India AI Summit Keynote Speakers | Sam Altman | Sunil Mittal | Jeet Adani | Bharat Mandapam LIVE

And he's well just getting started. Please welcome the co-founder and CEO of Google DeepMind, Sir Demis Hassabis.

Thank you. It's a huge honor to be here today with so many of my esteemed colleagues from industry, academia, and government. And congratulations to Prime Minister Modi and the Indian government on convening such an impressive summit at this very pivotal moment for AI. It's fantastic to see how the summit has evolved over the years with the first meeting convened by Prime Minister Sunak at Bletchley Park in the UK. It's become an incredibly important convening point for international dialogue and hopefully cooperation in the future over the future of AI.

When we started DeepMind in 2010, almost nobody was working on AI in industry. It was just a dream. And it's been incredible to see how in the last 15 years where we've come from the beginnings, those humble beginnings to now where we are today, where the whole world is talking about AI. And we hope that this will just be the first example of amazing advances in science and medicine that have been enabled by AI. And we and others are working on many other branches of science now to bring AI tools to help advance material science, fusion, physics, and mathematics. In fact, almost every branch of science and medicine can be impacted by AI.

And now in 2026, we're another threshold moment where AGI, artificial general intelligence, is on the horizon, maybe within the next 5 years. And we're seeing these general purpose systems, foundational model systems becoming increasingly capable almost week by week. So this is obviously an amazing opportunity that we should all grasp economic and productivity as well as in the sciences. But it's also something that we have to approach with humility and understanding that we don't have all the answers yet as to how this technology is going to develop and be deployed into the world.

I've been really impressed with what I've seen in India. I spent some time prior to the summit in Bangalore. We have a really big office there, Google and DeepMind, a great research office where we do some really critical research that we then bring to our products and our technologies around the world in areas like efficient models, continual learning and multilingual capabilities. I also had time to give a talk at the Indian Institute of Science at Bangalore and I was incredibly impressed by the students and the faculty there. Their enthusiasm and their energy for AI and their ideas for how to use AI to improve India's standing in the world and to also seize all the new economic opportunities and scientific opportunities that AI opens up. It's incredibly impressive to see the energy around the country and I think India will indeed be a powerhouse for AI in the and across the globe.

We have many partnerships. Sundar, you heard Sundar announce many Google partnerships that we have with India. I'm especially proud of our deep partnership with Mr. Ambani and the Reliance Jio group to bring intelligence to everyone in India with our Gemini foundation models in partnership with Reliance. So we hope to build on that in the next few years.

So if I was to try and quantify what's coming down the line with the advent of AGI, I think it's going to be one of the most momentous periods in human history. Probably something more like the advent of fire or electricity. One way maybe we can quantify that is I think it's going to be something like 10 times the impact of the industrial revolution but happening at 10 times the speed, probably unfolding in a matter of a decade rather than a century. So really there's an enormous amount of change is going to come and it's still to be written how we can make that beneficial for the whole world.

And I think the main way we should try to do this is by taking a scientific approach using the scientific method to understand what the capabilities of these systems are, to build good guardrails and monitoring systems to understand more deeply what these systems are capable of and how we can make sure that they serve the purposes that we want. And then of course simultaneously we also have to be bold to grasp these new opportunities to advance science and medicine and to improve human health and the human condition that society and the globe badly needs. So I think we've got to try and navigate this moment very carefully, very thoughtfully. And if we do so, I'm very optimistic that we'll usher in a great new era.

Thank you so much Sir Demis for your very profound and illuminating address. We really thank you. Sincere gratitude to your address ladies and gentlemen. And now I would like to invite Mr. Vishal Sikka. He's the founder and CEO of Vianai. As CEO of Infosys, Vishal Sikka led one of the most ambitious transformations in Indian IT history before leaving to build Vianai, a company focused on human-centered artificial intelligence. He is a computer scientist by training, a philosopher by temperament. He is one of the most original thinkers at the intersection of AI and enterprise. Please welcome the founder and CEO of Vianai, Mr. Vishal Sikka.

Thank you so much. Thank you so much for that. Wow. Wonderful introduction and what an amazing event. I want to share three points from a long time that I have spent in AI. My first point is that what we see today in the world of AI, people who know what they are doing with AI are astonishingly effective with AI.

Recently a friend of mine, he and I were students together at Stanford. He has a large service that he runs, open public service. That service was built by 15 people, very world-class engineers, over nine months. Recently he rebuilt that service entirely by himself in 14 days using one of the generative AI coding tools. So if you are counting that is about a more than 250 times improvement in productivity. Now he's a genius and not everyone gets a 250 times productivity gain but you will see that people who understand how to use AI are astonishingly effective with it.

And I had a similar experience recently with a customer of mine who is a distributor of home goods and one of their main suppliers shut down their factories in one of their countries. And they did analysis using our product, all kinds of simulation scenarios and over a few days they reached the decision that they need to exit that country entirely. I asked him, you know, such a monumental decision to get out of an entire country, how long would that have taken you before and he said easily it would have taken a year and it would have involved heavy duty consultants and things like that.

So we now have instant access to knowledge in any language. A condensation of things that we can present in any way. It is an incredible power and yes it is deeply disruptive to the ways that we have worked before the way that we have done things in the past. But at the same time and even more importantly we can do unprecedented things with this, things that we could never do before.

So this astonishing effectiveness and Demis referred to this as a jagged frontier. It is not uniform. Not everyone sees this. So that's my second point. Being effective with AI requires not only a knowledge of AI itself but understanding its limitations and how to overcome those limitations. There is a huge gap between LLMs and the business users inside enterprises especially and how to bring value to those users and overcoming that gap is where a lot of value creating opportunity is.

Bridging that gap requires delivering correct systems, trusted, verifiable, reliable systems that deliver value to people. My own company works in this area. A layer that sits above the language models and delivers value to business users while ensuring correctness and things like that. When we overcome that gap, we can deliver massive value. Demis talked about it just now. We can transform every existing system. Legacy systems, enormous complexities inside enterprises can be removed. Industries can be transformed. We can give end users wings. We can amplify them to deliver things that were not possible to do before that or in the best case it required professionals to do this.

Doing that also requires not just overcoming the limitations of AI but also imagination to see what is not there to see what is possible. India has all of this in great abundance. The honorable prime minister has called for a billion entrepreneurs, people who can overcome these and deliver value using AI. And I think this is exactly what the world needs and what India has the potential for.

My third point is that we not only have to master today's AI but we have to leapfrog it. AI today has enormous limitations. I have worked in AI for the last 38 years. You know one of our scriptures is Bhaja Govindam. It was written by the Shankaracharya and it has a beautiful line. What it means is that when you are faced with a life or death situation, the knowledge of a book does not help you. Knowledge without wisdom does not save us. That wisdom comes from living, from doing, from being in the world. AI today has plenty of limitations. Demis mentioned hallucinations. That's one of the main issues blocking the use of AI in enterprises.

But beyond hallucinations, understanding the world, understanding physical activities, the physical movement, this is one of the next frontiers. Safety, safety of AI, and the honorable prime minister talked about this today, is an existential issue. Swarms of agents can be made to do completely reckless things and we don't yet have ways to understand or deal with this and Demis also talked about this. We have to solve this issue. We have to deliver AI that is safe. We have done this with nuclear power for the last 80 plus years. We can and we must do this with AI.

Energy is another one of these issues. Where I live in California on Highway 101 just north of San Tomas, I drive by there every time I go to see my dad. There is a massive data center that is coming up. It's 720 megawatt. And this idea that I write a prompt and these gazillion GPUs blast into existence to produce a response and then I make a tiny change to that prompt and then I do that again. It just seems like a completely absurd idea especially to someone who has been around AI for such a long time.

I have, thanks to the Ministry of IT, honorable Ashwini Vaishnaw, I have a colleague who has been accompanying me throughout this conference and he told me that yesterday he walked 32,000 steps and I asked him what did you eat and he said I ate two burgers. Two burgers, you know we normally eat 2,000 calories in a day that's about a 100 watt light bulb, like less than one of these light bulbs and out of that our brain, our nervous system is maybe 15, 20 watt, that's like when your laptop is in sleep mode it takes more power than that. So there are many zeros still to be removed from these models and the models themselves have to be removed.

So I think that there is a tremendous opportunity here. India is a country of the human potential. We have plenty of times before delivered the ability to, you know, billion plus Indians. Mukesh talked about Jio and Sunil talked about Airtel and how now we have billion plus Indians who have data and connectivity. And when I was young one of my earliest childhood memories is of worry in my parents' faces around food. They used to tell stories of how there was a shortage of food and then the green revolution happened and India is now one of the largest exporters of food in one generation.

So I think that when you look at the time of intelligence, it is not only an opportunity to learn about this technology, to learn to master this technology, to understand its limitations, but to leapfrog that and to build the next generation of it. And as this summit so vividly demonstrates, we can be on our way to a human revolution powered by AI, by good AI, by purposeful AI where every one of us, a billion entrepreneurs, is not just making a living but is making a life. Not some artificial life or some artificial general life, but our own life and the life of others. And that would be so much fun to do. Thank you so much.

Thank you so much Mr. Sikka for your profound and very interesting remarks and of course your work at Vianai also exemplifies the transformative potential of artificial intelligence. And with this movement on the stage you can make out that now we are heading into a fireside conversation. And well this would be a remarkable conversation we're going to have with Mr. Nandan Nilekani, co-founder and chairman Infosys, and Dario Amodei, founder of Anthropic. And before I invite our guests on the stage, let me say a few words about Mr. Nandan Nilekani who is the architect of Aadhaar, the world's largest biometric identity system and the intellectual godfather of India's digital public infrastructure movement. Nandan Nilekani has spent decades proving that technology built in the public interest can transform entire societies and Aadhaar is a big example before the world. His thinking on artificial intelligence and open digital ecosystems is essential reading for anyone serious about this field. So ladies and gentlemen, I would now invite Mr. Nandan Nilekani and Mr. Dario Amodei for this conversation which is being moderated by Mr. Rahul Matan, partner Trilegal. I invite all our three guests on the stage.

Dario. Welcome Dario. Great speech in the morning. You mentioned that we are in the end of the or towards the end of the exponential. This is something that you spoke about in Machines of Loving Grace that we would have a country of geniuses in a data center. And the models over the last I guess two months have been sort of giving us a sense that we're getting there. But in your podcast with Dwarkesh you sort of walked that back a bit by saying you know we may reach a country of geniuses in a data center but the impact on society will take a long time. Can you explain what that means because we thought we'd do AGI and we'd be finished and done with it.

Yeah, thank you. Thank you for having us Rahul. You know I would say there is this duality between the fundamental capabilities of the technology and the time that it takes for those capabilities to diffuse into the world. We're getting models that are very good at software engineering, that are increasingly good at biomed innovation. We're not there yet but we're on this very fast exponential. But when I look across the world and I look across the enterprises of the world, we have many enterprises as customers, even if we froze in place what the technology was capable of today, I think the economic impact could be much greater than it is because, you know, it just takes time. And there are just frictions to adopt things through enterprises. And I think even more so in the developing world.

And you know when I visited Infosys one of the things I talked about with Nandan was, you know, we're both obviously very interested in making sure that this technology gets to everyone and Nandan has devoted a big part of his life to many things in that direction and has built out India's digital public infrastructure. And so you know I think this question of diffusion is very tied to the question of how do we make sure that everyone benefits.

So when the foundation models came Nandan you said that we should do use cases and it sounds like Dario is saying the same thing that even if we do the foundational model we will still need to do use cases.

No, I think it's great what the foundation models are doing and the speed of evolution but what we have learned is that diffusion of technology is a different ballgame and how do you get technology to a billion people. And I think India we have a little bit of experience with that. 1.4 billion people on Aadhaar, 500 million people on UPI, 20 billion transactions a month, the world's largest cash transfer system, the largest financial inclusion system, you name it, all that stuff. And we learned that diffusion is a technique. It's both an art and a science. It involves institutions, it involves policymaking, negotiations, dealing with incumbents, dealing with newcomers, strategies for execution. So the whole, you know, trust building. It's a whole host of things.

And I think if all the investments in AI are going to deliver the value to society not just to individuals we'll have to look at diffusion pathways to take this to everyone. And I think India will lead on that. That's why I've always been saying that India should focus on becoming the use case capital of the world.

You had a more recent essay which you call the adolescence of technology which is a little more somber, spoke a little bit about sort of dimming the enthusiasm of the first essay. And I want you to perhaps unpack that a little bit. You know we all have spoken about the risks of the technology but particularly in the global south where we think that AI is going to be hugely beneficial for us. We perhaps will have a different calculus on the risk-reward ratio. What do you think about that and how would your essay address that?

I think that's an insightful comment which is that I think in the global south there's an opportunity for AI to accelerate catch-up growth to solve a bunch of problems that are in the way of catch-up growth. And so you know I think AI is a technology that has big risks and big benefits but in the global south the benefits may be even bigger than they are anywhere else. But at the same time that doesn't mean of course that the risks aren't real. You know India is the world's largest democracy, we need to think about how democracies handle AI and how we confront other countries that are authoritarian. That's one of the risks I talk about.

Another risk I talk about is making sure that AI systems are safe and predictable and autonomously behave in a way that's under our control and everyone in the world has to worry about that. That affects everyone in the world. And then I think of particular relevance to India is the concerns I raised around economic displacement. Right where I think the signature of this technology is going to be that it greatly grows the economic pie for the whole world and again huge upside because the opportunity for catch-up growth, growth can be very, very fast. But you know things are going to change and there's some potential for disruption.

And you know I think what I've been thinking about as I visited India these last few days and the last time I visited is how can we work together with the companies in India to kind of drive this growth for everyone to make sure that the existing companies large and small continue to prosper along with us and the other makers of AI. And you know also on a philanthropic basis how we make sure that the benefits reach everyone both in an economic sense, in a health sense, in kind of other senses. So you know I think India offers a particularly keen distillation of especially the benefits but also the risks.

Now Nandan you've had experience with an adolescent technology with the whole DPI. In the early days of DPI it was challenging, there were challenges with getting the big vision which of course now we're looking at and in hindsight it looks like it was easy but the early days was difficult. So as the father of a mature technology would you want to give the father of an adolescent some advice?

I know that makes me a grandfather. So I think when you talk about diffusion and you have to think of AI, everybody agrees is like a general purpose technology like people give the simile to fire or electricity or whatever. It's about starting from the user and how can we improve their lives. How can we take a billion people and help them to learn better. How can we take a billion people and give them better healthcare. How can we take a half a billion farmers and improve their earnings. You have to start from there and then figure out how to make it happen. And it's not just technology. Technology is just one piece of the puzzle. It's about institutions. It's about trust building. It's about negotiations. It's about guardrails which Dario mentioned. It's about working with different stakeholders and making them go towards a common vision.

So diffusion is difficult. It's not a simple task. So I think I feel that India will demonstrate this because we have the experience of diffusion at population scale in all the various areas and obviously diffusion of AI there are some differences that we need to think about, data, guardrails and so on. But I think we can build a pathway or multiple pathways to that goal and that will show the world.

Because I believe right now in AI there's a race to the top and a race to the bottom. And the race to the bottom is faster than the race to the top. So I think all of us who have a stake in AI being useful to humanity have to accelerate and redouble our efforts to make the diffusion happen. Otherwise the consequences are going to be very, very difficult because there's going to be a backlash. If the only thing that AI does is create deep fakes or raise the price of your power bill or all the other things that are happening people are going to respond. I mean the resentment of the blue collar worker led to the train wreck of globalization. The resentment of the white collar worker is going to lead to the train wreck of AI. So I think we really have to work very hard to show profound useful cases of AI.

Dario, you were in India in October and you're back again now. You spend a lot time actually with the developer community. You clearly were impressed because you've come back so quickly. Could you tell us a little bit about you know what your experience is with how India is building and using AI. Perhaps just go through the stack. I mean enterprise, small business, startups, then developers. What's different about the way India does it?

Yeah so I would say there's just an excitement here and technical acumen and we can even see it in the statistics of usage of Claude. You know use of Claude for technical kind of programming and software engineering, mathematical tasks, the fraction is substantially higher here in India than it is in most other places in the world. And you know every time I go to speak at one of these, you know, we'll host these builder or developer events in India, just there's a lot of excitement. You know I can feel the brimming excitement of like what is something that we can build. In just the last four months, you know, the use of Claude and Claude Code has doubled in India.

And you know I'm sure it's the same for the other developers. I don't say that to promote Claude and Claude Code, it's more a statement about the kind of excitement in India. On the enterprise level, I mean, the two of us just announced a partnership just yesterday. So you know we're really excited to work with all the large enterprises in India. They know much more about the Indian market, they know much more about distribution, they know how to serve enterprises within India and they're much better at that than we are. And can we plug our technology into what they do and create something that kind of wins for both sides. We would like to be able to jointly win with the companies in India.

And then finally I think there's another element that's almost unique which is that there's an excitement to build but there's an excitement to build for public good and for philanthropic benefits. So you know Nandan kindly introduced me to the EkStep Foundation which of course builds digital infrastructure and we've already started to work on a number of projects really to reach people in rural areas. We're trying to combine Claude with something called Open AgriNet which helps farmers in rural regions to kind of find better information and better advice to be more effective and efficient and we're looking to expand that a great deal. So I think that's something totally unique to India and that through folks in the private sector we would get connected to these efforts and there would be mutual enthusiasm to promote these efforts.

And you of course have an office, you've declared a managing director but actually more importantly you set Sonnet 4.6 which dropped yesterday very inconveniently so I couldn't try it. Apparently is doing very well on 10 Indic languages so there seems to be a bit of a focus in your development as well on India. Can you tell me why that's important, why language, cultural context is important and what role India can play in that?

