation ecosystem. And the third is to strengthen capabilities and capacities, including infrastructure. And the last is mitigating risk. You know that this national roadmap is important for us because we need clarity for five years ahead. Regarding to the issue that come from AI. Regarding to the ethical AI guideline, we set up the rule and clarity of responsibility of AI actors. And also we preparing the instrument for monitoring and evaluation. Because you know, ethic not just ethic, we have to monitor it one. And the last is we have… We have to put the safeguard for the people, how they using and develop AI. That’s the main thing that we preparing.

Moderator

Thank you, Ibu Ayu. I think it’s been mentioned already, and I’m glad Ambassador Garcia mentioned it. And, of course, in his address, Minister Kinanath mentioned, and I’m going to turn to Dr. Parakana. You did mention something about, in our, sorry, I’m going to bring the discussion that we had in the green room. I’m calling it the green room. It’s not green. It’s green, about how you, as a private company, utilize and how that could be beneficial for climate resilience and development, especially in vulnerable countries. So can you tell a little bit about that? Dr. Parakana, of course, is the founder and CEO of AlphaGeo.

Parag Khanna

Thank you. Thank you so much, Ina. Thank you all for being here. Well, AI as a concept evokes this notion of leapfrogging. Do you remember when we used to use that? We used to use that term all the time, leapfrogging. And, of course, it applied very appropriately to mobile telephony, to fintech, to renewable energy, solar panels. So, you know, faster, better, cheaper. and inherent in that concept, which is very important now when we talk about AI, is the notion of second mover advantage. That’s what leapfrogging was fundamentally about, having second mover advantage. Now, why that’s relevant right now is because, of course, developed countries in particular, particularly the United States and others, have invested enormous amounts of capital in the capex requirements of AI.

You know, some significant percentage of U.S. GDP growth, for example, is attributable right now to that AI capex -related infrastructure investment. But that is not something, of course, that nations of the global south, so to speak, developing countries can afford. And so the question becomes, is there an advantage to late development when it comes to AI that can save developing countries of the south a lot of money while still enjoying the fruits of that innovation? So it’s important to not, especially in the context where you’re making trade -offs, between electricity, food, water, the basics for your population, while, of course, there’s now this almost emotional and hype pressure to invest, you know, to clear land, to build data centers, to divert energy, we have to ask ourselves, is that the right way to allocate capital?

Or should one be taking advantage of cloud computing, edge computing, sovereign cloud solutions that can generate the same or better output, bang for your buck, with less CapEx expenditure? And that’s the moment that we’re at. And it’s important to remind that we’re having this conversation in India. And one of the virtues of India hosting this event is precisely that India’s rise as an AI superpower, you know, breaks the narrative out of this conventional wisdom that it’s a two -horse race between the U.S. and China, and that you’re doomed in some way to choose between your data being, you know, hoovered up by one or the other player. what India is offering, at least more than in theory, is rapid diffusion of the latest technologies, cloud -based models and solutions, through the tools of digital public infrastructure, DPI, which has been one of the benefits of this event now over the course of the years.

People have learned this all -important acronym, DPI, which I’ve adhered to or believed in, been a supporter of for quite some time, because it does hold the promise for neutrality, for a menu of options, for being delivered in a way that protects sovereignty of data, but in a very affordable way. And India has done it, been a pioneer of it, obviously domestically, with Adar and so forth. And for those, if it hasn’t been disclosed enough this week, more than 50 countries are building payment systems and identity systems on that stack. So that’s a great example of DPI. So think of AI in that mold of second -mover advantage, leapfrogging, following the mold of cloud -based sort of solutions that can be low -cost.

Now let me just quickly talk about two areas where there are huge gaps in public sector access to data or ownership or simply knowledge of solutions that AI, and particularly the AI that we, the way in which we apply data science, is to geospatial data. And these are also two areas that are of critical, fundamental, if not existential importance to developing countries. One is sustainable urbanization, and the second is climate adaptation. Anywhere you go in the world, actually rich or poor countries, if you survey the average person on the street and ask them, what is the biggest problem plaguing your society, nine out of ten people that I speak to in dozens of countries around the world is affordable housing.

And I think that’s a really important part of the problem. just sustained urbanization that is so organic, so rapid, so unplanned accelerating around the world but now finally governments have the tools again, geospatial tools, mapping tools understanding which districts, which settlements are expanding and why where are people coming from what kinds of housing need to be built where governments have always been fighting backwards or if not given up, quite frankly, on grappling with these issues but now we have foresight AI -powered geospatial tools that can look decades ahead and say this has been your time series urban expansion this is how you map it out this is where you should be building what and when and so bringing together demographics bringing together infrastructure bringing together migration, fiscal spending and directed targeting in a way that is a great use case for AI that almost the entire development developing world could use and has barely begun to use and is very cost -effective, right?

So that’s number one. The second, equally if not more important, is climate adaptation. Climate risk is both acute and chronic. We’re talking about monsoons, floods, fires that are becoming more frequent and devastating. And, of course, complex climate modeling is not the kind of thing that any individual country can or should finance. We have global climate models that are AI -powered, that are developed with the world’s best institutions, that are publicly financed, that are now available to be downscaled for your country. And this is something that, again, especially developing countries, especially countries of the south, that are most affected by climate dislocation, by climate risk, can and should take advantage of. But, again, to be clear, they have barely begun to do so yet.

So targeting infrastructure investments, targeting your infrastructure to adapt to climate risk, where do you need to build? Seawalls, flood barriers, flood control measures. irrigation systems for drought, all of that, we are again, just like urbanization, are years and years and years behind, and there’s almost no country on this panel, almost no country in the world, even wealthy countries, that are ahead of the curve on this. The entire planet is behind, as we know from COP summits, but it is countries of the south that are going to be the worst affected on the fastest timeline. If you’re not using the tools that are available right now, AI -powered climate modeling, scaling, adaptation scoring, in order to plan your national infrastructure, and then putting together the public -private partnerships to get it done, you’re behind.

So this is about global public goods, right? Affordable housing, a manageable urbanization at a global scale, climate adaptation for people everywhere, but it has to be delivered locally. And that’s why it’s incumbent on each nation represented here, each nation of the global south to really harness and take advantage of these tools.

Moderator

Thank you so much, Dr. Parag. Again, lots of questions in my head. Kip Wainscott, Executive Director of Global AI Policy from JPMorgan Chase, one of our biggest supporters as well. Thank you so much for supporting us for this event. You are not here just because of that, I can assure you. But I’d love to hear what you have to say, particularly the question that I brought forward earlier about the obstacles, in particular in where you see it. But again, financial services, model risk management, and all of that in the safety architecture of AI. Yeah. Go ahead.

Kip Wainscott

Thank you. A lot to unpack there. This is a great panel, by the way. So many esteemed panelists. I really feel privileged to share the microphone with all of you. You know, it’s interesting thinking about these things from the vantage of JPMorgan Chase because we’re really kind of interrogating the questions from sort of three different perspectives, right? One is one of the world’s largest financial houses that’s deeply invested in artificial intelligence. We have an acute interest in unlocking the value of this technology and seeing the growth potential of this technology. But there’s a simple truth that we recognize, and that is that AI is only valuable if it is deployed, and deployment depends on trust.

And so really building out, you know, we have an interest in this sort of multi -stakeholder dialogue about what that trust model that is going to unlock diffusion, you know, not just across enterprises, but in the public sphere across the global south, and really putting this technology into organizations that are impacting people’s real lives. The second perspective from which we’re looking at all of this is as a deployer of the technology ourselves. We are one of the world’s largest deployers of AI. And what’s interesting, we’re also one of the most regulated industries in the financial sector, and yet financial services have been the earliest adopters of AI. We’ve been using artificial intelligence through this sort of evolutionary ramp of really more than a decade.

To combat fraud, to protect consumers, to create just more efficient personalization of financial services. And I think one reason why you see financial services companies so ready and eager to adopt is because we have that existing trust architecture. Trust isn’t just a feature of financial services. It’s the core business model. And so we have… Thank you. We have these, you mentioned, you know, model risk management. We have these rigorous practices of evaluating models, of documenting governance and oversight, of really ensuring that there’s ongoing monitoring across all of our technology deployments in a way that just lends itself to what I would call a comfort in sort of building the trust ecosystem for responsible deployment. And then sort of the third prism that we look at this issue from is as a purchaser of these technologies and like kind of almost a procurement lens here.

We spend $20 billion annually on our technology budget. That puts us in this really sizable position in the innovation ecosystem of, you know, startups and scale -ups that they want to sell their products. They’re building innovative new artificial intelligence applications with the hope that they’re going to be able to sell their products to the world. Selling it to JPMorgan Chase. And we see a real innovation. inefficiency right now in the fact that there isn’t a shared sort of set of expectations for trust, for, you know, what these products should be benchmarked against in order for us to ingest them, you know, in a way that, you know, we have the confidence is going to serve our customers well, is going to reflect our, you know, our responsibilities, our duty of care as a, you know, a regulated industry.

And so, you know, it speaks to, I mean, I think one, the need to bring these diverse perspectives to this conversation around governance so that we can really kind of get past the sort of compartmentalization of like AI safety as sort of a siloed conversation and accelerated AI adoption as a different conversation. This is the same conversation. And, you know, what we really need to, I think the purpose of both of those conversations is to really get past the sort of compartmentalization of AI safety as sort of conversations is to really align on this trust model that is going to ensure that we can deploy these technologies, you know, in a very broad and impactful way across the economy.

Moderator

I’m going to put you on the spot while you have your microphone a little bit you’ve been here throughout the week and you’ve heard the panelists just now speak from what you’ve been hearing throughout the week how optimistic are you in terms of I think His Excellency Sokeng mentioned about collaboration how confident are you in building these collaborations to build trust in AI just from the conversations that you’ve had this week?

Kip Wainscott

Yeah, no I’m optimistic I think just the fact that we’re here in New Delhi and having this summit in this environment this is a much bigger summit, I think it’s a more inclusive cross section of voices and so I think that that reflects that this conversation is getting bigger that we’ve moved past this focus on that technical capabilities, which is kind of where we have been, to now I think capability has really been almost commoditized and legitimacy has not. And we’re in this phase now where we really need to establish the legitimacy of these technologies and that they are fit for purpose, that they can be trusted and deployed across these different societal sectors. And so I think that I am optimistic.

It requires intention. And I’m seeing the intentionality, I think, around the curation of these conversations. I think there’s a lot to carry forward here. Also, some of you may have seen we’re very near the end of this summit. And I think before we were even halfway through, excuse me, I’m running on fumes at this point, but we were more than halfway through the week and people were already writing up the assessment. Of what, you know, what the themes were, what the takeaways were. and people were saying, you know, oh, this summit is no longer about, you know, responsibility or safety or, and I just, that isn’t my perception of these conversations. It really is that, you know, we’re just talking about them in a different way.

We’re talking about them in how they are going to impact real lives, how we can take this technology into the economy in real valuable ways. And in order to do that, we have to include that sort of trust dimension.

Moderator

Okay. Thank you so much. We have eight minutes left, and I’ve been told that we have to finish on time, but I really want to get this question in and hopefully be able to hear from everyone. So Ambassador Garcia and Your Excellency Sokeng and Ibu Ayu, what are you taking away? What are you taking home from this panel, first of all? Or from the week that you’ve been here, reflecting on what Kip just mentioned?

Eugenio Vargas Garcia

Yes, thank you. First, I think India was very successful bringing this summit to the Global South for the very first time. But this was the Bletchley process that began in the UK in 2023. We have Seoul, Paris. So this, what we have been discussing here, is something that is more inclusive. And some new concerns were added to the agenda, sustainability, not that it was not discussed before, but with this perspective coming from the Global South, which is important. So I would conclude with three recommendations, because we need to be practical. We are thinking mostly we agree on high -level principles in terms of AI governance. But when we think of countries lacking resources, or having other competing priorities, so they need to decide what to do and prioritize in many cases.

So I think they should start small and have a few small scales. quick impact projects so that they can build on proven success so let’s say focus on some education, healthcare, agriculture then focus on some specific projects and then build to reach the next level second is that we need to seek they need to seek international partners sometimes it’s it’s useful and needed to enhance national capabilities it’s difficult for a single country alone to do this investing in infrastructure and do something that’s expensive so seek international cooperation and third, as I said before engage in these discussions at an international level engage in tech diplomacy and send more people to discuss where I think it’s important including the United Nations thank you so much

H.E. Sokeng

Thank you. Having seen the time, I’ll just go very quickly on the last sentence. Coming to this summit, I agree with our parents that it’s very inclusive and we can see perspective from all the stakeholders, from the government, the industry, academia, and even the startup. So learning from this, I have just one wish, which is that we have to be honest with each other, the industry, the government, and bear in mind that we are here to protect people for the people. So whatever we do, we need to think about people first. With that, please consider that when we think of governance frameworks, the regulation of the law that the government might put should be the mechanism to promote innovation.

It’s not an obstacle. It’s not an obstacle for the innovation. So in order to do that, we need to build trust also, and we need to be honest with each other. Thank you.

Moderator

Ibu Ayu, quickly.

Aju Widya Sari

Thank you. Actually, I’m very impressed with the spirit of Prime Minister Modi yesterday. I think every country has the same spirit regarding to the AI. So the three points that I’m taking from this summit, one is collaboration, indeed, and then inclusive, because if we consider about inclusive, we need intention from government, from industry, from the people. And then the last is investment, because investment, you know that AI needs more and more investment. This is a collaboration come. But the issue will come is how we define the sovereign, because sovereign is based on the… the needs of the country. how we define, is it equal or not? And still, it’s an under question of me also.

Moderator

Thank you so much, Iwayu. Dr. Parag, I’m going to have you bring it home in one minute. What you’re taking home, in particular in your conversations with some of the different governments here.

Parag Khanna

Well, the first thing is I actually want to echo Kip’s point is that we’re at an inflection point where we can’t, we’ve been, in phase one, let’s say, there was a lot of harping about trust. Can we trust? Can we not trust? And I think it’s a good thing that that pressure was there, but now that pressure to have transparency in models has delivered to some degree. And that it’s been done in a way where public and private have not been on opposite sides of the discussion, but have really partnered. So I think we’re really beyond that. And now we can move from models and theory into action and application. And that’s the part of the stack that we want to be on.

The infrastructure build -out is there. It’s being provided. The apps are being developed. They’re being deployed. I have seen a little bit of but would want to see a lot more in subsequent editions of this, especially as this summit, you know, migrates around the world now and remains perhaps in the hands of developing countries on the application side as much as possible and that we think not just about very specific verticals as we have been here and elsewhere, sort of your health care, education, I’ve emphasized climate and others, but probably something more societal and around resilience. You know, resilience is a term that comes up a lot but doesn’t really get quantified enough. And if we can push for that, that’s going to help us to establish performance benchmarks, not just of models but in applications.