Yeah so you know language models have always been multilingual but of course they're better at languages that they've been trained more on. And you know of course as I learned when I first came here India has a very long tail of regional languages and you know we see this as something related to access, something related to making, we provide benefits for everyone right. If it can only speak the most common languages then there's a long tail we're not reaching. The farmers that we mentioned, many of them speak one of the less common regional languages. So we've put in place a push, you know, collaborating with folks in India to acquire more data for this long tail of Indic languages and Sonnet 4.6 represents an improvement. We're not all the way there yet. We want these models to be as good even far out in the long tail of these languages as they are at speaking English. And we're making progress towards that. We're not there yet, but we want to keep going.

Now Nandan, after you built DPI, I mean I say after like as if you stopped, you still continue to do it, but after you did the bulk of the work, you spent some time and effort actually taking it out to other countries. And I was wondering whether you've thought about that for AI. And you know as it's been mentioned so many times today that this is the first AI summit in the global south and so I think perhaps countries of the global south if there's a model as it were for doing this would benefit from those ideas. So as you think about it is it cost, is it skill, is it data, infrastructure, what is it that countries need to think about for this?

Oh sure, no, you know finally it's about a lived experience. If you have done it you can do it better next time. So what we did in the DPI part, the digital public infrastructure, is that after several years of that experience we worked with global philanthropists, set up something called Co-Develop and said let's take DPI global. And today we have some version of DPI running in about 40 countries around the world. We recently had a summit in Cape Town where we had 1,200 delegates from 109 countries. So you know it's become a global moment and we feel that AI has to be, if AI has to really be impactful we need something similar. So yesterday we just launched something called 100 Diffusion Pathways by 2030. We like to have targets.

Can you explain that?

Yeah. So the idea is that a diffusion pathway is basically a way to reach a particular goal which you got from learning from doing things and then packaging it. And it's not just technical packaging. It's about guardrails. It's about how do you get institutions on board? How do you make data available? There's a whole host of things. But think of it as a toolbox or a playbook for doing things. And then this is a global initiative. So we're going to work around the world and create multiple diffusion pathways and then share them with each other so that we can accelerate this thing. And you know Anthropic is part of that, we have Google as part of that, Gates Foundation is there, UNDP is there, the Kenyans, it's a global coalition.

Because what we learned from the agriculture experience, you know, we implemented, we worked with Maharashtra on their Agri Stack which is called Mahavistar and that took us 9 months to figure out how to make it work safely at scale. Using the same learning it was done in Ethiopia which took 3 months because we had the learning of Maharashtra. And then using the same learning the PM was very keen to see it in animal husbandry. So we worked with Amul and we did that in 3 weeks. So you can see the trajectory of time right from 9 months to 3 months to 3 weeks. So what that shows is that if we can do this lived experience and keep improving and package that and take it to the world, we'll move the implementation of AI to the real world and that I think is strategically important for the world of AI.

So 100 by 30 is the new...

Yeah, 100 diffusion pathways by 2030.

And we welcome everyone to join this moment. You have many such catchphrases but the one that really stood out to me some time ago was India needs AI and AI needs India. We've spoken a bit about the India needs AI but why does AI need India?

Because this is where we're going to show it working. You know I mean I think because of the history of India's digital journey and thanks to the leadership of Prime Minister Modi who is the biggest champion of all the work that's going on. We have a political leadership that's committed. We have technologists. We have enough people with the right value system to make this happen. And we have done this before and therefore India will be where you'll see most of the deployment of AI in a tangible way where farmers are able to make more money where children learn better where healthcare is better where people talk in their own language so you have universal access. So this is where you're going to show this and the world needs this to be shown and the AI companies need this to be shown because they have to show real stuff where this is working at scale for people. So I think yeah it's very important.

Dario if I can ask you if you were to rewrite Machines of Loving Grace which is a beautiful 20,000-word or something essay for India, if you were to think about you know what is that utopic vision of what AI could be for India what would it be? I mean obviously not 20,000 words but you know whatever few ideas you could have now.

Yeah, I mean you know I think a lot of what was there was universal but there are some things that I would accentuate that are possible when you have such a large population for running this kind of large possibility of experiments. Right you have a very large population for kind of studying and improving human health. You know there's world-class medical research so I think I would double down especially on some of the sections about accelerating the cures for diseases. You know we just had Demis who has basically solved the protein folding problem with AI and kind of shown us all the way. And you know what we need are like 50 improvements like that.

And you know the hope is working together between the AI developers and the folks who diffuse AI and do the actual medical research can all of us working together between the AI companies and folks in India really accelerate progress. I would also say accelerating the rate of economic development. You know there is so much technical potential and technical adeptness in India. And it actually almost seems like a perfect case study for the idea that AI could really accelerate economic growth because it seems like the base ingredients are all there and AI could help to tie them together.

So you know in the developed world I've wondered could AI lead us to 10% growth rates which sounds absurd but you know the thing I imagined in the positive scenario of Machines of Loving Grace. But I think here in India there's a lot of catch-up growth to be done, there's an enormous amount of technical potential and ability and as I'm seeing there's this eagerness to adopt AI. So India is one of the few places in the world where I wonder could there be 20 or 25% growth which sounds absurd, is unknown anywhere in the world but as I think about this it kind of stacks all the factors for a very bullish picture of how that growth could happen. So you know I think I could imagine India being one of the countries in the world that most embodies this, certainly the large country that most embodies this.

And Nandan with all of these things there needs to be some unlock. So if you were to advise governments of the world, governments of India, governments of the global south, what should they do to unlock this 20-25% growth that Dario dreams of?

If I get 10, I'll be happy. But I think a number of things obviously. I think people before have talked about the need to create massive compute. We need to bring in the models. I think the focus has to be on inclusion. I think this AI has to carry everybody. Everybody must feel it. Everybody must benefit from it. And that's why I think the language is very important. We want people to be able to speak to the computer in their language, in their dialect, mixing English, Hindi, Tamil, whatever needs to be done. I think that's a big thing.

And then I think making agents work for people. I think if we can make agents work for people, then it means more inclusion because they can get complex things done because you're hiding all the sophistication behind the agent. So I think there are a lot of things we can do which you'll see now in the coming years. We already have three or four examples in agriculture, in healthcare, in language, in education, in electricity. We have a very good example of P2P trading. So I think all these are examples of how AI will actually benefit people and then I think as to Dario's point India is a country which is very positive about technology in general and AI in particular and we need to take advantage of that and not let them down by giving them truly transformative applications using AI which you will see in the next two to three years.

Nandan, Dario, thank you so much. What a lovely conversation.

Thank you so much Mr. Nandan Nilekani and Mr. Dario Amodei and thank you Rahul Matan for moderating it. Well, it was quite an engaging conversation I must say and they are the pioneers and the thought leaders of artificial intelligence and they shared their profound perspectives. I thank our panelists ladies and gentlemen. Our next speaker is Mr. Rishad Premji. He is the executive chairman of Wipro. The son of one of India's most beloved business leaders, Rishad Premji has carved out his own identity as a thoughtful steward of Wipro's transformation into an artificial intelligence native technology services company. He's also an unusually candid voice on the responsibilities that business leaders carry in times of technological disruption. Ladies and gentlemen, please welcome the executive chairman of Wipro, Mr. Rishad Premji.

You know thank you for those of you who are here for being here. Once in a generation a technology emerges that doesn't just change what we can do. It truly changes what we must do. AI for me is certainly that technology and how we as a country, how India responds in the next few years will shape not just our own economic trajectory but our ability to solve problems that matter to over a billion people.

For the past several years, the conversation around AI has focused just not on the possibility. What can it do? How powerful could it become? How quickly could it evolve? But we are now at an inflection point. The conversation has fundamentally shifted from possibility to practicality, from experimentation to adoption and from pilots to scaled impact. This shift matters and it matters tremendously because technology creates value only when it is applied to solve real world problems responsibly and at scale.

So what does this moment mean for India? It means India has the opportunity to become one of the world's most consequential environments for the application of AI. Not just as a builder of the technology but as a place where AI is tested against real world complexity and made to work at scale. Our context as a country is demanding. Systems here must work across multiple languages, across urban and rural settings and across populations with very different levels of access, need, data quality and infrastructure. That raises the bar, but it also makes success meaningful.

We already see what this looks like in practice. In education, AI can support learning outcomes in local languages and help address teacher shortages and skill mismatches. In healthcare, it can enable earlier disease screening and strengthen rural care, especially where access is limited. And in public services, it can help build smarter, safer infrastructure and reduce leakages in welfare delivery.

Which brings me to India's strengths and why I believe India is well placed today to take advantage of all of this. Let me just highlight a few that matter most and have been highlighted by many. One of the most significant is our experience with DPI. UPI today processes over 20 billion transactions every month and has transformed how individuals and businesses participate in the digital economy. It has demonstrated that technology can scale rapidly when it is accessible, reliable and most importantly inclusive.

India also has one of the largest and fastest growing pools of AI talent in the world. We are truly the AI talent destination of the world. Approximately 650,000 professionals in India work in AI related roles today and this number will double by 2027. This talent brings not only technical capability but importantly practical experience in applying technology in complex real world environments.

Equally importantly many of the foundations to build out this talent are already in place. Government initiatives to train 10 million young people in AI along with industry partnerships with universities are expanding access to practical job-ready training. Curriculum is evolving and people are giving opportunities as apprenticeships to get exposure to real world applications. This capability is reinforced by a vibrant innovation ecosystem.

India is home, as many of us know, to the world's third largest technology startup base, including more than 4,000 startups in the deep tech and AI space. Together, these companies are helping translate technological capability into practical real world applications.

We are already seeing what this looks like on the ground. In agriculture for example, farmers across Karnataka, Maharashtra, Telangana, AP and Punjab are using AI systems trained on satellite imagery and local crop data. These systems provide early pest alerts and in some regions have reduced crop losses by nearly 25%.

In small commerce, artisans in Gujarat, Tamil Nadu and UP are using AI related platforms connected to open networks. Products are automatically cataloged, descriptions translated across languages, prices optimized, and logistics coordinated, allowing small sellers to reach markets that were once out of reach. And we are also seeing deliberate investments in the future. National initiatives are expanding access to compute infrastructure and building capacity across the AI stack in our country.

At the same time and equally importantly, we as a country are taking a very pragmatic approach to governance, putting early guardrails in place, but balancing accountability with innovation so AI can scale safely and with confidence.

All of this lays a strong foundation for India to lead in the AI era. But there is one more factor that I believe positions us as a country uniquely. Our long engagement with global enterprises. Today the constraint as many have said is not access to technology. The real world begins when AI is introduced into large real world organizations.

In those environments, technology has evolved over many years. Application landscapes are complex. Data is fragmented. Workflows are siloed. Processes vary across geography, business units, and regulatory regimes. Decision making is rarely uniform.

Making AI work in this environment means modernizing legacy architectures. It means curating and labeling data to create highly specialized context-aware models. It means orchestrating across agents in ways that are reliable and secure. And it means earning confidence of security teams, risk leaders, regulators, and critically the people who are expected to use these systems every day. This is where a more practical pattern has emerged in enterprises.

Models designed for specific processes or decisions tend to deliver the most...

Reliable results. When AI is closely aligned to a defined workflow, it becomes more predictable, easier to govern, and more effective over time. What enterprises need today is not a model that does everything, but models that do the right thing consistently inside how work actually happens. But technology alignment alone is not enough for these systems to deliver value in organizations. Organizations themselves will have to invest in change, taking people truly along, helping them adapt to new ways of working, redesigning roles and decision-making, and building confidence in how AI is used. That includes reskilling people, reskilling teams to work effectively with AI tools so that they understand the outputs and exercise judgment where it matters most.

When models are well aligned to workflows and people are supported through the transition, AI becomes not just deployable but sustainable at scale, and that plays directly to India's strengths. We have decades of experience working inside complex enterprises, helping them modernize systems, manage risk, and take people along through this change. And that works in environments like these is not just deployable, it is resilient, responsible, and truly scalable.

The same dynamics that determine success inside organizations will also shape how countries navigate this moment. As we look ahead, India's advantage in AI will not be defined only by the size of our models or the scale of our infrastructure. It'll be defined by the choices we make about where we apply AI, how we diffuse it, how responsibly it is deployed, and whether we can translate capability into real impact for governments, citizens, and enterprises.

India's advantage will come from developing talent at scale. Not just people trained on AI, but people who can apply it with context, judgment, and an ability to adapt to change. That is why AI fluency must extend beyond engineers to teachers, to nurses, to administrators, to supervisors, to small business owners, among everyone else. The dividing line will not be human versus machine. It will truly be between those who adapt and those who hesitate to adapt.

Technology shifts inevitably create uncertainty. But for countries that act decisively, they also create opportunity. India has embraced such shifts in the past and I believe we are really well positioned to do so again.

I want to close by sharing a personal story from the work of the Azim Premji Foundation, which is also the majority shareholder of our company, Wipro. You know, India sees 2.7 million tuberculosis cases every year, making it one of the country's most serious public health challenges.

Early detection is essential, but confirming TB often requires patients to travel to distant public hospitals for sputum molecular tests. For many, the real barrier is not medical capability, but access. To address this, our foundation is running a pilot in a rural community in Tamil Nadu. Community health workers carry portable X-ray devices directly to people's homes. AI analyzes the X-rays instantly and identifies signs consistent with TB, enabling early screening and faster referral without requiring patients to travel. If successful, this approach can help detect TB earlier and extend the reach of healthcare into communities that need it most. With a national doctor-to-population ratio of roughly 1 to 800 and even deeper shortages in rural India, AI does not replace care. It multiplies scarce expertise infinitely.

The same last-mile challenges exist across other countries in continents of Asia, Africa, and Latin America, home to more than four billion people. Solutions that work here in India at scale, low-cost, multilingual, and resilient can travel far beyond our own borders.

If we can do that, India's contribution can be vast. Not just in building AI, but in applying it to solve problems for enterprises, for our own country, and for the world at large, thoughtfully, inclusively, and with impact at scale. Thank you for listening to me.

Thank you so much, Mr. Premji, for your visionary insights, which I'm sure will undoubtedly guide the path forward. And we also thank Mr. Premji for highlighting how AI is being used by Wipro for human-centric projects and for the welfare that is what India is aiming at, to have an impact at ground level to change the lives of human beings. Ladies and gentlemen, few individuals have done more to bring artificial general intelligence from the realm of science fiction into boardrooms, into parliaments, and living rooms than our next speaker, Sam Altman, CEO, OpenAI. Under his leadership, OpenAI launched ChatGPT and forced the world to reevaluate its relationship with artificial intelligence. So, ladies and gentlemen, please welcome CEO of OpenAI, Mr. Sam Altman.

Thank you so much. It's really a treat to be here in India, and it's incredible to see the country's leadership in advanced AI. I was last here a little over a year ago, and it's striking how much progress has happened since then. We've gone from AI systems that struggled with high school-level math to systems that can do research-level mathematics now and derive novel results in theoretical physics.

It's also striking how much progress India has made in its mission to put AI to work for more people in more parts of the country. And India's leadership in sovereign AI, building on infrastructure, SLMs, and much more, has been great to watch. More than 100 million people in India use ChatGPT every week. More than a third of them are students. India is also the fastest-growing market now for Codex, our coding agent that works to help people develop software faster and better.

India, the world's largest democracy, will decide what our future is going to look like, and it's important to move quickly. On our current trajectory, we believe we may be only a couple of years away from early versions of true superintelligence. If we are right, by the end of 2028, more of the world's intellectual capacity could reside inside of data centers than outside of them. This is an extraordinary statement to make, and of course, we could be wrong, but I think it really bears serious consideration.

A superintelligence at some point on its development curve would be capable of doing a better job being the CEO of a major company than any executive, certainly me, or doing better research than our best scientists. As we prepare for this possibility, we are guided by three core beliefs.

Number one, we believe that democratization of AI is the only fair and safe path forward. Democratization of AI is the best way to ensure that humanity flourishes. On the other hand, centralization of this technology in one company or country could lead to ruin. The desirable future a couple of decades from now has got to look like a world of liberty, democracy, widespread flourishing, and an increase in human agency.

Some people want effective totalitarianism in exchange for a cure for cancer. I don't think we should accept that trade-off, nor do I think we need to. AI should extend individual human will. We'll probably need superintelligence to help us figure out the new governance mechanisms to ensure that this happens fairly at scale and to avoid problems like extremely unbalanced compute access or something else.

Second, we believe that AI resilience is a core safety strategy. We don't mean that this is the only safety strategy. We will continue to need to build safe systems and solve difficult technical alignment challenges. But increasingly, we need to start broadening how we think about safety to include societal resilience. No AI lab, no AI system can deliver a good future on their own. For an obvious example, there'll be extremely capable bio models available open source that could help people create new pathogens. We need a society-wide approach about how we're going to defend against this.

And third, this future of AI is not going to unfold exactly like anyone predicts. And we believe that many people need to have a stake in shaping the outcome. The development of AI has already held many surprises, and I assume there are bigger ones to come. We understand that with technology this powerful, people want answers. But it's important to be humble about what we don't know, and always remember that sometimes our best guesses are wrong. Most of the important discoveries happen when technology and society meet, sometimes have some friction, and co-evolve.

For example, we don't yet know how to think about some superintelligence being aligned with dictators and totalitarian countries. We don't know how to think about countries using AI to fight new kinds of war with each other. We don't know how to think about when and whether countries are going to have to think about new forms of social contracts. But we think it's important to have more understanding and society-wide debate before we're all surprised.

Of special note and related to all three points, we continue to believe that iterative deployment is a key strategic insight and that society needs to contend with and use each successive new level of AI capability, have time to integrate it, understand it, and decide how to move forward. This has been working surprisingly well so far.

If we are right and systems continue to improve at this pace, it's going to change the economics of a lot of things. A really great thing about AI progress is that it looks like many things are going to get much cheaper and have much faster economic growth. We're already seeing what AI is doing for access to high-quality healthcare, education, and more. In the coming years, we expect to see robots make many products and physical goods cheaper as supply chains get automated. The limit to how far this cost reduction can go may only be government policy.

But the other side of this coin is that current jobs are going to get disrupted. As AI can do more and more of the things that drive our economy today, it'll be very hard to outwork a GPU in many ways. It'll be easy in some other ways. For example, we really seem hardwired to care about other people much more than we care about machines. We're somewhat less concerned about the long-term future. Technology always disrupts jobs. We always find new and better things to do. The people of 500 years ago would have thought that our current jobs often look silly, like ways to entertain ourselves, create stress. And the people 500 years from now hopefully will look at us, hopefully look to us like impossibly rich people playing games, trying to find ways to pass their times. But we should all hope that they feel much more fulfilled than we do today.

I'm confident we will keep being driven to be useful to each other, to express our creativity, to gain status, to compete, and much more. But the specifics of what we do day-to-day will probably look very different. Each generation has built on the work of the generations before, and with new tools, the scaffolding gets a little taller. This collective external lattice, the set of tools that we have built up around ourselves, is remarkable, and we are capable of doing things that our great-great-grandparents couldn't have dreamed possible.

It is a moral imperative to make sure that our great-great-grandchildren can say the same. And technology, and especially AI, is how we're going to get there. For a democratic AI future, it is not enough to just give people tools and wealth. We also need to give them agency and power. The vision that AI companies lay out fundamentally reduces to either unilateral control or decentralized power.

Sharing control means accepting that some things are going to go wrong in exchange for not having one thing go mega wrong: cemented totalitarian control. This is a fundamental trade-off of democracy, and it is one that we believe in very strongly as the way to give everyone collective agency over the future.

Of course, this is not to suggest that we won't need any regulation or safeguards. We obviously do urgently, like we have for other powerful technologies. In particular, we expect the world may need something like the IAEA for international coordination of AI, and especially for it to have the ability to rapidly respond to changing circumstances. The next few years will test global society as this technology continues to improve at a rapid pace. We can choose to either empower people or concentrate power. Thank you very much.

Thank you, Mr. Sam Altman, for your very interesting and compelling remarks. Ladies and gentlemen, I would like to now welcome Mr. Brad Smith, Vice Chair and President, Microsoft. Mr. Brad Smith has been Microsoft's conscience and its chief diplomat through some of the most consequential debates in technology policy, from privacy and cybersecurity to AI regulation. His book, Tools and Weapons, remains one of the most lucid accounts of the responsibilities tech companies carry in the modern world. So, please welcome the Vice Chair and President of Microsoft, Mr. Brad Smith.

Good afternoon. It's always an important day when the world comes together under one roof as we have today. It gives us an opportunity together to ask important questions, even hard questions, and think about how we want to answer them. As we think about this summit, the first AI summit in the Global South, it's only right that we start, I believe, by focusing on AI and what it means for the Global South. In some ways, I think the best way to start thinking about AI is to look more broadly and think about the state of the world in which we live.

We live in a tumultuous time and in a fragmented world. But I think in so many ways, the deepest and most enduring divide has been the economic divide between the Global North and South. And what I believe we need to recognize is that this economic divide is a result more than anything else of a technology divide. The technology divide created by unequal access to electricity.

Electricity became one of humanity's most important general-purpose technologies. Meaning it spread across economies. It was applied in every industry. It boosted productivity. Where electricity went, economic development and prosperity followed. But as we all know, electricity did not spread everywhere at the same pace. It was literally 144 years ago that the first electrical power plant started operating in lower Manhattan. And yet we come together today and we still live in a world where 700 million people lack access to electricity.

Now comes AI. AI, perhaps more than any other technology this century, will play a bigger role either in closing this economic divide or in exacerbating it and making it even wider. That is perhaps the single most important question for us, I would suggest today, as we think about the role of AI in the Global South. How can we do better? Because we need to do better.

What will it take? I think it's going to take a few things that will require that we all come together and work together. First, the obvious. We need to bring infrastructure to the Global South. That means data centers and compute. It also means more connectivity. It means more electricity. That is going to take not only the world's best technology, it's going to require an enormous amount of investment.

That's why we at Microsoft announced yesterday morning that we're on pace to spend $50 billion by the end of this decade to bring AI to the Global South. And of all the countries in which we are investing, India, not surprisingly, is one of the largest. But we'll need to harness private capital, investments from tech companies, other sources of private capital, government funding. We'll need governments and others to generate demand for the use of AI in the Global South because that is the only way to get the wheels of the market spinning and to do what we need to do together. That's the first thing we need to do together.

There's a second thing we need to do. We've talked about it here already today, and it is so clear when you study the history of technology. Infrastructure is not only hardware. It's not only wires and grids. It's skilling for people. Because the key to scale is to give people across the country access to the skills they need to put it to work. And that's why it's such good news that we see so many governments, supported by the United Nations and supported by private companies, investing in more skilling.

It's actually something that should speak to all of us. Certainly, as a tech company, we're committed. We've launched through Microsoft Elevate new initiatives, including one we're announcing this week, Microsoft Elevate for Educators, to equip teachers with access to help their students learn how to use AI. But the truth, it doesn't matter where you work, you have a role to play. Because the lesson of digital technology, I was an example of this, was that it took employers to open their doors to computing. It takes employers today to open their doors to new AI tools. It will take employers to invest in the skilling of their employees. It's not just for the next generation, it's for every generation that this fully matters.

Then there's a third challenge for the Global South. We need to make AI work effectively for the Global South, and that requires some special initiatives, at least two. First, we need to make AI as effective in every language as it is in English. And today it is not. Performance tests show that's the case. That's why one of the good things to come out of this week is new announcements to invest upstream in better data in other languages, to provide better tools and measurement systems for AI that is built in other languages, to build out data provenance with a view to linguistic diversity. Diversity that we need to advance around the world.

And we need to use AI in the Global South to solve the problems that matter to the Global South. Oftentimes, as we're doing here in India, that's about improvements in agriculture, or as a number of partners, including Microsoft, are doing this week, launching a new initiative to address food security across Africa. These are just two of the myriad of opportunities we have to put AI to work in ways that will bring faster benefits to countries in most of the world.

If we do those three things well—build infrastructure, invest in skilling, address real-world problems—then I think it may create the foundation to think more and do more about the question I am willing to bet will be a bigger part of the conversation in the next few AI summits: What will AI mean for the future of work and jobs?

Within these walls, I think we're mostly enthusiastic about the future of AI. But outside these walls, I think we need to recognize that increasingly around the world, and especially in some countries, many parents are asking a common question: What will AI mean for my kids? What will AI mean for my family? What will AI mean for our future? I get it that some people are excited and they'll do well, but what about us? Us meaning most of the people who live on this planet?

I think we have something to prove. I think we have something to prove not only to communities and countries and our customers, but to ourselves that we can not only embrace but pursue a brighter future for people. It's great to come to conferences like this and hear people talk about all of the advances in technology, but let's remember one other thing as well. Human capability is neither fixed nor finite. It's great to think about what it would mean to have computers in a data center that would be like a country of geniuses. But let's also recognize this: compared to the people who lived in the Bronze Age, all of you, all of us, are already geniuses.

Whenever technology advances, it creates a new platform, a new foundation that enables people to stand taller and reach higher, if and only if we're committed to using that technology. Well, as AI makes it possible to cure more diseases, then it is right that we expect that it will improve human health. As we use AI already every day to find faster answers, it gives us the opportunity to ask more questions. The fundamental fuel of human capability has always been the same: curiosity. We need to look at AI as the next great generator for human curiosity, and we need to take some inspiration, because we all know the world could use a little more inspiration.

I often think about the following. Before the invention of the washing machine, it took someone, almost always a woman, between six and eight hours to wash a load of laundry. But as the washing machine improved, that was compressed to 30 minutes. But do you know what happened? One thing happened more than anything else. Everyone wanted to wear cleaner clothes. Everyone expected to wear cleaner clothes. People did their laundry a lot more often. They had better clothes, and they had more time, and they put that time to work to do more with their lives.

Ultimately, that is the question for us, and this too is not just a question for companies. This is about what tech will do to people. It's people will use technology to do for, and it's not people who create products. It's every government. It's every company. It's every nonprofit. It's every employer, because we all have the opportunity to work with our people to manage through the change that is coming, to show people how with the right AI skills, they can create jobs and careers that will be brighter for their future. That will not be easy. But if that's not our goal, then we're missing the big picture.

As we come away from this AI summit, it reflects so much progress. But I would say one thing as well. Each of these AI summits is a proud moment for a great nation. But we have an opportunity. Rather than have summits that are islands that are disconnected from the summits before or that follow, we need to build bridges. We need to build bridges between these summits. We need to define clear goals. We need to have common measurement systems. And every year we need to ask the same question: Did we make 12 months of progress in the year that just preceded our meeting? So how can we build on that progress to do more and move faster in the year ahead?

For those of us who come to these meetings in different countries every year, I hope we will take that away. Let's aim higher, not just for technology, but for what technology can do for people. Let's be clear in defining what we want to accomplish. Let's put in place the ability for us to measure our progress and all hold ourselves accountable as a global community. If we can do these things, then we can use these summits and we can use this next generation of technology to build a better world. I know that's what we within these walls want ourselves to do. But even more than that, I know that the people outside these walls are hoping and expecting us to do just that. Thank you very much.

Thank you so much, Mr. Brad Smith, for that very energizing address. Ladies and gentlemen, I think he really deserves an energetic applause from you all. His address has actually given a very constructive direction to the discourse on artificial intelligence. And well, now we are moving to the next conversation, for which our guest is the person who's often called the godfather of deep learning. Our guest is Mr. Yann LeCun, Executive Chairman, Advanced Machine Intelligence Labs, and his foundational work on convolutional neural networks underpins virtually every image recognition system in use today. Now at the frontier of next-generation AI architectures, he's one of the field's most provocative and independent voices. Please welcome our next speaker, Mr. Yann LeCun. And this conversation will be moderated by Miss Maria Shaikh, Managing Editor, India Today. Please welcome our guest and our moderator, Mr. Yann LeCun.

Good afternoon, everyone. So let's begin with the big idea here, Professor LeCun. Are we on a path to creating the smartest mind that humanity has ever known? And will that happen in our lifetime?

Maybe in the lifetime of some people here. Possibly not in mine. We'll see. It will take a while. But I think the more interesting thing that we're going to build is an amplifier for human intelligence. So maybe not an entity that surpasses human intelligence in all domains, although that will happen at some point, but at least something that will amplify human intelligence in ways that will accelerate progress.

So then will we end up defining and redefining genius? What will a genius be?

Well, you know, I think several thousand years ago or even a few centuries ago, what people identified as genius is very different from what we currently identify as genius. And I think there will be more evolution of that concept of genius. You know, in the past, perhaps, you know, genius was, you know, some act of creation or invention, but maybe not at the theoretical level like we tend to think of it today. It was, you know, more practical. Certainly in the very ancient past, people who figured out how to cultivate crops or domesticate animals probably were seen as genius.

So, you know, we have often seen, and this is a thought that you have all, you know, pretty openly shared, that AI is powerful but not intelligent. When we make that distinction, and there are conversations around LLMs, where do you see intelligence and AI-driven power?

Yeah, I think there's a lot of confusion, really, because we tend to anthropomorphize systems that can reproduce certain human functions. So what's, I mean, LLMs are incredibly useful. There's no question about that. And they do amplify human intelligence like computer technology going back to the 1940s. But LLMs, to some extent, except for a few domains, are mostly information retrieval systems. They can compress a lot of factual knowledge that has been previously produced by humans and can give easy access to it. In a way, it's kind of a natural evolution of, you know, the printing press, the libraries, the internet, and search engines, right? It's just a more efficient way to access information. And there are a few domains where the intelligent capabilities of those systems actually is more than that. It's more than just retrieval. So for generating code, maybe doing some type of mathematics, you know, we're getting the impression that it's beyond this, but it's still to a large extent domains where reasoning has to do with manipulating symbols.

The problem is that, you know, why do we have systems that can pass the bar exam and win mathematics olympiads, but we don't have domestic robots? We don't even have self-driving cars, and we certainly do not have self-driving cars that can teach themselves to drive in 20 hours of practice like any 17-year-old. So, we're missing something big still.

So, what are we teaching a 17-year-old then?

Well, so the, you know, the question is how does a baby learn or even an animal, right? Animals have a much better understanding of the physical world than any AI systems that we have today. Which is why, you know, we don't have smart robots. And so, you know, we learn about the world, how the world works, mostly by observation when we are babies, a few months old, and then we learn by interaction, and we learn mental models of the world that allows us to apprehend any new situation even if we haven't been, you know, exposed to it beforehand, we can still handle it. So, a big buzzword in AI today is world models, and this is really this idea that we develop mental models of the world that allow us to think ahead, to apprehend new situations, plan sequence of actions, reason, and predict the consequences of our actions, which is absolutely critical, and LLMs don't do this really.

There is the sense, Professor, that perhaps AI will unlock an era of radical abundance. Will this abundance benefit us?

Well, so there, you know, if you talk to economists, they tell you, you know, if we can measure the improvement that AI will bring to productivity, which is, you know, amount of wealth produced per hour worked, is going to add up to maybe 6% per year. Okay, this is from economists that actually have studied the effect of technological revolutions on the labor market and the economy. People like Philippe Aghion or Erik Brynjolfsson. And so that seems small. It's actually quite big, and you know, it's certainly going to accelerate scientific progress, progress in medicine. I do not believe there's going to be like a singular identifiable point where the economy is going to take off and there's going to be abundance. And there's also the question of the, you know, policies surrounding this, you know, are those benefits going to be shared across humanity or, you know, different categories of people in various countries, and that's a political question, has nothing to do with technology.

So if economists see this as a boom, will then openness survive?

It's not going to be an event. It's going to be progressive. There is this false idea that somehow at some point we're going to discover the secret of, you know, human-level intelligence. I don't like the phrase AGI because human intelligence is specialized. So, I don't like the, you know, artificial general intelligence phrase, but it's not going to be an event. We're not going to discover one secret. We're going to make continuous progress, and we're not going to be able to measure that progress by just having a series of tests that are going to test, you know, whether a machine is more intelligent than humans, because machines are already more intelligent than humans on a large number, a growing number of narrow tasks. And so, you know, it's not like a uniform, you know, scalar measurement of quality. It's a collection of quality. But what's more important is that intelligence is not just a collection of skills. It's an ability to learn new skills extremely quickly and even to accomplish new tasks without being trained to do it the first time we apprehend it. That's really what intelligence should be measured at. So we're not going to be able to just design a test that is going to figure out, you know, are machines more intelligent than humans.

So if it's about upskilling and ensuring that you're relevant, then only perhaps you're intelligent. Will that then mean that the countries that adopt AI, and the, you know, the pace at which India and the scale at which India has adopted AI, the challenge would be to create talent which is upskilled and reskilled and have the required skills for this?

Absolutely. So the relationship that we're going to have with intelligent AI systems is going to be similar to the relationship that a leader in business, politics, or academia, or some other domain has with their staff. Okay, AI is going to be our staff. Every one of us is going to be a manager of a staff of, you know, intelligent machines. They'll do our bidding. They might be smarter than us, but, you know, certainly if you are an academic or a politician, you work with staff that are smarter than you. In fact, that's the whole point. You need to, you know, attract people who are smarter than you because that's what makes you more productive. You know, for an academic, it's students who are smarter than their professor, and it's not the professor that teaches graduate students, it's the other way around actually. And certainly, we have a lot of examples of politicians who are surrounded by people who are smarter than them.

Earlier today, when Prime Minister Modi addressed the gathering, he said that India doesn't fear AI. We are seeing this as our destiny, future, which is 'bhagirath'. Do you see that with a summit of this nature being hosted in India, it's a message to the Global South, and that's where perhaps the next big innovation in AI could be coming from?

Well, long-term, it's going to come from countries that have favorable demographics, and that means India, Africa. You know, the youth is the most creative part of humanity, and there's a sort of deficit of that in the North largely. So, you know, the scientists of the future, and in fact many of the present, are from India, and in the future will be from mostly Africa. So, what does that mean, though? It means having incentives for young people to kind of study, first of all. So the idea that somehow we don't need to study anymore because AI is going to do it for us, and, you know, that's completely false, absolutely completely false. And it's not because I'm a professor, okay, that I'm saying this. On the contrary, we're going to have to study more. We see, for example, a trend where in industry, in the past, in certain countries, it's certainly true for India, but it's also true in European countries, and certainly in the US, we see more demand for people with more education, at the PhD level, for example. The demand for PhD-level scientists in industry has grown in the last 15 years, in part because of AI, but because of everything, because technological progress hinges on scientific progress, and scientific progress is brought about by scientists, and scientists mostly have done PhDs. And so there's more demand for education, not less. And so for countries in the Global South, that means, you know, investing in education and youth.

And making AI more accessible, something that India believes in, democratizing AI. 'AI for All' is the theme of this summit as well. Do you think AI can become that accessible, particularly for a country as large as ours with 1.4 billion people?

Yeah, in all kinds of ways. Unfortunately, the cost of inference for AI systems has to come down to kind of become practical for the vast majority of the population in a country like India. Right now the inference is just too expensive, and, you know, energy cost and things like that. It's mostly energy cost, actually. So this has to come down, but then it will play a role in education. AI will improve the quality of education, not degrade it, you know, once we figure out how to use it best. It will improve, you know, agriculture, and healthcare in particular.