And that’s really what I think everyone wants to see to make sure that AI doesn’t become something of not just a financial bubble but something almost of a policy bubble as well.

T

Tejpreet S Chopra

Speech speed

197 words per minute

Speech length

2261 words

Speech time

687 seconds

Collaboration over displacement

Explanation

Chopra argues that AI will augment human work rather than replace it, emphasizing a collaborative relationship between humans and machines in the workforce.


Evidence

“you’re right and I like what you just said and first of all I’m hearing that one collaboration not displacement because the word I’ve been using is enhancement not displacement but I think it’s going to be all of the above so I think you’re absolutely right Dr. Karpen it would be good to get your perspective especially of healthcare you talked about telemedicine right technically I guess a doctor in the United States or India could be providing advice to somebody sitting in Guyana so how are you seeing this whole world panning out in terms of the impact on healthcare jobs” [4]. “It’s going to be collaboration, not replacement.” [5].


Major discussion point

AI Impact on Workforce and Jobs


Topics

The digital economy | Artificial intelligence


Cheap renewable energy as AI advantage

Explanation

He highlights India’s low‑cost renewable power as a strategic edge in the global AI competition, framing cheap energy as an “AI arms‑race” advantage.


Evidence

“So I think we have an incredible opportunity in India to really win this AI arms war because the cost of producing energy is quite cheap.” [112].


Major discussion point

AI Infrastructure, Compute, Energy, and Data Centers


Topics

Environmental impacts | Artificial intelligence


AI for all MSMEs

Explanation

Chopra stresses the need to make AI affordable for India’s 70 million micro‑, small‑ and medium‑enterprises, noting their massive employment footprint.


Evidence

“The other big critical thing is how do we bring AI for all, how do we bring AI for all these companies that can’t afford what normally large companies do?” [151]. “We at Industry .ai this week launched the world’s first AI supercomputer for manufacturing, which can go on every factory floor of the world, especially at a price point for 70 million MSMEs to transform productivity.” [152]. “In India we have 70 million MSMEs.” [153]. “These MSMEs employ 230 million people.” [155].


Major discussion point

AI for Economic Inclusion and Development


Topics

The enabling environment for digital development | Financial mechanisms


Government AI subsidies and GPU pricing

Explanation

He points out that the Indian government is subsidising GPU access for innovators, making compute resources inexpensive for startups.


Evidence

“They are giving GPUs available at 65 rupees per month.” [119]. “so there are quite a few no no it’s public it’s all public the event is all about India … this is only possible when you democratize the AI access or GPU access to the innovators like you so that’s what government has already done you just request you will get the allocation of the GPU with one of the providers like us and you can get half of the prices paid by government by the way it’s not subsidy they are paying full price and subsidizing the end user like you the innovators thanks” [120].


Major discussion point

Funding, Subsidies, and Investment


Topics

Financial mechanisms | Artificial intelligence


S

Satvinder Singh

Speech speed

175 words per minute

Speech length

1913 words

Speech time

652 seconds

White‑collar job transformation

Explanation

Singh notes that AI’s biggest impact will be on white‑collar roles, where augmentation rather than full automation will dominate.


Evidence

“I think the biggest impact is actually more on white -collar jobs rather than blue -collar jobs.” [16]. “And it’s true because a lot of it, I think even in the white -collar jobs, a lot of it has got to do with collaborative augmentation rather than full automation and handing over to the AI to do everything.” [18].


Major discussion point

AI Impact on Workforce and Jobs


Topics

The digital economy | Artificial intelligence


Upskilling as continuous learning

Explanation

He stresses that continuous upskilling and lifelong learning are essential for workers to stay relevant as AI reshapes tasks.


Evidence

“what they sometimes upskill with may not be enough in two years time so I think this upskilling is going to be really an upskill task for all of us … continuous learning to adapt is going to be the name of the game …” [41]. “But I’m also worried sometimes, what are they upskilling with?” [43]. “And obviously there are countries who can afford the upskilling.” [44].


Major discussion point

AI Impact on Workforce and Jobs


Topics

Capacity development | Artificial intelligence


DEFA’s job and growth benefits for LDCs

Explanation

Singh explains that the Digital Economy Framework Agreement will generate jobs and economic growth especially for least‑developed ASEAN economies.


Evidence

“We were able to show that the impact of DEFA will be greatest in terms of jobs, prospects, economic growth, because they are really economies which are least developed, but they are going to be more developed.” [161]. “So it’s a mixed bag of economies, but the momentum of getting all of them together to do this, we were able to move the agenda because we were able to show very quickly through data that the biggest beneficiaries actually of the DEFA is not even advanced economies like Singapore, because they are already there, digitally connected, but actually are the LDCs.” [162].


Major discussion point

AI for Economic Inclusion and Development


Topics

The digital economy | Social and economic development


D

Dr. Mahendra Karpan

Speech speed

134 words per minute

Speech length

1394 words

Speech time

622 seconds

Human touch in healthcare

Explanation

Karpan argues that while AI can improve diagnostics, the empathy and human presence required in critical care cannot be replaced.


Evidence

“But that human touch, I don’t believe it will be replaced at all.” [36]. “that’s a human function at difficult stages of life when you’re facing terminal situations end stage of cancer you want somebody with warmth to hold your hand that cannot and can never be replaced by AI…” [193].


Major discussion point

Sector‑Specific AI Applications


Topics

Social and economic development | Artificial intelligence


Telemedicine and remote diagnostics

Explanation

He describes how telemedicine links doctors from India and the U.S. with patients in remote Guyanese villages, expanding access to specialist care.


Evidence

“thank you so I’m glad that you mentioned the collaboration of these services yes indeed we have in the telemedicine space we have doctors from India we have doctors from New York the Apollo hospitals here the Northwell group in New York they collaborate they are able to help us with patients…” [7]. “So we have been able in recent times to use our resources to establish telemedicine in particular areas.” [190]. “So a healthcare worker, not necessarily a doctor, a community health worker, somebody indigenous to that area, can assess these patients, they go on video conferencing…” [192].


Major discussion point

Sector‑Specific AI Applications


Topics

Social and economic development | Artificial intelligence


N

Nihar Shah

Speech speed

198 words per minute

Speech length

1151 words

Speech time

348 seconds

Cooling and power bottlenecks

Explanation

Shah highlights that energy and cooling are hidden constraints that limit AI scaling, calling them “energy blind spot” and “cooling blind spot.”


Evidence

“The thing that I disagree with Mr. Khosla about is that, again, I mentioned the energy blind spot and the cooling blind spot.” [80]. “Another thing that’s needed is going to be cooling.” [81]. “And free cooling, free energy.” [82]. “I think the people are underestimating the challenges of developing all this infrastructure, whether it’s in terms of cooling, whether it’s in terms of power, whether it’s in terms of communication, fiber optics.” [84].


Major discussion point

AI Infrastructure, Compute, Energy, and Data Centers


Topics

Environmental impacts | Artificial intelligence


AI‑driven chip design

Explanation

He notes that AI can design more efficient chips, delivering performance gains that reduce overall energy consumption.


Evidence

“It’s like when they gave the, you know, Google DeepMind, when they gave the problem to AI to actually design better chips, they found a 30 % improvement in the performance of chips because AI was able to design better chips.” [200].


Major discussion point

Sector‑Specific AI Applications


Topics

Artificial intelligence | Environmental impacts


V

Vinod Jhawar

Speech speed

160 words per minute

Speech length

941 words

Speech time

350 seconds

Renewable‑powered gigawatt data‑center campuses

Explanation

Jhawar describes building large‑scale, renewable‑energy‑sourced data‑center campuses to meet fast‑growing AI demand in the Indian subcontinent.