Healthcare, of course, right?

So I don't work at Meta anymore, but there was an experiment a couple of years ago or a year ago that was run by my former colleagues where they gave smart glasses to farmers in India, and they could talk to the AI assistant to figure out, like, you know, what is this disease on my plant, or should I harvest now, or what's going to be the weather, you know, and it is being used a lot in agriculture as well.

That's right. It is assisting farmers to ensure that their produce gets better, they make right choices. But when you say about education, will AI assist education in terms of making students or youth of the country more literate, or will they become more AI dependent?

Well, I mean, we're dependent on technology, right? I'm dependent on this pair of glasses, otherwise I don't see you. So that's been with us for centuries. Yeah, we'll be dependent on AI, of course, but AI will facilitate access to knowledge and thereby kind of be a tool for education. I think the effect on society might be extrapolated from what was observed in the 15th century when the printing press started enabling the production of printed matters and the dissemination of knowledge. It had a huge effect on society worldwide, at least in countries that allowed it to flourish. And I think it's going to be a similar transformation with AI, of course, in the modern age, just more access to knowledge. The internet played also a similar role, and, you know, I think this is just going to make people more informed, smarter, able to make more rational decisions if it's deployed in the proper way.

So if you were to define this moment which we are witnessing in history, we are living it. How will you say it? Is it like the advent of electricity?

Yeah, people have made that claim, including economists. It's the new electricity. I think it's more like the new printing press, really. But again, in the sort of this vision of, you know, kind of more dissemination and sharing of knowledge and amplification of human intelligence. But, you know, the impact on society and the way countries need to be run is very difficult to predict at this point. I'm sort of an optimist in the sense that, you know, I think societies will figure out how best to use the technology for the benefits of their population.

While I am an optimist, nevertheless, I'm going to ask this question to you, Professor. Are we overestimating the change or underestimating what has struck us?

So, usually in technological shifts of this type, we are overestimating the changes in the short term and underestimating them in the long term. I think for AI it's a little bit different because there's been a huge amount of hype and expectations that, you know, the transition to human-level AI, superhuman-level AI is going to be an event and it's going to happen within the next few years, and people have been making that claim for the last 15 years and it's been false. In fact, they've been making it for the last 60 years or 70 years and it's been false. Every time in the history of AI that scientists have discovered kind of a new paradigm of AI, how you build intelligent machines, people have claimed, you know, within 10 years, the smartest entity on the planet will be a computer. And that just proved to be wrong, you know, four or five times in the last 70 years. It's still wrong. We're still very far from that. We're not very far. We're getting close, right? We're seeing the end of the tunnel, but it's not like, you know, we're going to have super intelligent systems within two years. It's just not. You know, in 20 hours of practice like a 17-year-old, even though we have millions of hours of training data of people driving cars around, we should be able to train an AI system to just imitate them. That doesn't actually quite work. It's not reliable enough.

Okay. So, let's try and wrap up this conversation with who gets to define intelligence now onwards. Will it be actually humans, machines, or both together?

Probably both together, but mostly humans. Like, we set the agenda. And the biggest difficulty is not to get fooled into thinking that a computer system is intelligent simply because it can manipulate language. We tend to think of language as the epitome of human intelligence, right? But in fact, it turns out language is easy to deal with because language is really a sequence of discrete symbols of which there is only a finite number, and that turns out to make things easy when you train a system to predict what the next word is in a text, which is what LLMs are based on.

It turns out the real world is much, much more complicated, and it's been known in computer science for many years. It's called the Moravec Paradox after roboticist Hans Moravec. And so the company I'm building and the research program I've been working on for the last 15 years or so is intelligence for the real world. You know, how to deal with high-dimensional, continuous, noisy signal that the real world is, which your house cat is perfectly able to deal with, or a squirrel, or whatever, but not computers yet. That's the big challenge for the next few years in AI, dealing with the real world. And that's the point of the company I'm building.

So AI has to deal with the real world, or real world has to deal with AI?

AI has to deal with the real world, the messiness of the real world, the unpredictability of the real world.

All right. Thank you so much for this conversation, Professor.

Thank you, Mr. Yann LeCun, for sharing your insights on artificial intelligence, and thanks, Maria, for moderating this conversation. Ladies and gentlemen, I would like to now welcome Mr. Ankur Vora. He's the President of Africa and India Offices and Chief Strategy Officer at the Gates Foundation. And well, talking about him, Ankur is a development economist by training whose life trajectory was influenced by his parents' dedication to purpose and India's economic reform that lifted millions out of poverty. Ladies and gentlemen, please welcome Mr. Ankur Vora.

Thank you, Honorable Prime Minister Modi, for hosting this summit. India's leadership on AI is remarkable. It is fitting that India is hosting the first major international AI summit in the Global South.

I grew up in Gujarat watching my parents serve patients at a community health hospital. I joined the Gates Foundation in 2013, inspired by the mission that every person deserves the chance to live a healthy and productive life. Earlier this year, I stepped into a new role overseeing the foundation's work across our Africa and India offices. I never imagined that I would stand on a stage like this at a moment like this, speaking about technology that may shape the future of billions. I feel humbled by this opportunity.

Many people predict that AI will help the world be better for everyone. Others predict it will only benefit the privileged few. But the fact is, it's not a matter of prediction. It's a choice. Technologists can choose whether we use AI to take on the world's greatest challenges or just the most profitable ones. Policymakers can choose to build rules that ensure everyone benefits and not just a few. That means governance, safeguards, infrastructure built for inclusion. Here in India, leaders have already made that choice. India has built world-class digital public infrastructure like Aadhaar and UPI.

This has improved the ease of living for billions. India is investing in Bhashini and AI Kosh to ensure languages and high-quality data sets are no longer a barrier and innovators do not have to start from scratch. During its G20 presidency, and for good reason, because of these choices, low-cost open-source AI tools are ready and improving lives already. AI is not a leap into the unknown for India. It is the next chapter in a journey of building solutions that serve everyone. If the world follows this approach, AI could possibly compress progress of the next 20 years into five. That progress means fewer children dying from preventable causes, fewer women dying in childbirth, more infectious diseases eliminated, millions rising out of poverty. If we step back, the real test of AI is simple. Will it help make people's lives better? That fundamental question guides how we think about our work in health, education, and agriculture. Since 2000, the world has cut child deaths into half. That represents millions of lives saved. Within our lifetimes, we could see the end of preventable child deaths. AI can help us get there faster. In sub-Saharan Africa, there are 6 million fewer health workers than we require. AI tools, when deployed correctly, can free up time of existing workers so they can help more patients. Last month, Bill announced Horizon 1000 in partnership with OpenAI, the government of Rwanda, and ministries of health across the regions. The effort will deploy AI tools in 1,000 primary health clinics across Africa. Imagine visiting a local health center that offers AI-powered guidance. Simple cases can be resolved immediately, complex ones are referred appropriately, and millions of lives are saved. AI will not just speed up innovation, it can help bring that innovation to community clinics, to health workers like my parents, and to the patients who depend on them. That is expanded access. Another area where AI can make a material difference is in education. There are two hard problems in education. First, accurately assess, and second, once a teacher knows that, helping her customize her lesson plans for that child. Earlier in my career, I worked to bring Pratham's Teaching at the Right Level model to Africa, to Ghana. I have seen firsthand that it works, but the challenge has always been about cost and scalability. AI now makes that challenge surmountable. It makes activities like personalized assessment far more affordable and easier to implement at scale. With Vakwani AI here in India, we developed a tool that analyzes short audio clips of children reading. Each assessment takes only 2 minutes. It costs about 5 paisa. That is less than 1 cent per child. The result is more children being supported, more hardworking teachers having the time and ability to do the things that they love the most, shaping the next generation. 6 million children in Rajasthan and my home state of Gujarat have already benefited from this revolution. So it is clear AI will make a difference in health and education. But can it also help advance economic opportunities for the poorest? More than half of the workforce in the global south is engaged in agriculture. Every country that has moved out of poverty has seen rising farm productivity. For a farmer, every cropping season comes down to a handful of decisions: what to plant, when to plant, what seeds to buy, what fertilizers to use, when to sell. If even one of these decisions goes wrong, it can wipe out an entire year of income. And that does not just affect a harvest. It affects the choices the farmer's family can make for that year. AI can ease that uncertainty. It can provide timely localized information so farmers can make better decisions with confidence. Earlier this week, Bill and I met Annapurna, a banana farmer in Andhra Pradesh. She showed us how she used an AI assistant on her phone to identify a pest attacking her crop. She took a photo on her app. Within minutes, she saw technology help her in real time to save her harvest and protect her family for the season. When Bill and Melinda first thought about the Gates Foundation, the vision behind it was simple. Innovation should serve those who are left behind. At that time it meant vaccines, diagnostics, better delivery systems. Today it also must mean artificial intelligence. Globally, the Gates Foundation has three objectives. No mother or baby should die of preventable causes. The next generation of people should grow up in a world without infectious diseases. And millions of people should escape the clutches of poverty. AI can accelerate progress across all three. For the first time, we can deliver precision at scale, replacing one-size-fits-all solutions with the right-fit solutions that are cheaper, faster, and more inclusive. To support these efforts, the Gates Foundation is launching Advantage India for AI. Yes, that is AI for AI. This initiative will bring together innovators and philanthropists across India and the global south to advance AI for social good. Ultimately, history will not remember the models we perfect or the speeches we give. It will remember the lives we improve. It's not a prediction. It's a choice. Thank you.

Thank you, Mr. Nilekani. Your perspectives on leveraging AI for social impact have undoubtedly added depth to this summit. And ladies and gentlemen, our next speaker is Ms. Julie Sweet, Chair and CEO of Accenture. Ms. Sweet has repositioned Accenture as one of the world's largest AI and technology transformation companies, deploying hundreds of thousands of professionals across every sector of the global economy. Her perspective on what AI adoption actually looks like at scale, beyond the hype, is grounded in hard operational reality. So please welcome the CEO of Accenture, Ms. Julie Sweet.

Thank you, Prime Minister Modi, Minister Vaishnaw, and your outstanding teams for convening us for this critical summit around AI. The breadth of distinguished guests from around the world is a recognition of the importance of broad global partnerships to capture the incredible potential of AI and address the risks. It is also a recognition of the importance of India in our AI-enabled future. At Accenture, we're incredibly proud to have over 350,000 and growing reinventors here in India. We also have one of the largest AI workforces in the world, tightly integrated with our growing AI hubs in the US, Europe, the Middle East, and Japan. And I want to take this time to thank all of our people in India for your incredible commitment to value and to our clients. Today I want to leave you with three perspectives that we believe will help us ensure that AI's immense potential is captured for the benefit of all. First, using AI as an engine for growth is the only path for global prosperity for all. Second, the agenda ahead of us is unprecedented. Companies, countries, and individuals must reinvent how they work, how they work together, and how they learn. And finally, it is humans in the lead, not humans in the loop, that will determine our future. As we turn to the imperative for growth, I want to take you back for a moment to 2013. Oxford University had just published a widely read study that said based on technology progress at that time, 47% of US jobs would be automatable. Dire headlines and predictions soon followed. One of those technologies was robotic process automation or RPA. And there were predictions that IT services would be badly damaged because it would automate so many jobs. And in fact, we used RPA to automate thousands of jobs. And we also as an industry embraced the new technologies of digital and classical AI and we created many, many more jobs. We helped our clients adopt RPA and those who did created investment capacity to invest in new technologies and to grow. And in fact, the IT services industry has thrived over the last decade, including many of India's most successful companies that you've heard from today. At Accenture alone, in 2013 we were roughly 275,000 people and $29 billion in revenue. And today we're over 750,000 and growing and $70 billion in revenue. What the last decade has taught us is a critical lesson. When companies and countries embrace new technologies and then use them to drive growth and productivity, they prosper. Advanced AI should be the same. In fact, in our latest quarterly survey of C-suite across 20 countries, they agree: 78% say AI's greatest value is in growth. Now, as we think about what growth should look like, there's two important considerations. First, AI should make the impossible possible. If in a few years as a CEO you cannot point to new products and services, new levels of performance that were not possible before, then you have not captured the potential of AI. Think about the consumer and retail industries. LLMs are about to become the new mall. This is an entirely new way to engage customers and to engage in commerce that did not exist in 2022. If you think about pharma, we see a path toward bringing drugs to market much faster than the average of 9 years, not possible before, which means that life-saving drugs will get to people faster and pharma will have accelerated growth. And we are just beginning to understand how AI will create new drugs, new materials, new products across industries. A second consideration around growth is that we must commit to providing access to the technology and the talent for small and medium-sized enterprises. If we are to use AI as an engine for growth, we need to make sure that these types, these size enterprises have access. 50% of the world's GDP are small and medium-sized enterprises. And in the global south, it's 70% of employment. To do so, there will be lots of business opportunities. So many industries will serve small and medium-sized enterprises. But that will not be enough. Private and public partnerships will be critical to making sure there's access. For example, we're working with the US college system where we're funding internships of college students at small and medium-sized enterprises. It's a win-win. Statistically, if you have an internship, you have a better chance of getting a job. And it's providing these enterprises access to some of the cutting-edge talent. And so we must make sure that we're continuing to focus on the small and medium-sized enterprises. Now, I know and we all know that advanced AI is much more powerful than the technology advancements of the last decade. And of course, that means that the impact is more profound. But that doesn't change the critical lesson that AI must be used for growth and productivity. What it does change are the sets of actions, the time frame, the need for global collaboration, the need for more public and private partnerships, and the urgency of what we must do in order for AI to drive growth. So companies must be willing to reinvent how they operate, their processes, how they've been doing work for the last decades. Underneath the headlines of a failure of AI is mostly a failure to reinvent. Companies have to invest to reshape their workforces and companies must commit to creating sustained entry-level jobs. Now entry-level jobs make economic sense. They're the only way to create future leaders and they bring needed truly AI-native talent to each of our organizations. But AI fundamentally is changing what an entry-level job looks like. And so a commitment means we have to be intentional about changing the roles, investing in training, which is exactly what Accenture is doing. We will hire more entry-level into more entry-level jobs this year than last year. But the skills we require and the way we're onboarding those individuals is fundamentally different. Now countries must also reinvent. They must reinvent their role and how they work with the private sector. They have to themselves as governments become the best credential for why AI matters. They must work with the private sector to help create lifelong learning because education is no longer a destination. We have to have lifelong learning. India is doing a great job of embedding AI into the educational system starting in primary school and governments across the world will need to do so. At the same time as countries are thinking differently, individuals have to think differently and recognize that formal education is no longer the destination. But perhaps the biggest fundamental change that must be made is that companies and countries need to pound the table for global standards. These standards should apply to safety but also to the industries where AI can make the greatest impact. For example, in pharma, if one country is allowing pharma companies to use the latest technologies to discover drugs and then test drugs, but other countries don't follow suit, it means that you won't be able to scale. You won't be able to bring it. And we know that most often that impacts the most vulnerable. Now we have a view of course that we have to reinvent. But as we think about that reinvention, core to our future is the fundamental belief that it is humans in the lead, not humans in the loop, that will shape that future. We should not confuse how you deploy AI responsibly. Of course, all of our compliance programs have humans. They have technology. That doesn't change the critical lesson that we've learned over and over again. Technology, no matter how powerful, is only a tool. It is simply a tool. It is leaders who decide how to use those tools. It is leaders who decide to commit to reinvent, who dedicate their time to making sure that people come along the journey. And it is leaders who must choose to work together to ensure the safe widespread adoption of AI. There are lots of headlines today that predict less. Less jobs, less opportunity, less human relevance. We are here because we see a future of more. At Accenture, we live by eight leadership essentials, the qualities we believe we need to run our company. And one of them is particularly important. We expect leaders to lead with excellence, confidence, and humility. As we look to our collective future, we should have the confidence to have the unwavering belief that together we can make a future that is better for all. We also must hold ourselves individually and collectively accountable for executing on that belief with a high bar of excellence because our people around the world are counting on that excellence. And finally, we must all have the humility to know that we cannot do this alone. Thank you very much.

Thank you so much, Ms. Julie Sweet. I think I can take a tagline out of your address which says that AI should make the impossible possible. But thank you for your thoughtful articulation of AI's impact on industry and on society. Ladies and gentlemen, our next speaker is the youngest billionaire in history and he's now helping to define how one of the world's largest technology platforms deploy AI at unprecedented scale. Next speaker is, ladies and gentlemen, Mr. Alexandr Wang, Chief AI Officer at Meta, the founder of Scale AI. Alexandr Wang built the data infrastructure that powers much of the modern AI industry before joining Meta as Chief AI Officer. So with a round of applause, please welcome Mr. Alexandr Wang.

Thank you so much for having me. Namaste. It's fair to say my upbringing wasn't typical. My parents were physicists in a town called Los Alamos in New Mexico. Los Alamos is a government lab town where for decades scientists have come to push the boundaries of what's possible in mathematics and supercomputing, in human genome studies, vaccine research, space explorations, and material science. My mother studies how plasma behaves inside stars. At the dinner table, we'd talk about physics problems, scientific trade-offs, the reasoning behind how systems work. One kid in my town made huge balls of plasma in their garage for a science fair project. You know, normal high school stuff. Growing up in a place like Los Alamos leaves two things deeply ingrained in you. A belief that anything is possible and that science should serve society. Those ideas are what led me to study AI while I was at college at MIT. They led me to start my own company, Scale AI. And last year, they led me to Meta, where I am now the Chief AI Officer. If you believe that anything is possible, Meta is one of the few companies with the resources, talent, and ambition to push the science of AI forward at scale. If you want to make technology that serves society, Meta has an incredible opportunity to get this technology into people's lives. Three and a half billion people use at least one of our apps every day. That blows my mind. It's more than half a billion people in India alone. People are already using our AI to do amazing things. Across India, creators use our AI to automatically translate Reels into the language of the person watching. Small businesses talk to customers through WhatsApp Business agents that they create in 10 minutes on their phones. And they use our GenAI tools to create ads and reach customers way more efficiently than they ever could before. And India has world-class developers building genius things to solve societal challenges. For example, there are more than 20 million people with disabilities in India who are locked out of education, jobs, and digital services because the digital world wasn't designed for them. So, I-Stem built voice-first AI-powered infrastructure that helps people with disabilities to learn, discover careers, and complete digital tasks independently, like converting textbooks into usable formats or giving personalized career guidance that takes into account their disability. In healthcare, researchers at Ashoka University used our SAM 3 model, which is trained on billions of natural images, to speed up the identification and segmentation of cancer tumors and at-risk organs. Their model, ENOSAG, can help radiologists and radiology oncology teams do in seconds what it takes hours to do manually. The beauty of general-purpose models is the same technology that can segment tumors in the brain can segment leaves to help farmers assess the health of their crops, as AgroPoint has done. We recently open-sourced our omnilingual models which recognize speech across more than 1,600 languages and can rapidly adapt to new languages with just a few audio samples. It's not a fantasy that in a few years we'll have real-time voice-to-voice translation for every spoken language on earth. Now build that into your glasses. Real-time translation in any language just for you. That's transformative. Perhaps most especially in countries like India where so many languages are spoken. In fact, language is an area where we're collaborating with the Indian government through its AIKosh platform. We're providing data sets in 10 major Indian languages so people can build AI models that deeply understand Indian languages and contexts. I'm sure you're used to people from big tech world making lots of grand but vague assertions about what AI will be able to do. But we don't have to be vague. People use our AI right here, right now. They're getting value from it and they're building amazing things with it. And that gives us confidence about what we're building towards. We're releasing new models this year with the first coming in the next couple of months. These will be deeply integrated with our products in a way we're really excited about. We're optimistic about the trajectory we're on. The first models will be good and as the year goes on, I think we're going to be pushing the frontier. Our vision is personal super intelligence. AI that knows you, your goals, your interests, and helps you with whatever you're focused on doing. It serves you, whoever you are, wherever you are. We all lead busy lives. I'm sure you'd want to do more if only you had the time and headspace. That's how I think about personal super intelligence. Say you want to be healthier. Your personal AI could help you see through a personal health plan covering diet, exercise, and sleep, and your daily routine. Or you have a project you'd like to get done, like putting on an event. It can track your progress, reach out to venues, arrange invites, remind you of things you haven't considered, and more. If you love to go fishing or paint, or want to travel more, it can help free you up so you can do more of these things. And it can give you advice when you need it and or help you show up as a better friend or in your community. It won't just do your admin. It'll be an extension of you so you can be you more. I get that some people will worry what companies like Meta really want is to get you hooked and leave you passively staring at screens. But the whole point of personal super intelligence is the opposite. It's about helping you be more active in your life in pursuing your goals and deepening your relationships. I know people are going to be skeptical when I say we're going to do this work responsibly. But you don't have to take us at our word, take us at our incentives. This is a competitive space, which is why we're seeing so much innovation. Given how intimately your personal AI will know you, people aren't going to hire us for the job if we're not doing it responsibly. Our AI needs to work the way we say it does, as well as we'd say it does, and as safely and as securely as you need it to. It needs to help you in your life. And if it doesn't, people simply won't use it. We'll lose customers. We'll lose public trust, and we'll lose out to our competitors. That's why we're transparent about our models. We publish model cards and evaluation benchmarks and data so you can see how they work, their intended use, and how we assess their performance. And as they get more advanced, we're looking at ways to share even more. It's why we invest in the science of model evaluation, growth, improving the existing tests, and building new ones for risks we haven't yet confronted. And it's why over many years, we've developed ways to identify and mitigate potential risks before we release a model through risk assessments, scaled evaluations, red teaming, and fine-tuning. And we can monitor aggregate trends in how people use AI in our apps. So we have a feedback loop that can flag potential risks and help us improve our models. As the models improve, the governance around them has to keep pace. So we're innovating with how they learn and apply principles and how they're tested and evaluated using AI to strengthen checks and balances. Realizing the full promise of AI is as much a matter of getting policy right as it is investment. There are four building blocks for AI. Talent, energy, data, and compute. Governments and industry need to work together to make sure there's access to each so we can realize AI's potential and do it in a way that means you can build for your needs, not ours. That's in part about having bold national AI strategies and policies that encourage innovation, not patchworks of inconsistent regulations that make it harder. But above all, it's about collaboration between public and private sectors to deliver these four building blocks and to design and deploy AI that works for your citizens and your economies. I don't want these amazing technologies to be one-size-fits-all. I want them to serve your needs designed for the challenges and opportunities that are unique to India, to societies across the global south and all over the world. I want them to serve you as an individual. No matter who you are, where you live, what language you speak, or what culture you're a part of. That's only going to be possible if the public and private sector are on the same side. We need to be partners working together in a spirit of openness and collaboration and with a sense of shared ambition. I truly believe we're on the cusp of a moment where really anything is possible. We want to work with you to build AI that serves our societies. I hope you'll work with us. Thank you.

Thank you, Mr. Alexandr Wang. Our heartful gratitude to you for your remarks, for sharing your findings as well. And well, your vision for AI and innovation, it does inspire many of us. Well, ladies and gentlemen, please join me now in welcoming Mr. Roy Jakobs, CEO of Philips. Mr. Jakobs leads one of the world's most storied healthcare technology companies through a pivotal transformation, putting AI diagnostics and patient monitoring at the center of Philips' mission. His work sits at the critical intersection of AI and human health where the stakes could not be higher. Ladies and gentlemen, please welcome CEO of Philips, Mr. Roy Jakobs.

Thank you so much. Good afternoon. It's a true honor to be here among so many brilliant minds and very bold ambitions and building on the visionary path of the prime minister. I want to share how we are walking that path, designing and developing in India and delivering to the world. And since I have your attention, let me share something that I want to leave behind. We believe that artificial intelligence will have its biggest impact in healthcare because healthcare needs it. And maybe some of you are skeptical, but let me try to convince you otherwise. For decades, healthcare has been adopting technology cautiously. And there are different reasons for this. But today, something fundamental has changed in healthcare. Health care systems are under immense pressure. Rising demand, chronic disease, stretched workforces and high expectations of patients and society. The pressure is only accelerating and that will also accelerate the adoption of data and AI-driven innovation. AI is already today helping to provide better access to care. It's embedded in clinical workflows. It's augmenting human expertise. It's improving imaging precision. It's enabling earlier detection. It's extending care beyond walls. And so the task now is how do we build an intelligent care system that is predictive, trusted, more effective and accessible for people everywhere. Because ultimately it's not about AI or technology. It's about the people that are served by technology and AI. Just consider for a moment the pressure care teams are under. If you ask clinicians what they lack most, the answer is almost always time. Time to think, time to explain, time to connect with patients. In many health systems, nurses and physicians spend hours on documentation and administrative tasks, hours not spent on the patient. AI has the full potential to change that equation. The first wave of AI is about removing friction, automating repetitive steps, reducing clicks, supporting documentation, making systems more intuitive. This may not be flashy, but it is transformative and it does generate huge impact. When AI listens to a clinical conversation and drafts structured documentation in the background, that is not replacing a clinician. It's giving time back to the clinician. When AI prioritizes worklists so that the most urgent cases rise to the top, it's not making decisions independently. It's supporting better clinical judgment. This is AI working quietly in the background so clinicians can focus on what matters most. And this is real today. Let me make it even more tangible because AI is already reshaping what's possible across healthcare. Imagine a patient in a regional hospital. She has been waiting for weeks for an MRI scan. The backlog is long. The technologists are stressed. Clinicians are not available to support. Traditionally, an MRI required significant manual setup, precise parameter selection, and highly specialized expertise to conduct a scan. Variability was inevitable and access was limited. Now, imagine something completely different. The patient arrives for her MRI and checks in smoothly. Her clinical information is already available to the system that will conduct the scan. AI helps position her first time right accurately and selects the optimal scan protocol. It's tailored to her autonomy. And as the scan runs, the image quality is continuously monitored and adjusted automatically. This is autonomous MRI scanning. The result, clear, precise images delivered efficiently and consistently. The radiologist receives AI-driven insights and quantitative biomarkers. And Philips is working to make that a reality. It means more patients diagnosed earlier. Earlier detection of chronic and complex conditions. It expands capacity and access to care. It reduces variability. It scales expertise. And over time, it helps reduce the overall cost of care. And at Philips, we have been laying the groundwork for this future through advanced automation, integrated MR workflows and an AI engine that scans faster while enhancing quality. We are also leaders in helium-free MRI systems. That's a hardware breakthrough. And together, that does not only make it more sustainable, but it allows us to install MRI systems outside of the hospital, closer to patients where it was previously not possible to go to. That means even more access, more resilience, and more patients served. But diagnosis is not the only part of the story. Let's enter a hospital room. There is no lack of data. Actually, there's an overload of data. Many devices, alarms going off, dashboards to be read. Now, imagine a hospital room transformed into a smart healing environment. Data from devices flow into a unified platform where AI continuously analyzes vital signs and clinical trends. False alarms are reduced. True risks are elevated early. A subtle deterioration pattern in a patient is detected by AI hours before it becomes visible. The nurse is alerted within context, not with noise, and the physician receives predictive insights. Preventative action can and will be taken. The true patient crisis never fully materializes. That is the power of agentic AI software that can perceive, reason and act within fine guardrails always under human oversight. It reduces burden. It anticipates risks and it turns data into action. That's how we can give time back. With all of this excitement, we must be clear about one thing. Healthcare runs on trust. AI in healthcare needs to be transparent. It must be validated continuously, not approved just once. It must operate within regulatory frameworks. And those evolve as the technology evolves. Clinicians need to understand how systems arrive at their recommendations. Patients need to know how their data is protected. And regulators need confidence that safety and efficacy is rigorously monitored all the time. Innovation and governance must advance together with speed because trust determines adoption and adoption determines the success of valuable application of AI in healthcare. If they move at different speeds, trust erodes. If they move in alignment, adoption accelerates. Now, I'm very happy to be back in India. India represents a remarkable opportunity in this transformation standing at the intersection of scale, digital infrastructure and ambition. The country's digital infrastructure including initiatives under the Ayushman Bharat Digital Health Mission is laying the foundation for interoperable health records and longitudinal patient data. The foundation for a big data play. Unique health IDs and digital registries create the possibility for the continuity of care for population at scale. This matters enormously as we have heard earlier today. AI systems thrive on structured high-quality longitudinal data. When patients can be followed across settings from primary care to hospital to diagnostics and to the home, the power of predictive analytics increases dramatically. But India also brings something else to the table. Real world complexity at scale. Urban and rural settings, public and private systems, high-end tertiary care systems and primary health centers. The diversity of care environments creates an unparalleled test bed for scalable, resilient solutions. Solutions built for India's scale and constraints have the potential to inform global models of care. And at Philips, we see India as a global innovation engine. We are already here for 97 years and through our Philips Innovation Campus in Bengaluru and the healthcare innovation center in Pune, we have made significant investments in R&D, manufacturing, digital platforms, AI engineering and clinical collaboration. Our teams in India contribute to global development as much as to local development and they do that across imaging, monitoring and connected care. The work done here does not stay here alone. It shapes solutions deployed around the world. For example, AI algorithms developed and validated with diverse data sets here improve robustness across geographies. That's done by more than 4,000 engineers that we have in India developing for India and for the world. These software platforms engineered here connect ecosystems in multiple markets. Clinical workflow solutions co-created with Indian partners inform designs that scale globally exactly as the prime minister says we are doing that today. And this is the kind of distributed innovation model that healthcare needs. Not isolated breakthroughs but integrated globally connected ecosystems. If you look ahead in 10 years, success will not be defined by the number of algorithms deployed. It will be defined by the outcomes they generate. Earlier detection of disease, fewer avoidable complications, shorter waiting times, greater access, more time for clinicians, nurses, and technicians. The Philips Future Healthcare Index, one of world's largest recurring health research initiatives, tells a clear story. 76% of Indian healthcare professionals are optimistic that AI can help them improve patient outcomes. 79% of the Indian patients are optimistic that AI can improve their personal healthcare. This shows us that patients in India are ready for this and that Indian healthcare professionals are asking for this and so are policy makers and government. As we heard today, the promise is real. It's for today. Healthcare will move from reactive to predictive, from fragmented to connected, from episodic to continuous. The systems we build today will shape the health of billions tomorrow. So let me return to where I started. AI will have its greatest impact in healthcare for the world. And when we look at this in a decade from now, we will look at the outcomes and impact it has delivered. It will not be remembered for what is optimized on the screen, but for the billions of lives that we could improve with it. That's the responsibility. That's the exciting opportunity. And that's the future that we are committed to building together with all our partners together here in India and across the world. Thank you so much.

Thank you so much Mr. Jakobs for your enlightening words and also for highlighting how AI can be a game-changer in the field of health sciences. Ladies and gentlemen, I would now like to welcome Mr. Martin Schroer who is the Chairman and CEO of Kyndryl. As the leader of the world's largest IT infrastructure services company spun out of IBM, Mr. Martin Schroer manages the technology backbone of thousands of enterprises across the globe. His view of what it takes to actually run AI in production environments offers a necessary corrective to summit stage optimism. Ladies and gentlemen, please join me in welcoming the Chairman and CEO of Kyndryl, Mr. Martin Schroer.

Thank you. Thank you very much. Good afternoon everybody. First I want to thank the honorable prime minister of India Shri Narendra Modi for convening this distinguished group of ministers, policy makers, global leaders, fellow CEOs and of course everybody watching on the live stream. It is an extraordinary opportunity for us to be here with you as we all focus on how to usher in this new era of AI responsibly for people, for industry and for our communities. Today I'm proud to represent the collective knowledge and experience of Kyndryl's engineers, technical practitioners, problem solving consultants, the people who support the mission critical systems that the world depends on every day as the largest IT infrastructure services provider. A question that we continuously come back to at Kyndryl and one that I suspect many of the policy makers and the business leaders and the technologists and the citizens here among us have is how do we actually make AI work in the real world for real world impact, not a demo, not a pilot or an experiment, and not in theory, but in day-to-day operations under real constraints with people working alongside AI agents at national and enterprise scale. All scale means something here in India that's different than anywhere else where failure of these systems is just not an option because when AI moves from labs into the systems that power economies, the hospitals and the banks and the transportation networks and the energy grids and the governments, getting it wrong, and these are the systems we run every day, getting it wrong is not just an inconvenience. It actually impacts lives. And these systems sit at the heart of what this summit represents: the people, the planet, and the progress that we're all working on. Progress in all three depends on the ability to operationalize AI reliably and again at scale. So today, I'll share a bit about what we're learning working with our global customer base and our partners to close the gap between intelligence and reality and where AI either becomes part of how we work and how work actually gets done or never makes it out of the experimentation phase. And what we're seeing is not an innovation problem. The innovation is real, but it's a readiness problem. We've conducted global studies with business and IT leaders countless times. And our research shows that while more than two-thirds of global organizations are already heavily invested in AI, almost half still struggle to see meaningful returns. And in India, in India alone, 75% said their innovation efforts stall after the proof of concept stage. So based on our research and our experience with our customers both in regulated and unregulated industries, the reason, the leading indicator for why projects stall is not because of the technology isn't smart. It's brilliant. It's because we haven't industrialized it yet. AI today is not industrialized. The infrastructure, the data, the operations, and the people simply aren't ready to support AI adoption and deployment at scale. Our customers really want greater clarity and greater support on four critical questions. First, on operational conduct. They want to know how to deploy AI when data is fragmented across clouds, across their core systems of record, and at the edge of the environments in which they operate. When business processes were never designed for AI and when regulations differ by sector and by geography and when trust, security, and resilience are imperative to how it works. Second, and more systemically, they're asking, can this system really run 24/7 without failure? Can it withstand cyber attacks and outages and data drift and regulatory scrutiny? And can the people trust it when it matters most? When can they trust the decisions it's going to make? Those are the systems we run every day. Third, they're asking about agentic AI, whether they're truly ready to use it in mission critical environments. Are they able to meet the regulatory requirements that come with those environments? And are they able to integrate with existing systems? And fourth, they're asking about their workforce, how to prepare people for new ways of working with AI. Nine in 10 leaders expect AI to fundamentally reshape work. Yet fewer than one in three believe their workforce is ready or that they're equipped to help their teams get there. All of this ladders up to trust. Can leaders trust these AI systems and the insights they provide? And that trust is built when AI operates within clear guardrails where actions are accountable and transparent and explainable which is essential for organizations in every industry and especially in government, in banking and other regulated environments. These are the core readiness questions and the core readiness challenges that we see every day and they're at the