Evidence

“We are in this business of building infrastructure for data centers.” [95]. “We are at present, we have contracted close to 400 odd megawatt of renewable energy.” [97]. “We are here to develop large scale gigawatt kind of campuses to that to cater to the fast requirements of some of our customers to grow primarily in the Indian subcontinent areas here on that.” [100]. “And there is a big pool of renewable energy for us to tap into that.” [101].


Major discussion point

AI Infrastructure, Compute, Energy, and Data Centers


Topics

Environmental impacts | Artificial intelligence


AI tools for blue‑collar upskilling

Explanation

He predicts AI will enable self‑directed learning for blue‑collar workers, removing language barriers and reducing reliance on formal degrees.


Evidence

“I think that’s how we feel the education system also will change with the tools being available there” [207]. “Just to add to that, what we expect AI tools probably to do is to give an opportunity to grassroots.” [208].


Major discussion point

Sector‑Specific AI Applications


Topics

Capacity development | Artificial intelligence


N

Narendra Singh

Speech speed

183 words per minute

Speech length

889 words

Speech time

291 seconds

Cost advantage of Indian data‑center build‑out

Explanation

He points out that building data‑center capacity in India costs roughly half of that in the US, Singapore or Dubai, giving India a competitive edge.


Evidence

“And we can lead as India because the ecosystem, today look at the cost of building data center in India is 4, 5, 6 million dollars per megawatt versus 12 million dollars in US, in Singapore and Dubai.” [98].


Major discussion point

AI Infrastructure, Compute, Energy, and Data Centers


Topics

Environmental impacts | The enabling environment for digital development


Trillion‑dollar AI opportunity

Explanation

He emphasizes the massive market potential of AI infrastructure and services for India’s economy.


Evidence

“so opportunity is huge, it’s a trillion dollar opportunity for the country thank you” [273].


Major discussion point

Funding, Subsidies, and Investment


Topics

Financial mechanisms | Artificial intelligence


A

Audience

Speech speed

154 words per minute

Speech length

294 words

Speech time

114 seconds

Upskilling/reskilling to preserve jobs

Explanation

An audience member asks how up‑/reskilling can keep jobs and maintain a human‑in‑the‑loop approach.


Evidence

“As you are taking the topic of job in securities, say upskilling or reskilling, how can these strategies can help preserve the jobs and still the human in the loop and in the end, the relationship between these two, more better, more human friendly.” [46].


Major discussion point

AI Impact on Workforce and Jobs


Topics

Capacity development | The digital economy


AI subsidies question

Explanation

The audience inquires whether AI projects will receive subsidy support similar to solar initiatives.


Evidence

“And are we also planning to give subsidy on various AI projects which are into development or subsidy level because it will play a catalyst to boost up the AI model as solar revolution came in India.” [263].


Major discussion point

Funding, Subsidies, and Investment


Topics

Financial mechanisms | The enabling environment for digital development


Hydrogen fuel‑cell hurdles

Explanation

A participant asks why large‑scale hydrogen adoption has stalled, prompting a response about infrastructure and cost bottlenecks.


Evidence

“Sir, I am Harsh Vartan basically from HDI industry but before that I was working as a research fellow in CSIRC so my question to Mr. Shah is we have seen hydrogen fuel cells being used at experimental level in railways and buses but it has not been implemented at a large scale neither in India nor abroad so what are the…” [211].


Major discussion point

Sector‑Specific AI Applications


Topics

Environmental impacts | The enabling environment for digital development


M

Mohamed Kinaanath

Speech speed

91 words per minute

Speech length

1484 words

Speech time

975 seconds

Trusted AI at scale

Explanation

Kinaanath frames trustworthy AI as an existential prerequisite for responsible AI deployment worldwide.


Evidence

“With that, I’m delighted to open this dialogue, and we’ll begin with opening remarks that set the stakes why trusted AI is existential and not abstract.” [175]. “That is the through line of this session, from why trusted AI matters to who it must reach to how it is enabled, governed, and ultimately operationalized.” [179].


Major discussion point

AI Governance, Trust, and Policy


Topics

Artificial intelligence | Human rights and the ethical dimensions of the information society


UNESCO readiness recommendations

Explanation

He cites the UNESCO AI Readiness Assessment’s call for an independent governance body and multi‑stakeholder advisory council.


Evidence

“The UNESCO Readiness Assessment has further recommended the establishment of an independent AI governance body and multi -stakeholder advisory council.” [58].


Major discussion point

AI Governance, Trust, and Policy


Topics

Data governance | Artificial intelligence


M

Moderator

Speech speed

165 words per minute

Speech length

860 words

Speech time

312 seconds

Operationalising trust – biggest obstacle

Explanation

The moderator asks panelists to identify the single greatest barrier to operationalising trustworthy AI.


Evidence

“so everyone that you see in front brings a very specific experience, skills and coming either from private sector or their government so I would love to in particular as Dipali mentioned, building trust starts from the beginning, it’s not an afterthought so I’d like to start with Under Secretary of State Your Excellency Sokeng I guess the question I’m going to have for everyone is what is the single biggest obstacle to operationalizing trust in your context based on your experience and what is it that this room that’s filled with quite a lot of people from different sectors what can we do about it as well and what you’ve heard as well in these past couple of days as you’ve been here in the summit” [73].


Major discussion point

AI Governance, Trust, and Policy


Topics

Artificial intelligence | Capacity development


Collaboration confidence query

Explanation

He probes participants on their confidence in building collaborations to foster AI trust after a week of discussions.


Evidence

“I’m going to put you on the spot while you have your microphone a little bit you’ve been here throughout the week and you’ve heard the panelists just now speak from what you’ve heard throughout the week how optimistic are you in terms of I think His Excellency Sokeng mentioned about collaboration how confident are you in building these collaborations to build trust in AI just from the conversations that you’ve had this week?” [54].


Major discussion point

AI Governance, Trust, and Policy


Topics

Artificial intelligence | The enabling environment for digital development


D

Dipali Khanna

Speech speed

136 words per minute

Speech length

674 words

Speech time

295 seconds

Catalytic capital for inclusive AI

Explanation

Khanna calls for patient, impact‑focused funding to support regulatory sandboxes, safety assessments and talent pipelines for trusted AI rollout.


Evidence

“Catalytic capital can support regulatory sandboxes, independent safety assessments, talent pipelines, and interoperable standards so that adoption is both fast, nimble, and short -lived.” [185]. “The Rockefeller Foundation stands ready to continue playing a catalytic role in that journey because trusted AI is not simply a governance aspiration.” [174].


Major discussion point

Funding, Subsidies, and Investment


Topics

Financial mechanisms | Artificial intelligence


Women’s central role and gender‑inclusive governance

Explanation

She highlights that women are currently peripheral in AI discussions and calls for gender‑inclusive governance structures.


Evidence

“What struck me in this panel is the women are at the periphery, right?” [240].


Major discussion point

AI Governance, Trust, and Policy


Topics

Human rights and the ethical dimensions of the information society | Capacity development


S

Son Sokeng

Speech speed

128 words per minute

Speech length

501 words

Speech time

234 seconds

Human‑centric AI readiness goal

Explanation

Sokeng states Cambodia aims to have 100 000 AI‑ready talents within ten years, emphasizing people‑first AI strategy.


Evidence

“And our goal is that in the next 10 years, we will have 100 ,000 talents who are AI -ready.” [62]. “So whatever we do, we need to think about people first.” [66].