Heart of why so many AI initiatives stall. They remind us that innovation must operate reliably, predictably, and securely day after day in the real world. So, I'm thrilled that this year's AI summit is in India because India is one of the world's most important proving grounds for industrializing AI at extraordinary scale. Under the leadership of Prime Minister Modi, India has recognized AI as a strategic national priority, building policy and digital and talent foundations needed to support innovation and again at scale through initiatives like Digital India and the India AI mission and investments in digital public infrastructure. India has positioned itself not just as an adopter of AI but as a global contributor to how AI can be deployed responsibly and inclusively. AI-powered platforms like the Unified Lending Interface are expanding access to credit at scale, reducing loan times from weeks to minutes and while improving transparency and inclusion. India's digital experience offers an important lesson for the world: when technology must operate at a national scale across public services and financial systems, healthcare, transportation, and energy, reliability, governance, and human integration are not features, they are prerequisites. Kindle is very proud to be a partner to many of India's leading companies and government agencies. Our local engineering teams have built scalable platforms for banking, for citizen services, for telecoms, and for airports to handle the millions of users and transactions every day. At Bangalore International Airport, we've applied Agentic AI to shift IT operations from a reactive response to a proactive resilience, supporting self-healing capabilities that improve operational predictability and strengthen trust in the airport's digital backbone. Through our community partnerships in India, we're helping build digital and cyber security skills because safe, responsible AI adoption depends on people being ready, not just technology. And because sophisticated adversaries are already using AI to move at machine speed, tomorrow we're opening a new cyber defense operations center in Bangalore so we can detect and contain threats that already start at the edge of the network before they become disruptions. So we are deeply committed to helping India and our partners around the world implement AI at the scale to drive people, planet, and progress outcomes in every part of the globe. The conversation about agentic must now shift from intelligence to industrialization, from what AI can do to how it's orchestrated and how it's governed and secured and integrated and how it's sustained with agents and humans partnering to drive business impact. This is a transition every major technology invention has gone through. Invention comes first, but impact only comes when societies learn how to industrialize it safely, reliably, and at scale. A critical part of this industrialization is operationalizing the governance of AI. That means moving governance out of policy documents and into live systems, embedding auditability, logging, explainability, and compliance directly into how AI operates. We're seeing how approaches like policy as code can establish clear guardrails for agentic AI to drive trust and compliance, giving regulators, boards, and citizens alike confidence that these systems are controlled, accountable, and safe. So what do we do next? We get ready by focusing on the fundamentals: infrastructure that can scale, security that earns trust, and people with the skills to operate AI responsibly. This readiness perspective is particularly important for policymakers because the impact of AI will not be measured only by productivity gains or economic growth, as important as those are to drive the future. It will also be measured by how institutions help people adapt in the next phase of industrial automation and how work evolves. AI can absolutely change the world. It can change work. It can change skills. It can change mindsets. And it can change operating models. But it will only change the world when it is embedded responsibly and reliably into the systems that society depends on every day. The future of AI will not be decided in the research labs or the boardrooms. It'll be decided by the choices and the investments we make now. By how we close the gap between experimentation and industrialization. The work ahead is hard because this is not just a technology shift. It's a human shift. We have to build trust in AI. We have to reskill our workforces at scale. And we have to ensure these systems are worthy of the societies that depend on them. The responsibility belongs to the companies and the governments alike. And it is a responsibility worth embracing because when AI is industrialized responsibly, it doesn't just optimize, it strengthens the institutions people rely on every day. And that is how AI truly changes the world. Thank you very much.

Thank you Mr. Shiter for your remarks. And ladies and gentlemen, now I would like to welcome Mr. Olivier Blum, global CEO of Schneider Electric. Schneider Electric sits at the intersection of two of the most pressing challenges of the AI era: energy efficiency and digital infrastructure. As data centers consume an ever-growing share of global power, Olivier Blum is leading the company that is helping make that infrastructure sustainable. Please welcome the global CEO of Schneider Electric, Mr. Olivier Blum.

Thank you very much. So, first of all, I'd like to congratulate the prime minister and the entire Indian government and all the associates for this beautiful event. This week has been tremendous and that put together an ecosystem of stakeholders who are really moving technology to the next level. Now, I'd like to tell you a little bit about my own story. I landed in 2007 in India, was appointed at that point of time managing director of Schneider in India to develop Schneider Electric, and I discovered a country where the major issue was really access to power, access to reliable power. Now I am sitting in front of you, I'm standing actually in front of you as a CEO of a global company, Schneider, almost 20 years later, and guess what? What is the biggest problem of the planet? Access to reliable and clean power. So it's not only the issue of India, it's the issue of the worldwide planet, and we are just at the beginning of a new era because we are facing issues with access to power in many geographies. You heard many stories of problems of peak load in different geographies, including the US where you have power cuts, and we have not even started the era of AI. What AI changes to the world? AI means more compute. More compute means more energy, and we just don't underestimate today. We don't know exactly what it's going to take, but that's going to put pressure on the energy system which has nothing to do with what it is today. So we know that energy is already a priority for governments, for nations everywhere in the world. It's even a geopolitical topic. But we are entering a new era where AI could transform the planet. And since this morning you have heard many speakers talking about how AI could impact our life, our businesses everywhere in the world. But the real question is how we take the energy system to the next level and what AI can bring to make energy more efficient. So we do believe for a company like Schneider it changes everything because we are the first time in the history of Schneider after 190 years in the power sector where we are at a point where we can connect the physical and the digital world and it was not possible before. Now let me look back since 2015. What happened in 2015? Something very important happened in the world which was the climate agreement, the Paris agreement, where the world has put a huge focus on energy. And if you remember at that point of time a lot of people spent time on the supply, bringing clean energy everywhere in the world, which was great. But Schneider Electric was a very strong advocate to say, look, working on the supply is very important but we have to spend even more time to work on the demand side, on how we make energy efficient. And guess what? In the past 10 years, companies like us, but not only, we've been really strong advocates that if we build a world which is more electric, if we build a world which is more electric and more digital, we might have a path really not only to decarbonize the planet but to give access to energy everywhere in the world. I think we've made good progress, but it has been complicated because we faced a lot of resistance in the system. We faced resistance with power grid actors. We faced resistance by companies implementing those new technologies. We know large companies don't like necessarily to put all their data on the cloud. They want to do it on-premise and so on and so forth. But let's make it clear: I don't think all the technologies were ready everywhere in the world to make energy systems much more efficient. So I think it has been a good journey in the sense that we've started really to electrify more and more in the world, but I think we have just started to scratch the surface. Now let me come to the topic of AI and the conference and I will come back on energy. I'm sure you are aware that in any kind of report we are talking about more than 200 gigawatts of capacity that needs to be built in data centers in the next coming years by 2030. We say usually that 50% will be AI-driven, and we see the acceleration for a company like Schneider. We see the acceleration since two years, and we started to see the acceleration when we built our partnership with Nvidia, when we started really to understand the next generation of chips that will be used. For those who are not very familiar with what is a data center, we were talking a couple of years ago about a couple of kilowatts per rack in a data center. Then we moved to 10, 20, 30. What we are building right now in India is something which is already around 80 kilowatts per rack, even more. And what we are doing in the US right now with the GPUs which are available from Nvidia is already at 150. We are foreseeing a world with Nvidia where it can go to 500 to 1 megawatt, and that puts tremendous pressure on the energy system that forces every single company to reinvent the energy system. I'm sure some of you have heard about the concept of 800-volt DCs. So which are the new type of electrical architecture you will need to have for the data center of tomorrow that will be able to power the AI industry. But again, I'm coming back: there are two faces of AI. There is one which is there will be many new infrastructure that has to be built, but we have really to invent this next level of infrastructure to make sure that they can support what the AI would need. But the second part of the equation, which is even more exciting for me, is that probably we are entering a new era where for the first time we can make energy more intelligent. But let's be very realistic. There are a certain number of data from IEA which are telling that to support the global economy, the world will need another 10,000 terawatt-hours of electricity to be produced between 2024 and 2035, and another 12,000 on top of that between 2035 and 2050. When we are looking with our research team at Schneider Electric who are building energy scenarios, we believe that those scenarios don't include what AI will bring to the planet. So the scenario in terms of electrification that you need for the planet, it's not about making usage more electrical and supporting the electrification of the planet for cars, for heat pumps, for electrification of processes. What AI brings on top of that is another level of pressure on the energy system. And if you look at this conference, which has been great, where I've learned a lot, where I've spent a lot of time with great people, I've not heard enough about energy and I've not heard enough about the need to make energy much more intelligent if you want to support the next AI journey. Now for a company like Schneider Electric, it's really fascinating. We created the company 190 years ago. We have been a great company in the physical world. 10 years ago, and I mentioned the Paris agreement, this is when we decided to make sure that every single asset that we will connect, that we will sell in the market, will have to be connectable. So we are entering a new era where all energy systems are connectable, and if we are able to apply all the great models, all the great foundational models which have been built by a lot of partners with whom we are working, we can for the first time in our history connect the physical and the digital world, and that's what we call energy intelligence. And by doing so, we believe we can overcome many of the difficulties that we faced in the past 10 years to make energy systems more efficient, that can eventually also solve one of the biggest problems of the planet, which is the climate transition, because again, it's not only about clean energy, it's about more efficient. And we believe we are entering this new era where if we are able to connect systems, to collect data, to apply foundational models that will connect the physical and the digital world, we can save between 10, 20, 30% of energy consumption in every single application in the world. And I'm just going to tell you and finish with one example: think about your home. You are all sitting today in this conference or some of you are connected, and while we are speaking there is a lot of energy consumption in your home. Tonight you will be back to your home. You have an electrical panel somewhere in your home. Very likely your electrical panel is not connected today. Imagine a world tomorrow where every single electrical panel in a home will be connected. Imagine a world where you are able to extract data. Imagine a world where you can apply AI agents and where we can manage energy for you while you are not even in your home. You can save again between 10, 20, 30% of your energy consumption. Actually I can prove it. I'm testing it in my own home. So I'm telling you it works. Maybe you don't know but consumption of energy in homes is the largest consumption of electricity in the world. So the good news: we are entering a new era where we know that the world will be more electrical, and for the first time in our history we can say that the world can become more electrical if we are able really to leverage the power of the new technology. And I will just finish by telling you that why I'm extremely pleased to be here in India, almost 20 years after I started really my journey in this country, is because India has a lot of different factors which are very different than the rest of the world. And what I've learned a lot by spending six years of my personal life in India: India is one of the countries where equipment are under tremendous pressure more than in any other country in the world. Point number two: India is an extremely cost-competitive country where you need to bring the best innovation at the best price. Number three, the level of innovation. I know in India some people say jugaad in India. But the level of creativity that you can have in India to create new systems that will solve the most complex problems of the planet can be done in this country. And when you look at the number of engineers you have in power, automation, digital, you have all the ingredients which are together at a point of time where we need to make AI a big transformation for the planet. For a company like Schneider, I can tell you it's not only words. India is the third largest country of Schneider, I think, in the world. This is the largest one in number of employees, 40,000 employees. You don't know it, but this is the largest R&D center we have in the world with 8,000 employees, largest number of software engineers. So I'm super excited because we are starting a new phase for the planet, a new technology revolution which is called AI, where India can be the place where a lot of innovation starts. I came to India 20 years ago where we were bringing a lot of products from outside. I think we are at a point of time where India can innovate the next technology that will make the world more efficient. So we call that Schneider Electric Energy Intelligence. I've been very excited to be part of the summit. We've met a lot of people from government, from construction companies, from technology companies who have really this strong appetite to make sure that AI will bring progress for all and making sure that India can be at the center of that transformation. And I always say to my team, because now I'm leading Schneider Electric globally, if you can crack the code in India, we'll crack the code everywhere. Thank you very much.

Thank you so much Mr. Blum for highlighting all those facts which concern the power consumption so far as AI is concerned, which is of course a very important factor especially when we talk of sustainability, when we talk of innovations. And I must thank Mr. Blum for highlighting the role of innovation and sustainability so far as the energy sector or energy-secured future is concerned. And all those numbers which you could see on the screen here were actually mesmerizing and this also gives hope because on one end we are talking about how to leverage artificial intelligence in the areas which touch the lives of common people and at the same time it's like hardware and it's the software part. And when it comes to the hardware part, that is where the whole world is now moving forward to have more data centers, to have more advanced servers, to have more GPUs installed. And of course when you talk of power that comes with this hardware to maintain this hardware, to have a higher computing power, you have to have electricity for cooling and for all those aspects. Well, they're all experts who are sitting here who know all these facts so well, but then this is one important aspect which I think is raising a big question also in front of the whole world as to how do we find an answer to it. I could see the statistics, the numbers which were being showcased for India as well. And then of course honorable prime minister has given us a goal of zero emissions by 2070 and the way we are moving ahead so far as the non-fossil fuel is concerned, we are really working hard towards that and the goals that we had set for ourselves, we are trying to achieve those goals well in advance when it comes to the alternative sources of energy. Yes, there are questions which are being raised about all the alternative sources of energy as well. When it comes to the environment and the pollution and things like that, there are a lot of questions being raised. But I'm sure as everybody is hopeful that the science will find answers to such questions. But for the moment we are here at AI Impact Summit and artificial intelligence is helping us find solutions to the common men's problems and that is what India is aiming at to achieve through this AI Impact Summit, that is we are looking at those aspects of AI where we can leverage AI, we can use AI to find common solutions to the problems of people not only in India but across the world and especially global south because we feel that if we find solutions to the problems of India, we are able to provide those solutions to global south as the factors more or less are really common. The problems are common. So well now let me move on to our next speaker. Ladies and gentlemen, I would like to invite Mr. Arthur Mensch, CEO and co-founder of Mistral AI. In just a few years, Arthur Mensch and his co-founders built Mistral AI into Europe's most significant large language model company, proving that world-class frontier AI need not be exclusively an American or Chinese story. His work is a model for what sovereign AI capability can look like. Ladies and gentlemen, please welcome CEO and co-founder of Mistral AI, Mr. Arthur Mensch.

So, honorable Prime Minister Narendra Modi, President Macron, your excellencies, distinguished ministers, ladies and gentlemen, good afternoon everyone. It's an honor for me to stand before you. I'm the co-founder of Mistral, but I'm also someone who believes that AI should be a tool for empowerment and not for dominance. While others may speak about scale or speed, I want to talk about something a bit more fundamental, which is who is in control of AI deployment, who benefits from it, and how can we ensure that it serves the many and not the few. So we believe that the future belongs to the people that are building the AI, that are deploying the AI, and that actually own it. In a world where multiple digits of the GDP are going to be produced by AI in the coming two years, we need to ensure that everyone that runs AI workloads actually has access to the turn on and turn off button and can actually make sure that there is business continuity and that they are not dependent on external providers that can actually turn off that button. The global AI landscape is evolving rapidly. But too often the narrative is shaped by a focus on control, surveillance, and geopolitical leverage. There should be another path. At Mistral we believe in a different future, in a future where openness builds trust and where autonomy is a fundamental right. Countries and regions must own their AI destiny. It's not a privilege but it's a necessity for preserving digital autonomy and for shaping their own futures. So we need to decentralize AI deployment. And the first brick for that is open source. Human advancement has always been built on top of sharing knowledge, on openly collaborating on science, on transparency, and on collective work. Open source is not a radical idea. It is what has actually allowed us to build the cloud infrastructure that today we rely on. It is what has allowed us to build a secure internet. Today in AI we are facing a dichotomy between open source technology where a few companies like Mistral are working on making the world's knowledge compressed into models that can be used as the basis for creating applications and for serving the enterprise, the states, education, healthcare, and another world where these models are actually controlled by a few large private corporations that actually use them as leverage against their users. The second brick that we believe in is empowering directly all the regions through deep collaboration. So open source is the tool, and if you want to make better open source models, we need to collaborate, and that's what we do with multiple states. We collaborate with their local ecosystems, we collaborate with research institutes to make sure that languages make their way onto our models. Mistral models have always focused on making real languages more usable, and it's especially the case for Indian languages which have this 22-language diversity. We like to collaborate with companies and with research labs that are working on acquiring the content that is needed to make the models better, and that is what is making us wake up every day. Beyond that and beyond the open source that should become the foundation of artificial intelligence, if we want to make sure that every company and every state actually owns their destiny in the coming economy which is going to be mostly driven by AI, we need to go beyond the hype and look at what AI can actually do for our daily lives. AI is not about replacing humans. It's about giving them a way to delegate many of their tasks. It's about enhancing what serves them and it's about solving real problems. So at Mistral we work with public services, we work with healthcare, we work on making sure that citizens can access information in an easier way, in a faster way. We work on making sure that unemployed people for instance in France are actually able to find a job faster thanks to AI. AI should be a tool that empowers people, that empowers businesses, and that ensures that governments can improve the quality of their services, can improve the lives of their citizens, and can improve the quality of life of communities. However, it only works if everybody can access it and if everybody understands how to use it. That's why multilingual AI is actually a very strong necessity. That's also why we need to focus on training people and on bringing them the technology at an affordable price. To do so, we work as a model provider and as a software provider. We work with infrastructure providers across the world to deploy and modify our technology so that it is amenable to large communities, so that our small models can actually be deployed to create products that are cheap to serve and therefore are affordable by the masses. We're not waiting for the future. We're trying to build practical and impactful solutions on top of the open source models that we're creating. We're creating the enterprise layer on top which allows to customize systems, to make small models at sales purposes, to automate tasks in enterprises so that people can focus on the things that matter and on the creative aspect that is going to be the most important quality in human life thanks to artificial intelligence. And we focus on making impactful solutions. I would say that we are at risk today in the world to be facing too much concentration of power in artificial intelligence. We don't want to be in a world where three or four enormous companies actually own the deployment and the making of AI, actually own access to information, because really artificial intelligence is the way we are accessing information today, and actually own the infrastructure itself, the entire network that is converting energy into intelligence. We need to make sure that every country, every economic community actually has a strategy to own a part of it, not all of it. We're always going to be partnering, and that is extremely important to accelerate. But ownership and ensuring that nobody gets excessive leverage is going to be critical if you want to ensure that the world we live in remains stable. AI is going to change pretty profoundly the way economy is being run in the next few years. It's going to change the equilibrium in the world, and in order for the equilibrium to remain sustainable and stable, we need to ban excessive leverage. And in that, India is a leader in betting on self-reliance, which is absolutely critical for a country this size. To wrap up, I would say this: that the true potential of artificial intelligence is to level the playing field. This is entirely rewriting the way we build software. It is changing all of the previous established dominations and it's enabling every country to actually accelerate their economies. It's enabling startups to build large and growing businesses that are disrupting the old incumbents that have been increasing their margins way too much. And it's democratizing access to knowledge. It's enabling non-technical people to start building technical tools. The generation of code, which we have been heavy investors on especially, and a leader in releasing open source coding models, is enabling a very large community of people that were not builders before and that are becoming builders, and that is definitely going to change the way people look at their jobs, the way people become entrepreneurs. Becoming an entrepreneur today in every part of the world is made much easier with AI, and we need to accelerate that to ensure that on the other hand the technology we're building is not widening the digital divide. We need to ensure that no language and no culture are left behind. We need to ensure that the technology that we're building is affordable, and therefore our focus on open source is I believe a very important aspect and it's an aspect that requires a community of people that believes in this model, and this model has already proven its benefits in the course of technology in the last 30 years. We believe in partnerships over dependency. So when we work with states, we actually transfer some knowledge on how to build the technology, on how to run it, and we ensure that we can disappear. We ensure that once we have shipped the technology, this is in the hands of our customers, this is in the hands of the partners that we work with. Whether it's collaborating with local governments, whether it's collaborating with businesses or with academic institutions, we're committing to transferring that knowledge. We believe that India's opportunity is extremely large. In that, its talent, a quarter of our researchers are actually Indians. Its diversity of culture and its ambition and the size of its market and the size of its industry is giving it immense leverage when it comes to building artificial intelligence that will be differentiated, that will be a major product of export, and that will provide them with even more leverage on the international scene. By controlling its own AI, India can become a global hub for innovation and it can also lead the way for the entire world. A call to action I would say: we need to seize the moment. This is really an acceleration moment. We've gone from a place where chatbots were actually pretty amusing two years ago to a world where now we can delegate tasks over multiple hours and actually have an army of AI delegates that can do a lot of things on our behalf. And so it's enabling anyone to build much faster. But what that also means is that the people that are not catching that wave are going to be left behind. And so to governments I would say: you need to invest in AI infrastructure that you own, that you make sure to distribute to local and regional providers. You need to prioritize investment on local talent. You need to make all of your engineers and everyone better at using AI. You need to invest on content. We're all about compressing knowledge. This is something that humanity has always been doing. And to compress knowledge and to make sure that your language and your culture is represented, the aggregation of content and the usage of those contents to make open source assets is absolutely critical. And the time is really now. We need to not miss that. To the businesses, I would say adopting AI is going to take some time. But it's going to bring immense leverage and you have unique assets in your companies. You have IP, you have knowledge, you have full core knowledge, the way you're operating your business is different from the way your competitors are operating it. And what that means is that you need to build your own AI systems. The same way you train unique employees, you will need to train unique AI agents. And that will only happen if you take a meaningful part of the value chain and you make it internal. Finally, I would say the future is how to shape the AI revolution is here. The path that it can take is really, there are multiple paths it will take. Will it be a tool of dominance or will it be a force for empowering people? Will it deepen divides or will it bridge them? Will it allow certain countries to leapfrog? We believe it can happen, but we believe it only happens if we work as partners, if we work with a commitment to transparency and openness, and if we choose to look at AI as a next vector of autonomy and a way to ensure that every country remains self-reliant. So we choose a future where AI is built for the many and by the many and for the many, and India and the world deserves nothing less. So I would say let's build it together. Thank you.