Major discussion point

AI Governance, Trust, and Policy


Topics

Capacity development | Artificial intelligence


Human‑centric AI governance framework

Explanation

He outlines a draft AI governance framework that aligns regulation with AI risk and puts people, leaders and regulators at the centre.


Evidence

“Building on that our draft AI governance framework also very much human centric so we believe that the governance should be aligned with the risk of AI.” [53]. “I would like to thank Asia AI Safety Asia for having me on these panel discussions from Cambodia perspective … we have begun to back the journey of conducting the AI readiness assessment supported by UNESCO…” [56].


Major discussion point

AI Governance, Trust, and Policy


Topics

Artificial intelligence | Capacity development


E

Eugenio Vargas Garcia

Speech speed

121 words per minute

Speech length

414 words

Speech time

204 seconds

Tech diplomacy for equitable AI access

Explanation

Garcia stresses the need for international cooperation and tech diplomacy to ensure the Global South can secure AI resources and sustainable data‑center energy.


Evidence

“capabilities to harness the power of the technology so somehow we need to enhance our one national capabilities but in cooperation with other partners overseas… we included digital technologies and climate change as a sustainability problem… I think for the global south it’s important that we engage in tech diplomacy because otherwise we will not get hurt to do what we are doing…” [123]. “quick impact projects so that they can build on proven success… we need to seek international partners… engage in tech diplomacy and send more people to discuss where I think it’s important including the United Nations” [126].


Major discussion point

AI Governance, Trust, and Policy


Topics

International cooperation | Environmental impacts


A

Aju Widya Sari

Speech speed

113 words per minute

Speech length

491 words

Speech time

258 seconds

Broadband, 5G and GPU capacity gaps

Explanation

She points out Indonesia’s limited 5G coverage, low fixed‑broadband penetration and constrained GPU availability as barriers to AI deployment.


Evidence

“You know that AI, we need more coverage for 5G.” [115]. “And then the penetration of fixed broadband and backbone is quite low, because you know Indonesia has hundreds of district area and 10 ,000 of sub -district area.” [118]. “Regarding of the data center, today our providers of data center… We have many data centers, but the GPU basis is still limited.” [113].


Major discussion point

AI Infrastructure, Compute, Energy, and Data Centers


Topics

Closing all digital divides | Artificial intelligence


P

Parag Khanna

Speech speed

164 words per minute

Speech length

1473 words

Speech time

535 seconds

Edge vs. cloud and second‑mover advantage

Explanation

Khanna advocates that Global South nations can leapfrog by using cloud‑based or sovereign edge solutions, gaining a cost‑effective second‑mover advantage.


Evidence

“So think of AI in that mold of second -mover advantage, leapfrogging, following the mold of cloud -based sort of solutions that can be low -cost.” [136]. “That’s what leapfrogging was fundamentally about, having second mover advantage.” [138]. “Or should one be taking advantage of cloud computing, edge computing, sovereign cloud solutions that can generate the same or better output, bang for your buck, with less CapEx expenditure?” [139]. “and inherent in that concept, which is very important now when we talk about AI, is the notion of second mover advantage.” [140].


Major discussion point

AI Infrastructure, Compute, Energy, and Data Centers


Topics

Artificial intelligence | The enabling environment for digital development


Geospatial AI for urbanisation and climate adaptation

Explanation

He promotes AI‑powered geospatial mapping tools to plan affordable housing and climate‑resilient infrastructure in rapidly urbanising regions.


Evidence

“One is sustainable urbanization, and the second is climate adaptation.” [202]. “just sustained urbanization that is so organic, so rapid, so unplanned accelerating around the world… we have foresight AI‑powered geospatial tools that can look decades ahead and say this has been your time series urban expansion this is how you map it out this is where you should be building what and when…” [203].


Major discussion point

Sector‑Specific AI Applications


Topics

Social and economic development | Artificial intelligence


K

Kip Wainscott

Speech speed

154 words per minute

Speech length

964 words

Speech time

374 seconds

Model risk management and shared trust standards

Explanation

Wainscott stresses rigorous model evaluation, documentation and ongoing monitoring as essential components of a trustworthy AI ecosystem.


Evidence

“We have these rigorous practices of evaluating models, of documenting governance and oversight, of really ensuring that there’s ongoing monitoring across all of our technology deployments in a way that just lends itself to what I would call a comfort in sort of building the trust ecosystem for responsible deployment.” [129]. “We have these, you mentioned, you know, model risk management.” [255].


Major discussion point

AI Governance, Trust, and Policy


Topics

Artificial intelligence | Capacity development


H

H.E. Sokeng

Speech speed

144 words per minute

Speech length

158 words

Speech time

65 seconds

People‑first regulation as innovation enabler

Explanation

He argues that AI regulation should promote innovation while keeping citizens’ welfare central.


Evidence

“So whatever we do, we need to think about people first.” [66]. “With that, please consider that when we think of governance frameworks, the regulation of the law that the government might put should be the mechanism to promote innovation.” [249]. “It’s not an obstacle for the innovation.” [250].


Major discussion point

AI Governance, Trust, and Policy


Topics

The enabling environment for digital development | Artificial intelligence


Agreements

Agreement points

AI should enhance and collaborate with humans rather than replace them

Speakers

– Satvinder Singh
– Dr. Mahendra Karpan
– Vinod Jhawar
– H.E. Sokeng

Arguments

AI will create collaboration and enhancement rather than displacement of human workers


Healthcare will maintain human touch for patient comfort and reassurance despite AI diagnostic capabilities


AI tools will democratize opportunities by breaking language barriers and enabling grassroots participation


Honest collaboration between industry and government is essential for people-first AI governance


Summary

Multiple speakers agreed that AI should augment human capabilities rather than replace humans entirely, emphasizing the irreplaceable value of human touch, collaboration, and people-first approaches


Topics

Artificial intelligence | Human rights and the ethical dimensions of the information society | Capacity development


Continuous learning and upskilling are essential for AI adaptation

Speakers

– Tejpreet S Chopra
– Satvinder Singh
– Son Sokeng
– Vinod Jhawar

Arguments

Continuous learning and upskilling will be the key for all of us


AI impact is currently greater on white-collar jobs than blue-collar jobs, with collaborative augmentation being the primary model


Human-centric governance frameworks should be aligned with AI risk assessment


AI tools will democratize opportunities by breaking language barriers and enabling grassroots participation


Summary

Speakers consistently emphasized that the rapid pace of technological change requires continuous learning and capacity building for all stakeholders to adapt to AI-driven transformations


Topics

Capacity development | Artificial intelligence | The digital economy


Infrastructure development is critical for AI deployment

Speakers

– Nihar Shah
– Vinod Jhawar
– Narendra Singh
– Aju Widya Sari

Arguments

Energy, cooling, and water consumption are critical blind spots in AI infrastructure planning


Renewable energy integration is essential for sustainable AI infrastructure development


India has cost advantages with data center construction at $4-6 million per megawatt versus $12 million in other markets


Investment and infrastructure development require collaborative approaches


Summary

All speakers acknowledged that robust infrastructure including energy, cooling, connectivity, and data centers is fundamental to successful AI implementation, with emphasis on sustainability and cost-effectiveness


Topics

The enabling environment for digital development | Environmental impacts | Information and communication technologies for development


Trust must be built into AI systems from the beginning

Speakers

– Dipali Khanna
– Kip Wainscott
– Son Sokeng
– Moderator

Arguments

Trust must be designed from day one, not retrofitted after deployment


Financial services demonstrate that existing trust architectures enable successful AI adoption


Human-centric governance frameworks should be aligned with AI risk assessment


Trust is now the condition for scale in AI deployment, not a downstream concern


Summary

Speakers agreed that trust is fundamental to AI adoption and must be embedded in system design from the outset rather than added as an afterthought


Topics

Building confidence and security in the use of ICTs | Artificial intelligence | Human rights and the ethical dimensions of the information society


Global South countries should be active participants in AI governance

Speakers

– Eugenio Vargas Garcia
– Moderator
– Mohamed Kinaanath
– Son Sokeng

Arguments

Global South countries must be co-authors of AI governance norms, not passive recipients


Global South must be co-authors of AI governance norms, not passive recipients


Small island developing states need AI for institutional resilience and survival, not just competitive advantage


AI readiness assessments and national strategies are being developed across Global South countries


Summary

There was strong consensus that Global South countries should actively shape AI governance frameworks rather than simply adopt solutions designed elsewhere, bringing their unique perspectives and needs to global discussions


Topics

Artificial intelligence | The enabling environment for digital development | The development of the WSIS framework


Similar viewpoints

India has significant competitive advantages in AI infrastructure due to low energy costs and manufacturing capabilities, positioning it well for AI leadership

Speakers

– Tejpreet S Chopra
– Narendra Singh
– Vinod Jhawar

Arguments

Countries with cheapest energy will win the AI arms race


India has cost advantages with data center construction at $4-6 million per megawatt versus $12 million in other markets


Renewable energy integration is essential for sustainable AI infrastructure development


Topics

Environmental impacts | The enabling environment for digital development | The digital economy


Small and geographically dispersed nations can leverage AI and digital technologies to overcome physical limitations and serve remote populations effectively

Speakers

– Dr. Mahendra Karpan
– Mohamed Kinaanath

Arguments

Telemedicine and remote healthcare delivery can serve dispersed populations effectively


Small island developing states need AI for institutional resilience and survival, not just competitive advantage


Topics

Information and communication technologies for development | Social and economic development | Closing all digital divides


India’s approach to digital infrastructure and government support creates accessible, affordable models that other developing countries can adopt

Speakers

– Parag Khanna
– Narendra Singh

Arguments

India’s Digital Public Infrastructure (DPI) model offers affordable, sovereign solutions for developing countries


Government subsidies and support are making AI compute accessible at low costs in India


Topics

Information and communication technologies for development | Financial mechanisms | The enabling environment for digital development


Successful AI deployment requires strong institutional foundations, collaborative partnerships, and patient capital that understands the complexity of building trusted systems

Speakers

– Dipali Khanna
– Kip Wainscott

Arguments

Partnership, patient capital, and institutional strength are key to successful AI implementation


Financial services demonstrate that existing trust architectures enable successful AI adoption


Topics

Financial mechanisms | Building confidence and security in the use of ICTs | Artificial intelligence


Unexpected consensus

Energy and infrastructure constraints as primary bottlenecks

Speakers

– Tejpreet S Chopra
– Nihar Shah
– Vinod Jhawar
– Narendra Singh

Arguments

The world will need four times more energy in the next 10-12 years to support AI growth, requiring massive investment


Energy, cooling, and water consumption are critical blind spots in AI infrastructure planning


Renewable energy integration is essential for sustainable AI infrastructure development


India has cost advantages with data center construction at $4-6 million per megawatt versus $12 million in other markets


Explanation

Despite coming from different sectors (industry, research, infrastructure), speakers unexpectedly converged on infrastructure and energy as the primary constraints for AI scaling, rather than focusing primarily on algorithmic or governance challenges


Topics

Environmental impacts | The enabling environment for digital development | Information and communication technologies for development


Second-mover advantage for developing countries

Speakers

– Parag Khanna
– Satvinder Singh
– Narendra Singh

Arguments

Second-mover advantage allows developing countries to benefit from AI without massive infrastructure investment


Least developed countries will benefit most from digital connectivity initiatives


Government subsidies and support are making AI compute accessible at low costs in India


Explanation

Unexpectedly, speakers from different backgrounds agreed that developing countries could actually have advantages in AI adoption through leapfrogging strategies and lower costs, challenging the narrative of inevitable technological disadvantage


Topics

Information and communication technologies for development | The digital economy | Financial mechanisms


Space-based solutions as practical near-term options

Speakers

– Narendra Singh
– Mohamed Kinaanath

Arguments

Space-based data centers represent future opportunities for critical workload protection


Small island developing states need AI for institutional resilience and survival, not just competitive advantage


Explanation

The convergence on space-based solutions as practical options for both large countries like India and small island states was unexpected, suggesting space technology is becoming more accessible for diverse use cases


Topics

Information and communication technologies for development | The enabling environment for digital development | Environmental impacts


Overall assessment

Summary

The discussion revealed strong consensus on human-centric AI development, the critical importance of infrastructure and energy considerations, the need for trust-by-design approaches, and the imperative for Global South leadership in AI governance. Speakers consistently emphasized collaboration over displacement, continuous learning, and the unique opportunities for developing countries to leverage AI for leapfrogging development challenges.


Consensus level

High level of consensus across diverse stakeholders from government, private sector, and international organizations. The agreement spans technical, governance, and development dimensions, suggesting a mature understanding of AI’s multifaceted challenges and opportunities. This consensus provides a strong foundation for coordinated action on AI governance and deployment in the Global South, with particular emphasis on inclusive, sustainable, and human-centered approaches.


Differences

Different viewpoints

Approach to AI job displacement – government intervention vs. market-driven solutions

Speakers

– Satvinder Singh
– Narendra Singh

Arguments

Governments will implement policies to prevent complete replacement of important jobs by AI


Government subsidies and support are making AI compute accessible at low costs in India


Summary

Singh advocates for government policies to prevent AI job displacement, while Narendra Singh focuses on government support for AI adoption and entrepreneurship without addressing displacement concerns


Topics

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


Infrastructure investment priorities – centralized vs. distributed approaches

Speakers

– Vinod Jhawar
– Tejpreet S Chopra

Arguments

Renewable energy integration is essential for sustainable AI infrastructure development


Countries with cheapest energy will win the AI arms race


Summary

Jhawar emphasizes sustainable renewable energy integration for data centers, while Chopra focuses on cost competitiveness as the primary factor in AI infrastructure success


Topics

Environmental impacts | The enabling environment for digital development | Financial mechanisms


AI adoption timeline and readiness requirements

Speakers

– Son Sokeng
– Parag Khanna

Arguments

Human-centric governance frameworks should be aligned with AI risk assessment


Second-mover advantage allows developing countries to benefit from AI without massive infrastructure investment


Summary

Sokeng emphasizes the need for comprehensive governance frameworks and human capacity building before AI adoption, while Khanna advocates for immediate adoption using existing cloud-based solutions


Topics

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


Unexpected differences

Role of government subsidies in AI development

Speakers

– Audience
– Narendra Singh

Arguments

AI subsidies could catalyze adoption similar to India’s solar revolution


Government subsidies and support are making AI compute accessible at low costs in India


Explanation

While both support government involvement, the audience member questions whether current subsidy levels are sufficient compared to solar energy support, while Singh defends current government initiatives as adequate


Topics

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


Cost-effectiveness of AI vs. human labor

Speakers

– Audience
– Narendra Singh

Arguments

Government AI adoption policies should consider job displacement impacts and cost-effectiveness


Entrepreneurial culture must be prioritized in education to help people adapt to AI-driven changes


Explanation

Unexpected tension emerges where audience highlights AI being more expensive than human labor (7 rupees vs 1 rupee per call), while Singh promotes AI adoption through entrepreneurship without addressing cost concerns


Topics

The digital economy | Artificial intelligence | Financial mechanisms


Overall assessment

Summary

The discussion reveals moderate disagreements primarily around implementation approaches rather than fundamental goals. Key tensions exist between immediate AI adoption vs. careful governance development, government intervention vs. market solutions, and infrastructure investment priorities.