Thank you so much Mr. Mensch for your compelling insights and also for highlighting the importance of technological independence in this digital era. Ladies and gentlemen, I would now like to invite Mr. Rajesh Subramaniam, CEO of FedEx. At the helm of one of the world's largest logistics networks, Mr. Rajesh Subramaniam is deploying artificial intelligence to optimize supply chains, predict demand, and make global trade more efficient. His vantage point moving 15 million packages a day offers a uniquely grounded view of how AI performs in the real world. Ladies and gentlemen, let's welcome CEO of FedEx, Mr. Rajesh Subramaniam.

Thank you very much for the kind introduction and for the opportunity to participate in this important discussion. Gatherings like this are critical to advancing technology and making global progress collaboratively, responsibly, and equitably. And that's truly our charge at this pivotal moment. The recent exponential growth of AI has the potential to be one of the most significant events in human society since the advancement of electric power systems and the introduction of the internet. AI is no longer a trend. It's the next industrial system, a union of compute, energy, and labor that'll redefine how economies operate and how humanity evolves. We understand the science and now it's about rapid amplification and application. Building AI capabilities is not optional. It's essential. Intelligence is not an asset. It's infrastructure, the foundation of the future of global progress, productivity, and economic growth. As such, we have an opportunity and a responsibility to be more than consumers. We must be architects of AI. Every company, government, and institution should ask: how can we use AI to expand our ability to solve our most pressing problems, from broadening the economy to eradicating disease to improving energy efficiency? One of the most exciting aspects of AI is the potential to turbocharge problem-solving at scale. And that's always been the guiding principle at FedEx: to solve problems by connecting people and possibilities. Our journey began at another technological inflection point. Half a century ago, our founder Frederick W. Smith realized that we are moving towards a computerized, automated society. He saw the world changing and he seized the opportunity. He created an industry for the computer age, a noble way to move critical goods reliably and at scale. The integrated air and ground network would become a pillar of the modern economy. And flight by flight, route by route, hub by hub, we built a network that connected the world, shaping business, communities, and global commerce. Along with pioneering overnight shipping, we invented tracking, we also fueled a massive growth of high-tech, advanced pharmaceuticals, international trade, and e-commerce. We are indeed the heartbeat of the industrial economy. Now, the world is undergoing a fundamental shift. The patterns and the rules of commerce are changing. Impacts from the pandemic and shifts in trade policy are driving towards a new period of re-globalization. Global supply chains are moving from one equilibrium state to another, and FedEx is right in the middle of this transition. In my 35 years at FedEx and monitoring global trade, I've never seen change at this pace and scale. We also never had a powerful technological force for affecting change. AI is a force multiplier for shaping modern supply chains in a more connected, complex, and opportunity-rich world. We've always been a data-driven company. We have nearly 700 airplanes, 200,000 motorized vehicles, and more than 500,000 team members. We handle $2 trillion in goods annually, move more than 17 million packages daily across 220 countries and territories, and generate two petabytes of data every day. We realized the value of our data, our insights, and supply chain intelligence early, and we set about organizing and engineering our data ahead of the current AI revolution. And when you power the industrial economy and generate over two petabytes of data, the potential to harness that intelligence with AI to create smarter, more resilient supply chains is immense. And it is a capability only a few organizations in this planet can match. And for the past 50 years, FedEx built the world's most reliable network for moving physical goods. Over the next 50 years, our differentiation will come from orchestrating the intelligence that governs modern commerce. That is our future. And to get there, we're using AI to transform real-time network data into actionable insights that enable prediction, orchestration, and optimization across the entire supply chain. This is not just visibility into what happened, but intelligence about what will happen next. Identifying vulnerabilities and addressing them before they become disruptions is probably the most crucial element of supply chain resilience. Over the long term, we will power solutions allowing FedEx and our customers to anticipate disruption, to reroute flows, rebalance capacity, and prevent localized issues from becoming systemic failures. More importantly, we are scaling these capabilities responsibly and grounding them in strong data governance, cybersecurity, and ongoing focus on AI literacy so our teams know how to use these tools effectively. Now, this opportunity is not just operational, it's also commercial. We are extending our intelligence through digital tools that solve problems for customers and enable them to optimize their operations. Through collaborations and platform integrations, we can embed our intelligence directly into customer workflows, helping businesses make sourcing, routing, inventory, and fulfillment decisions with near real-time supply chain insights. We create common data platforms with our customers to build the best supply chain solutions together. This goes far beyond a supplier-vendor relationship. Our customers are often co-creators and many of our digital tools are shaped by the feedback from small and medium businesses seeking to grow internationally. Just one example: our clearance solutions have become increasingly important to our customers with ongoing shifts in trade requirements. FedEx Import Tool was first developed in India to simplify international shipping for small and medium enterprises. Their feedback helped us design features such as predictive logistics, automated shipment tracking, and real-time customs updates, all powered by AI. And this is now rolling out globally. What used to be a complex process became much simpler, giving small businesses better visibility and control over their shipments. Our AI-powered capabilities go far beyond traditional logistics, positioning FedEx as a digital backbone of supply, demand, and decision networks across industries. Today, technology is business and business is technology. As global citizens and leaders, we must think this way. We must use the AI revolution to propel global progress. From our experiences at FedEx, I encourage you all to get in the game. You cannot innovate from the sideline. If you don't like change, you will hate extinction. Seize this opportunity with AI. Our actions must be decisive because the opportunity is genuinely transformative. Ask not why, but why not. Question all ways of thinking. Take risks and embrace change as an opportunity for exploration and growth and keep asking questions. Nothing will matter more in the age of AI. As AI increasingly contains more of the world's knowledge, it becomes an even more powerful tool for anyone with questions. Have a bias to action. The world is becoming more agile by the day and action is critical to keep pace. There's also so much more to discover, including tremendous opportunity in how we apply emerging technologies. We have barely scratched the surface on how we use AI and machine learning to manage global supply chains. For a company with a legacy of delivering what's next, I cannot tell you what the end state of AI will look like. But I can tell you that we will be ready for it. The transformative potential of AI is immense and with that potential comes the responsibility to ensure that its benefits are widely accessible. How this latest generation of AI comes to life and how it impacts every aspect of our civilization is up to us. FedEx is ready for this journey. We're embracing AI and eager to solve problems, drive economic growth and global progress, and deliver a better and a brighter future. Thank you for your attention.

Thank you Mr. Rajesh Subramaniam for your valuable insights and also highlighting the importance of practical application of artificial intelligence in global logistics. Ladies and gentlemen, I now take the pleasure of introducing our next speaker, Mr. Jeet Adani, director of Adani Digital Labs, representing the next generation of one of India's most consequential business families. Mr. Jeet Adani is driving Adani Group's ambitions in digital infrastructure and AI with data centers, green energy, and ports as the foundation. The group is positioning itself as a critical enabler of India's AI economy. Ladies and gentlemen, please welcome director of Adani Digital Labs, Mr. Jeet Adani.

Distinguished global leaders, innovators and friends, good afternoon and namaste. We gather here today at a decisive inflection point in history and it is indeed a privilege to have the opportunity to speak to the audience that is reshaping our world. If you really look at it, throughout history, electricity powered industry, oil reshaped geopolitics, and the internet transformed commerce. And today, AI is going to redefine sovereignty. The central question before our country, India, is not whether we will adopt AI. The questions are: will India import intelligence or architect it? Will we consume productivity or create it? Will we plug into someone else's system or build it ourselves? The time for asking these is now over. As my country India rises, she does not rise to dominate. She rises to stabilize. She rises to anchor a world searching for balance. And she rises to build systems that are inclusive and enduring. And when India builds technology, she does not build for exclusion or control. She builds for inclusion. But in this geopolitically charged century, I believe that inclusion without capability is weakness and capability without sovereignty is foreign dependence. So today I want to speak about three pillars of sovereignty that will define India's AI century: energy sovereignty, compute and cloud sovereignty, and services sovereignty. These are not technical abstractions but they are the foundations of modern nationalism. The first pillar: energy sovereignty.

Thank you, Mr. Gautam Adani, for sharing your insights with us and your vision, as well as for enriching this august gathering. Ladies and gentlemen, it's my privilege to now welcome Mr. Vinod Khosla, founder of Khosla Ventures, co-founder of Sun Microsystems, and one of Silicon Valley's most visionary investors. Mr. Vinod Khosla has been making bold bets on AI, on climate, and healthcare for decades. He has argued that AI will replace 80% of the jobs and that this is cause for optimism rather than despair. How? Let's listen to him. Please welcome the founder of Khosla Ventures, Mr. Vinod Khosla.

Good afternoon. I am going to talk to you about some applications of AI that should be done immediately. I am not going to talk about business or technology or where it's going. I'm going to talk to you about what can be done today. If I can get my slides on the screen. Okay. So I'm going to talk to you about what can be done today in the next year or two to reach a billion and a half people in this country with really impactful immediate benefits. And unless AI benefits the bottom half of the Indian population, we're not going to see a huge amount of impact. So the first thing I'm going to talk to you about that's possible today, and in fact millions of kids in India are using today, is AI-based personal tutors. And I'm going to talk to you about 24/7 almost free doctors available to everybody through AI. This is not helping a doctor. This is building a doctor. And of course, every farmer should have an AI-level PhD agronomist available to them in their local small plot. This is all possible. They don't even need to know how to read and write. Just speak and look and take pictures. So, let me start with AI tutors. There's a lot of children in India who don't get much help in their education. In fact, in rural India, teachers don't often show up. So, it's very important that this kind of a service be available so every child has their destiny in their own hands. Thank you. The screen wasn't showing my slides. My wife has been running a nonprofit, CK12.org, that offers it. Now these are worldwide usage, about 400 million students have already used this service of AI content, which is all free, and AI tutors. In India, 4 million students have benefited by using the AI tutor. More than 12 million have used it constantly. So it is already in widespread use. This is already CBSE compatible, the national education policy compatible. The curriculum is available in English, Hindi, Odia, or Meghalaya in these state standards. Plenty of studies to show that they can be very efficacious. Does a student learn better with AI than without? In fact, I would venture to guess a student learns better with AI than if they had a personal tutor. Rich people can afford personal tutors. They won't do as well as people who have access to this AI. It's a holistic kind of approach. I won't go into much. It's a pretty complex system. And I won't go into the complexity of the system, but this is not just a chatbot. This is not just a key sort of use of AI simply. This has been built based on... and we've been working with Sarvam here in India to propose Diksha, which is a large collection of content in India which is mostly unusable to be honest, and build a 3.0 version of Diksha which is an AI-first experience. This is built on billions of student questions that have already been asked on the CK12 website. Billions. That is used to train the model to know how to teach a student. So it also has a pre-teacher professional development curriculum. So teachers can keep up with it and keep up with most modern education. Again, compatible with the national education standards in India and the CBSE curriculum. Before I go talk about AI doctors, I'm going to make a couple of comments. The AI tutors I'm talking about are far superior to human tutors. Here's what they can do. They can quickly assess a student where they are in minutes, 10 minutes or 15 minutes, and then teach and tutor to the gaps in what the student doesn't know through a complex process called knowledge tracing or keeping their... tracing what they don't know. Moving on to AI doctors, which are also entirely possible today. In fact, these will make available 24/7 to every Indian for almost trivial or no cost. Full primary care expertise, full disease management, chronic disease in India has been going up very, very dramatically. Free mental health therapy, physical therapy, and health and nutrition coaching. A level of comprehensiveness in AI help that isn't available to the people who have the highest, most best-paid doctors in the world. None of this is available at this level even in the US or most Western countries. More than that is possible here for almost no cost. So, and of course these AIs will be smart enough to know when to triage up to a human to do whatever functions only humans can do. But let me not delude you. There's very little a human doctor can do that this AI can't do today, other than the physical parts. If they have to feel your stomach, of course, an AI can't do that yet. I also fundamentally believe these services, AI-based doctors and AI-based personal tutors, should be part of the Aadhaar system. Aadhaar allowed us to offer UPI. There's no reason we can't offer on the same identity-based system, where the hard work has already been done, within a year or two to every Indian these services. So what I'm specifically proposing is to build a Section 8 nonprofit company to build, operate, and transfer into the Aadhaar ecosystem such systems. I think they're relatively simple to do. They need many cycles of iteration to adapt specifically to Indian conditions, all the Indian languages, all the difference in diseases in each part of India. So I'm very, very excited about this and what you can do for not only education, healthcare. The third element I want to talk about is agronomy, having every farmer have a PhD-level agronomist available locally 24/7 alongside a UPI-like service as part of the Aadhaar system. A tutor that can gauge students. It can find and teach to gaps in students and make the current Diksha system much more useful, much more friendly, and leverage all the great content that is in the Diksha system in India today but is not really usable because there's no way to organize it and have an AI tell you what part of this vast library is relevant to you on the day you're trying to do your homework or prepare for a test. You can multiply India's doctor resources. So many years ago, I looked at the question of how you could scale the doctor-patient ratio in India to the same level that is in the West, like in the United States, and it wasn't possible even if you had a trillion dollars in decades to do this. That's how far behind we are. But this will get us in India an opportunity to get well far ahead of the level of care available in a country like the United States, at least at the doctor level. There's still surgeries, there's still drugs, those are separate matters, all areas in which AI can help. But that's sort of my hope. So the AI talks directly to patients. It diagnoses, prescribes tests, prescriptions. We are using technology from a company that's been developed over the last five years and with Sarvam's help and adaptation to Indian languages using the Sarvam model. And you start with physician approval of the dialogue. So you oversee the AI with the doctor initially for the first couple of years. So think of AI as an intern, fresh graduate, an MBBS graduate who works for the doctor. They let them do a lot of things but then they oversee them and watch that. That's the model I propose is possible in the next year or two, and within two or three years I think that need for supervision will go away. And of course there's emergencies and times you have to send somebody to the emergency room or the hospital. So AI can do that. The same is possible with agronomy. This is the third service. I won't go through the details of this. I will try and finish up here. But I want to finish by saying the future is here today. These massive impact services that couldn't be done with hundreds of billions of dollars can be done very, very cheaply. Scale medicine, scale teaching, scale education, scale agronomy. And these services impact the bottom half of the population more, and they need it more than almost anybody else. That's exciting. If we don't do that, it is a massive opportunity loss for us. Thank you.