Disagreement level

Moderate disagreement with significant implications for AI policy coordination. While speakers generally agree on AI’s potential benefits and the need for inclusive development, their different approaches to governance, investment, and implementation could lead to fragmented strategies across the Global South. The disagreements suggest a need for more coordinated policy frameworks that balance rapid adoption with responsible governance.


Partial agreements

Partial agreements

All agree that AI should enhance rather than replace human capabilities, but disagree on implementation – Singh focuses on policy protection, Jhawar on democratization through tools, and Karpan on maintaining human elements in healthcare

Speakers

– Satvinder Singh
– Vinod Jhawar
– Dr. Mahendra Karpan

Arguments

AI will create collaboration and enhancement rather than displacement of human workers


AI tools will democratize opportunities by breaking language barriers and enabling grassroots participation


Healthcare will maintain human touch for patient comfort and reassurance despite AI diagnostic capabilities


Topics

Artificial intelligence | The digital economy | Social and economic development


Both agree that trust is fundamental to AI adoption, but Khanna emphasizes building new trust frameworks from scratch while Wainscott advocates leveraging existing institutional trust mechanisms

Speakers

– Dipali Khanna
– Kip Wainscott

Arguments

Trust must be designed from day one, not retrofitted after deployment


Financial services demonstrate that existing trust architectures enable successful AI adoption


Topics

Building confidence and security in the use of ICTs | Artificial intelligence


Both agree on Global South leadership in AI governance, but Garcia emphasizes practical diplomatic engagement while the Moderator focuses on institutional framework development

Speakers

– Eugenio Vargas Garcia
– Moderator

Arguments

Global South countries must be co-authors of AI governance norms, not passive recipients


Global South must be co-authors of AI governance norms, not passive recipients


Topics

Artificial intelligence | The development of the WSIS framework | The enabling environment for digital development


Similar viewpoints

India has significant competitive advantages in AI infrastructure due to low energy costs and manufacturing capabilities, positioning it well for AI leadership

Speakers

– Tejpreet S Chopra
– Narendra Singh
– Vinod Jhawar

Arguments

Countries with cheapest energy will win the AI arms race


India has cost advantages with data center construction at $4-6 million per megawatt versus $12 million in other markets


Renewable energy integration is essential for sustainable AI infrastructure development


Topics

Environmental impacts | The enabling environment for digital development | The digital economy


Small and geographically dispersed nations can leverage AI and digital technologies to overcome physical limitations and serve remote populations effectively

Speakers

– Dr. Mahendra Karpan
– Mohamed Kinaanath

Arguments

Telemedicine and remote healthcare delivery can serve dispersed populations effectively


Small island developing states need AI for institutional resilience and survival, not just competitive advantage


Topics

Information and communication technologies for development | Social and economic development | Closing all digital divides


India’s approach to digital infrastructure and government support creates accessible, affordable models that other developing countries can adopt

Speakers

– Parag Khanna
– Narendra Singh

Arguments

India’s Digital Public Infrastructure (DPI) model offers affordable, sovereign solutions for developing countries


Government subsidies and support are making AI compute accessible at low costs in India


Topics

Information and communication technologies for development | Financial mechanisms | The enabling environment for digital development


Successful AI deployment requires strong institutional foundations, collaborative partnerships, and patient capital that understands the complexity of building trusted systems

Speakers

– Dipali Khanna
– Kip Wainscott

Arguments

Partnership, patient capital, and institutional strength are key to successful AI implementation


Financial services demonstrate that existing trust architectures enable successful AI adoption


Topics

Financial mechanisms | Building confidence and security in the use of ICTs | Artificial intelligence


Takeaways

Key takeaways

AI will enhance and collaborate with human workers rather than completely replace them, with current impact being greater on white-collar than blue-collar jobs


Continuous learning and upskilling will be essential for workforce adaptation to rapid technological change across all sectors


The world will need four times more energy in the next 10-12 years to support AI growth, with countries having cheapest energy likely to win the AI arms race


Infrastructure challenges including energy, cooling, and water consumption are critical blind spots that need immediate attention


India’s Digital Public Infrastructure (DPI) model offers affordable, sovereign AI solutions that can be replicated globally, with over 50 countries already building systems on this stack


Small island developing states and Global South countries need AI for institutional resilience and survival, not just competitive advantage


Trust must be designed into AI systems from day one rather than retrofitted after deployment


Global South countries must be co-authors of AI governance norms rather than passive recipients of frameworks from developed nations


Second-mover advantage allows developing countries to benefit from AI through cloud-based solutions without massive infrastructure investment


Multi-stakeholder collaboration between government, industry, academia, and startups is essential for successful AI implementation


Resolutions and action items

Countries should start with small-scale, quick-impact AI projects in sectors like education, healthcare, and agriculture before scaling up


Governments need to implement policies that promote innovation while protecting people, ensuring AI governance frameworks are enablers rather than obstacles


International cooperation and tech diplomacy engagement is essential, particularly for countries with limited resources


Investment in renewable energy integration for sustainable AI infrastructure development should be prioritized


Development of AI readiness assessments and national AI strategies should continue across Global South countries


Focus on human capacity building through education and training programs, with targets like Cambodia’s goal of 100,000 AI-ready talents in 10 years


Establishment of regulatory sandboxes and independent safety assessments to support responsible AI adoption


Creation of interoperable standards and grievance redress mechanisms for AI systems


Unresolved issues

How to define and balance AI sovereignty while maintaining international cooperation and interoperability


The challenge of making AI economically viable when current costs often exceed revenue generation ($2 spent to generate $1)


Skill and talent shortages for maintaining and operating AI infrastructure, with some data centers experiencing 30% downtime due to lack of qualified personnel


The need for new indigenous AI chips with better performance and lower costs to address current economic challenges


How to prevent job displacement in sectors where AI adoption is accelerating faster than workforce retraining


Balancing the speed of AI adoption with the need for comprehensive safety and governance frameworks


Addressing the digital divide and ensuring AI benefits reach remote and underserved populations


Managing the environmental impact of massive AI infrastructure expansion while meeting sustainability goals


Suggested compromises

Governments should restrict AI adoption in certain sectors (like call centers) temporarily while developing retraining programs for affected workers


Adoption of collaborative augmentation models rather than full automation to maintain human involvement in critical processes


Use of cloud-based and edge computing solutions as alternatives to massive data center investments for resource-constrained countries


Implementation of risk-based governance frameworks that align regulatory requirements with the actual risk level of AI applications


Phased approach to AI deployment starting with proven use cases before expanding to more complex applications


Public-private partnerships to share the costs and risks of AI infrastructure development


Regional cooperation frameworks like ASEAN’s DEFA to pool resources and share AI capabilities across multiple countries


Thought provoking comments

The world that’s going to win the AI arms war is the country that has the cheapest energy… I really do believe that in India we have an incredible opportunity… My first solar farm eight years ago, my revenue was 18 rupees a kilowatt hour. Today we get 2 rupees 20.

Speaker

Tejpreet S Chopra


Reason

This comment reframes the AI competition from a purely technological race to an economic sustainability challenge, introducing the concept of energy cost as the determining factor for AI dominance. It provides concrete data showing India’s dramatic cost reduction in renewable energy, suggesting a strategic advantage.


Impact

This shifted the discussion from abstract AI capabilities to practical infrastructure considerations, leading other panelists to discuss data center costs, cooling challenges, and renewable energy integration. It established energy economics as a central theme for the remainder of the panel.


I think the biggest impact is actually more on white-collar jobs rather than blue-collar jobs… it’s really impacting certain segments of the economy… a lot of it has got to do with collaborative augmentation rather than full automation

Speaker

Satvinder Singh


Reason

This insight challenges the common narrative that AI will primarily replace manual labor, instead suggesting that knowledge workers face greater disruption. The distinction between ‘collaborative augmentation’ and ‘full automation’ provides a nuanced framework for understanding AI’s impact on employment.


Impact

This comment fundamentally shifted the jobs discussion from fear-based rhetoric to a more analytical assessment. It prompted other panelists to discuss upskilling, continuous learning, and the human elements that cannot be replaced by AI, leading to a more balanced conversation about workforce transformation.


For countries like ours, we’re starting out at a severe deficit. There is not a surplus of radiologists… So AI actually comes in to help us with diagnosis, accuracy, speed of diagnosis… But to comfort and reassure those parents, that’s a human function… that cannot and can never be replaced by AI

Speaker

Dr. Mahendra Karpan


Reason

This comment provides a crucial perspective from developing nations, showing how AI can address critical skill shortages rather than create unemployment. The distinction between diagnostic capabilities and human emotional support offers a practical framework for AI deployment in healthcare.


Impact

This grounded the abstract AI discussion in real-world healthcare challenges, demonstrating how the same technology can have different implications in different contexts. It influenced the conversation toward practical applications and the complementary nature of human-AI collaboration.


Another blind spot with respect to… the huge growth… is going to be cooling. And that’s another blind spot that I think we don’t really pay attention to… we need to really think about this in a holistic sense… the water consumption

Speaker

Nihar Shah


Reason

This comment introduces critical infrastructure bottlenecks that are often overlooked in AI discussions – cooling and water consumption. It challenges the assumption that energy is the only constraint and introduces environmental sustainability concerns.


Impact

This expanded the infrastructure discussion beyond energy to include cooling and water resources, adding complexity to the conversation about AI deployment. It prompted discussions about sustainable data center design and the true environmental cost of AI infrastructure.


Scale and AI. Today you spend $2 and you generate $1 because half of the 50% goes to the AI chip company… This problem can be only solved through enabling indigenous AI chips which has a better performance and the lower cost

Speaker

Narendra Singh


Reason

This comment reveals the economic reality of AI deployment – that current costs exceed returns due to chip monopolies. The call for indigenous chip development introduces the concept of technological sovereignty as essential for AI viability.


Impact

This comment shifted the discussion from AI applications to fundamental economic viability, highlighting the importance of supply chain independence. It connected AI development to broader themes of technological sovereignty and economic sustainability.


For ASEAN… we were able to show very quickly through data that the biggest beneficiaries actually of the DEFA is not even advanced economies like Singapore… but actually are the LDCs… because they are going to be more developed

Speaker

Satvinder Singh


Reason

This insight challenges assumptions about who benefits most from digital transformation, suggesting that least developed countries may gain the most from AI and digital connectivity due to their ability to leapfrog legacy systems.


Impact

This comment introduced the concept of ‘leapfrogging’ advantage for developing nations, influencing the discussion toward how emerging economies might actually have strategic advantages in AI adoption. It provided a more optimistic framework for Global South AI development.


Trust must be designed from day one, not retrofitted after deployment. Transparency, auditability, grievance redress, open architecture are not compliance burdens. They’re adoption accelerators.

Speaker

Dipali Khanna


Reason

This reframes trust and governance mechanisms from obstacles to enablers of AI adoption, challenging the common perception that regulation slows innovation. It provides a strategic framework for building trustworthy AI systems.


Impact

This comment fundamentally shifted the governance discussion from viewing regulation as friction to seeing it as infrastructure for scale. It influenced subsequent discussions about building trust mechanisms and the relationship between safety and adoption.


Overall assessment

These key comments transformed what could have been a superficial discussion about AI benefits into a sophisticated analysis of the practical challenges and opportunities for AI deployment in emerging economies. The insights collectively shifted the conversation from theoretical frameworks to operational realities, introducing critical considerations like energy economics, infrastructure bottlenecks, economic viability, and the unique advantages that developing nations might possess. The comments created a more nuanced understanding of AI’s impact, moving beyond simple narratives of job displacement or technological determinism to explore complex interdependencies between technology, economics, governance, and social needs. This elevated the discussion to a strategic level that could inform actual policy and investment decisions.


Follow-up questions

How can hydrogen fuel cells be implemented at large scale in railways and buses, given the current bottlenecks?

Speaker

Harsh Vartan (Audience member)


Explanation

This question addresses the gap between experimental use and large-scale implementation of hydrogen fuel cells in transportation, highlighting infrastructure and cost challenges that need resolution.


What are the specific technical barriers and cost challenges for AI pilot companies to achieve full-time impact and scale?

Speaker

CTO at MindEquity.ai (Audience member)


Explanation

This question focuses on the practical challenges startups face in scaling AI solutions, particularly the cost-revenue imbalance where companies spend $2 to generate $1 due to high AI chip costs.


How can upskilling and reskilling strategies effectively preserve jobs while maintaining human-in-the-loop systems?

Speaker

Audience member


Explanation

This addresses the critical concern about job displacement by AI and seeks practical solutions for workforce transition and human-AI collaboration.


What specific subsidies and incentives should be provided for AI projects to catalyze adoption similar to the solar revolution in India?

Speaker

Audience member


Explanation

This question draws parallels between renewable energy adoption success and potential AI adoption strategies, seeking policy frameworks to accelerate AI implementation.


How should governments balance AI adoption with job preservation, particularly in sectors like call centers where AI is more expensive but displaces human workers?

Speaker

Narendra Singh


Explanation

This highlights the policy dilemma where AI adoption may be economically inefficient but socially disruptive, requiring careful government intervention strategies.


What are the long-term implications of AI on white-collar versus blue-collar jobs, and how should societies prepare for potential full automation?

Speaker

Satvinder Singh


Explanation

This addresses the differential impact of AI across job categories and the need for societal preparation for potential widespread automation beyond current collaborative models.


How can countries develop indigenous AI chips to reduce costs and dependency on current expensive chip providers?

Speaker

Narendra Singh


Explanation

This focuses on the critical infrastructure challenge of AI chip costs and the need for sovereign AI capabilities to make AI economically viable at scale.


What are the specific cooling and water consumption requirements for AI data centers, and how can these be addressed sustainably?

Speaker

Nihar Shah


Explanation

This identifies often-overlooked infrastructure challenges beyond energy consumption that are critical for sustainable AI deployment at scale.


How can edge computing solutions be balanced with cloud-based AI infrastructure to serve different market segments effectively?

Speaker

Tejpreet S Chopra


Explanation

This addresses the strategic question of AI deployment architecture, particularly for serving MSMEs and manufacturing sectors that may need on-premise solutions.


What specific governance frameworks and ethical guidelines are needed for AI deployment in healthcare, particularly for telemedicine in remote areas?

Speaker

Dr. Mahendra Karpan


Explanation

This addresses the critical need for regulatory frameworks that ensure AI safety and efficacy in healthcare applications, especially in underserved regions.


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.