Thank you, Mr. Khosla. It was a pleasure listening to you and all your wonderful ideas giving AI solutions to India's problems. And no doubt, AI can be a game-changer to make this world a better place, and such ideas I'm sure will help us achieve that goal too. Ladies and gentlemen, I would now like to invite on stage Mr. Nikesh Arora, CEO of Palo Alto Networks. As cyber threats grow more sophisticated with every advance in AI, Mr. Nikesh Arora has built Palo Alto Networks into the world's leading cybersecurity company by platforming defense. A former president of SoftBank and senior Google executive, he brings rare breadth to the challenge of securing our AI future. Please welcome the CEO of Palo Alto Networks, Mr. Nikesh Arora.

Good afternoon everyone, and thank you very much for being here. I want to thank the honorable Prime Minister for bringing us all together. And as many of you were here this morning, not unlike Sundar from Google, about 40 years ago I used to take the Prayagraj Express from New Delhi to Varanasi, a city that was a city of temples and had the revered Banaras Hindu University, which is now a hotbed of AI innovation. You've spent the morning hearing about AI's vast potential, from curing ancient diseases to Dario's idea of having a country full of geniuses in a data center. Having spent my career at the intersection of major technological shifts, I can say I have never seen anything that has moved so fast from a technological perspective. Coincidentally, it was about three years ago I was on my way to BHU to give the convocation address and ChatGPT came out. That moment changed everything. AI is accelerating faster than our institutions, our governance frameworks, and even our intuition. This widening gap, if not handled right, is going to become a tangible threat to national security, economic stability, and social cohesion, making it a defining challenge of our era. As an eternal optimist and representing the world's largest cybersecurity company, I'm not here to throw cold water on our optimism and the idea that AI is going to solve every problem. I'm just here to come and say that for us to enjoy the benefits of AI, we have to make sure we have to solve for inclusion, for trust, and for safety while we continue to make advances on AI. I would say at the current moment, the balance is tilted not in the favor of trust, inclusion, and security. It's actually tilted in the favor of speed. You're seeing features and capabilities coming out as fast as they can, probably faster than we can absorb them. Every morning you wake up and something new happens. You know, there are agents that are doing things for us. There are new models being thrown out which can make music. I only don't know where this is going to stop. So, while we've been enjoying the capabilities of Claude, ChatGPT, Gemini, which are teaching us how to do all kinds of stuff, AI has already moved on. We're now battling towards the agentic future where the agents are going to take care of everything and we're going to kind of lose control. The challenge we have is, you know, we talk about agents. If you think about it, Sundar also mentioned Waymo, a car that will drive you from point A to point B. That car is effectively an agent. That agent used to be a driver who's no longer a human being. It's an agent. It's going to drive you everywhere. That was a very expensive agent. It took a lot of training to train that agent over a lot of time. However, it does give us a glimpse into the future. A future where we can actually build a trustworthy agent that can take over the task of a human being. But I was at Google in 2009 and I remember riding in the first iteration of a self-driving car. That was 16 years ago. So, it's taken a long time to get one job replaced by an agent. So, all of those of you who are really worried that our jobs are going to go away, it's going to take a little longer than you think. We're not going to trust agents that easily and that quickly. However, for us to be able to trust agents, once again, we have to build a future where the ideas of safety, the idea of security, the idea that we can trust an agent are developed cohesively with technology, not outside of that technology. So, and once you get there, you realize we're not going to stop at software agents. I think if you saw the Lunar New Year celebration in China, there were robots which are dancing and flipping around. Much we have challenges we have to solve. I think the first challenge is the challenge of governance and accountability. In the early stages of AI adoption, systems are advisory. You ask it to write a letter to your girlfriend. Ask ChatGPT to write a letter to your parent. A thank you letter. It can do that. That's pretty cool. It's an advisory system. You can change it. You're a man in the middle. You're in control. This is great. Very soon, you will give control to an agent, which is going to be your agent. It's going to do things for you. That's okay, too. As soon as you give control to an agent, which can act with its own agency, now you have to worry about who's responsible for the actions of those agents. If you use them in a social context, who's responsible? If you use them in enterprise company context, who's responsible? If your agent starts giving away money, who's responsible? If an agent goes ahead and balances your portfolio the wrong way, who's responsible? So there is a whole series of questions that are going to kick in from a governance and accountability perspective at an individual level, at a nation-state level, at a global level. These are problems that need to be solved. That is why we have to come to summits like this and talk about this from a public-private partnership perspective because the extreme option is let's ban it. If you ban it, it'll go away. It's not going. AI is not going to go away if you govern it out of existence. It cannot be governed out of existence. So, we have to figure out how to sit down and solve the governance and accountability problem before it's too late. If you don't solve that problem, we will erode trust in AI. If you erode trust in AI, it's going to cause a series of problems that we're not going to be able to solve. So, the second problem that we're going to run into with AI is this problem of human impact. AI is currently threatening to take away jobs. AI is currently threatening to take away agency from human beings. I think it's important for us to understand how that is going to manifest itself. I think many people have talked about that every technology inflection in history has resulted in a significant period of societal and economic disruption. But ultimately every inflection we've had, whether it's agriculture or industrial revolution, electricity, you pick your favorite one that you want, it has resulted in upskilling and reskilling of society. I think the farm agronomy production is up 20x and the number of farmers is down 90%. So we found a way of retraining people, upskilling people without social uprising, and we need to figure out how to understand the human impact of this, how to build plans from an upskilling perspective. I have a conviction that we're going to need five times the number of technology people in the future than we have today. So, we need people to work on these things. Who's going to train the robot who's going to dig the street? Who's going to train the robot that's going to build buildings for us? Who's going to train the robot that's going to go out and build a data center? That requires training. That requires development. That requires people who understand how AI works, how technology works. So, there is a solution to the problem. If you're an optimist, the solution is sit down and plan for it to understand how to make the social change happen simultaneously while Sam, Dario, and Sundar are busy building amazing models for the future. And last but not the least, as you know, since I work in cybersecurity, it is important to understand there is a security problem. A security problem manifests itself in many ways. There's lots of data being used and AI is going to consume more and more data. You know, as I don't know if you experienced the new models, the model says, 'Let me know more about you so I can be most helpful.' My fear is in about six months if I'm talking to my AI model, it might know more things about me than I've told my wife. So, I don't want my wife to get her hand on my Gemini prompt because I'm surprised what it might tell her. But if you expand that and take that more seriously, you will see that AI is going to become your therapist. It's going to become your nutritionist. It's going to become your advisor. It's going to become your friend when you're lonely and you're going to tell it things that you don't tell anybody. That's fine. Do whatever makes you happy. But when you do that, the risk is if that data falls in the wrong hands, it's not a good idea. So you have data concerns. What do you do with data that you're feeding AI? How does it stay segregated? How does it stay that it belongs to you? You have a problem where we're using the base application today for LLMs is coding. Well, that's great. Code can be malicious, code can be tampered with. So you got to make sure as people are busy writing code and rebuilding your systems in your companies, we have to build a secure system around the code to make sure that AI is doing it in a secure manner. You have problems with agents. We talked about agents, you know, great. How are you going to make sure that the robot that you bought to go clean do your dishes and your laundry at home doesn't go rogue and start threatening you? How are you going to make sure that nobody can intercept the control system of the robot and it starts to go rogue on you? Do you need security? Do you need to make sure that this is built in a way that can be secured, governed, and controlled? Including that you also have to worry about adversarial AI. What if AI turns against you? How are you going to make sure that we build security systems? Where is the kill switch if AI starts to act in a way that is not good for us? I'm not trying to scare you. These are all problems that we can solve collectively. But there are problems that we have to tackle whilst we're busy getting excited about AI. So we have to solve the problem of governance and accountability. We have to solve the problem of social and human impact. And we have to solve the problem of cybersecurity or safety as you build these AI models. However, despite the complexity of this challenge, I remain deeply optimistic. I think this optimism is because of the unparalleled strength and progress we've seen in three years. We've actually painted the future which none of us had imagined three years ago. So if you can do that, I'm sure we can collectively solve the problems if you put our hearts and minds to it. And I know there are many such companies that are inclined in such a way. There are many governance bodies that are inclined towards solving this problem because we have something no model can replicate. We have human judgment. We have shared values and we have the ability to collaborate. So I think that's important. That is why we come to places like this to talk about this with each other to collaborate to be able to solve these problems. India has already shown the world what is possible. When innovation is paired with inclusion through digital public infrastructure systems like Aadhaar and UPI, they demonstrate how technology deployed with public good in mind and scaled across a vast population can leapfrog traditional development methodologies. I hope we can apply the same energy in India to solving the problem of AI to make it more inclusive, more fair, more social, more trustworthy. With that, thank you very much for listening.

Thank you, Mr. Nikesh Arora. We deeply appreciate your perspective, and your remarks have actually strengthened our understanding of digital resilience in this rapidly changing world. Ladies and gentlemen, I would now like to invite on stage our next speaker who's a woman of substance who's been placed among the top 50 women leaders by Fortune magazine six times. She's one of India's most influential business leaders. Ms. Roshni Nadar Malhotra, Chairperson at HCL Technologies, who has steered HCL Technologies through a period of remarkable growth while also championing education and the arts through the Shiv Nadar Foundation, which is one of the largest philanthropic foundations based out of India. Her leadership brings both business rigor and social purpose to the technology conversations. Ladies and gentlemen, join me in welcoming Ms. Roshni Nadar Malhotra.

Thank you, respected leaders, distinguished guests, and everyone who has joined us here today. A very good afternoon to you all. By now, every major theme has been covered. The trillion-dollar projections, the model sizes, the disruption curves, the productivity deltas. So let me try and draw your attention more on perspective rather than information. Every decade has a defining sound. In the 1990s, it was the hum of the dial-up modem connecting India to a newly globalizing world. In the 2000s, it was the ringtone of the mobile revolution placing communication in every hand. In the 2010s, it was the silent scroll of the smartphone, reshaping how we live, work, and learn. Today, the defining sound of our era is quieter still. It is the invisible hum of neural networks. Learning, reasoning, creating, reshaping the foundations of society itself. Artificial intelligence is no longer something we switch on and switch off. It is with us at all times, even when we sleep. It is an assistant, a guide, a teacher, sometimes even a companion. From the most mundane tasks to the most advanced scientific discovery, AI is becoming all-encompassing. But this is not merely another technology cycle. This is a structural shift. For the first time in history, knowledge itself is being commoditized. When knowledge becomes programmable, industries are redefined rather than merely evolving. Business models change. Individuals are empowered more than ever. Nations have an opportunity to accelerate growth and move up the order. Our generation is fortunate. We are witnessing multiple technology revolutions within a single lifetime. Yet what truly distinguishes this moment is not just scale but speed. When knowledge and intelligence become abundant, judgment becomes scarce. When answers are instant, questions become valuable. The competitive edge in the AI era is not computing power. It is clarity of thinking. We began this AI journey with awe. Can machines write? Can they see? Can they reason? Can they create? Today those questions are getting answered at an accelerated speed. So instead of telling you what AI will do, let me suggest something more uncomfortable. AI is a mirror. It will reveal who we already are. The real question is not what AI can do but how responsibly we will deploy it. How inclusively we will scale it and how wisely we will govern it. Technology is a game-changer but only as long as humanity remains its master. This summit therefore is not just about AI alone but also about leadership. Every technological revolution eventually asks a human question. The printing press asked what should be preserved. The internet asked what should be connected. AI asks what should be delegated. And that question forces another. What is uniquely human? If AI writes, calculates, diagnoses, predicts, then leadership must mean more than knowing things. It must mean deciding things. For decades, India's technology growth followed a simple question. Scale drove revenue. As delivery expanded, so did output, influence, and global credibility. That model powered corporate success and became central to India's export story. AI is reshaping that equation, shifting us from scale-led growth to intelligence-led growth. The future will not be built by doing more of the same, but by reimagining how value is created. AI carries a powerful duality. It is both deflationary and expansive. It reduces cost, time, and effort through automation while simultaneously unlocking new markets, industries, and possibilities. As knowledge becomes commoditized, differentiation shifts. The real question is not whether disruption will come but whether we will lead it, and I believe HCL Tech will lead it. We are evolving from a people-centric delivery model to an integrated system of software products, intelligent agents, and human expertise delivering outcomes at scale. This is more than just a business shift. It reflects a broader national ambition to build intellectual property that creates enduring, compounding value. India must move from being a tech services-led nation to an IP-led nation. Services scale with effort. IP scales infinitely. In the AI economy, value accrues to those who build and own platforms, models, and products, not just those who deploy them. That shift is not only economic, it is transformative. And this is not new for HCL. 50 years ago in 1976, Shiv Nadar founded HCL as one of India's earliest bootstrapped technology startups. By 1978, India's first indigenous computer had been built and found a place in many homes all over India. HCL was driven by a belief in building, not adopting. That belief, that DNA, those guts, that grit continues to guide HCL Tech even today. We are moving beyond traditional delivery to a unified model where software intelligence systems and human expertise operate as one, driving measurable, scalable outcomes. Alongside this shift, we are building entirely new AI service lines. AI factory designs and manages next-generation AI infrastructure. Physical AI brings intelligence into the real world where systems sense, understand, and act autonomously, robots with embedded decision-making, warehouses that optimize themselves, and infrastructure that anticipates failure before it even occurs. This reinvention will multiply opportunities, create new industries, new professions, and avenues of employment for India's vast talent while expanding economic prosperity for the nation. How do we make this transition? If AI will define not just companies but countries, then this is a strategic shift and it requires three decisive moves. First, from scale-led growth to IP-led value creation. IP compounds. It strengthens competitiveness, anchors strategic autonomy, and ensures long-term economic resilience. Second, from adopting to building. Deployment matters, ownership transforms. Nations that build models, platforms, and software will define the era. India has the talent, the scale, and the complexity to be the ultimate test bed. Third, from fragmented effort to national AI infrastructure. Compute must be treated as digital public infrastructure. Democratized compute can unlock innovation across startups, universities, enterprises, and institutions. When compute is accessible, innovation decentralizes. When innovation decentralizes, IP multiplies. That is how an IP nation is built. Not by one champion but by an ecosystem. But ambition without purpose is incomplete. The true test of AI is not how fast it scales but whom it serves. Responsible AI is not a feature. It is a foundation. From awe to accountability, that is the journey. Speed is meaningless without control. Scale is unsustainable without trust. Now at HCL, we have 226,000 HCL techies with an average age of 26 or 27, similar to the average age of our nation. So I talked to them. You've been following the T20 World Cup. You'll know that India won by 61 runs on Saturday in Colombo. What a match. And if you watched Ishan Kishan's innings, 77 off 40 balls, you saw something that is a perfect analogy for AI. In T20 cricket, when a power hitter walks in and starts clearing the boundary from ball one, the captain doesn't take her fielders off the field. She resets the field. Deeper on long-on, a sweeper on the leg side, third man back. Every ball the field has to adapt. Not because the fielders are less important, but because the nature of the game has changed. The batsman is hitting harder and faster than ever before. And the only way to compete is with smarter positioning, sharper reflexes, and better anticipation. AI is the power hitter. It is clearing boundaries that used to require entire teams. But the game is not batsman versus nobody. AI is a team sport. Our job is to set the field, to position our nation where the ball is going, not where it was. To invest in the skills that AI cannot replicate. The ability to read the game, to anticipate, to make the judgment call in the moment that no algorithm would risk. India is repositioning. HCL Tech is repositioning. And the repositioning will be deliberate and it will be supported. Let us commit to building AI that serves people, protects the planet, and accelerates progress. I started with the sound of the decade. The hum of AI will define this decade. But what the world will remember for centuries is the leadership who shaped it responsibly, wisely, and with clarity. Thank you.

Thank you, Ms. Roshni Nadar Malhotra, for your inspiring reflections and also for highlighting the transformative role of artificial intelligence as well as the disruptive role of artificial intelligence, drawing our attention to it in shaping our future. Ladies and gentlemen, I would now like to introduce the speakers for a ministerial conversation. The speakers in this fireside conversation are Her Excellency Cina Lawson, Minister of Digital Transformation, Togo. His Excellency Nezar Patria, Vice Minister of Communications, Indonesia. His Excellency Rafat Hindi, Minister of Communications, Egypt. Minister Lawson has made Togo one of Africa's most-watched digital transformation stories, building mobile-first government services that reach citizens who were previously entirely excluded from the formal economy. Her work is a reminder that AI's greatest opportunities may lie in the Global South. Minister Patria representing the world's fourth most populous nation and one of Southeast Asia's fastest-growing digital economies. His Excellency is navigating the complex challenge of building AI policy for a country of 270 million people spread across 17,000 islands. Egypt is positioning itself as an AI hub for the Arab world and Africa, and Minister Hindi is leading that change. With a young population and growing digital infrastructure, Egypt's ambitions are both compelling and instructive for developing nations navigating the AI transition. Ladies and gentlemen, I would like to invite our speakers. Please, with a big round of applause, I would like to request you to please welcome the minister from Togo, from Indonesia, and also from Egypt. I request our honorable dignitaries to kindly take your place on this stage, and this conversation is being moderated by Ms. Deepti Gauri, Distinguished Fellow, NITI Aayog. I request Ms. Deepti Gauri to kindly join us.

AI summit is a place where everybody looks forward to such ministerial conversations, and this is one such conversation that everybody is looking forward to because when we say that this is the first-ever AI summit which is being organized in a country of the Global South, it makes a difference. And here we have a very elite panel with us. Her Excellency Cina Lawson, Minister of Digital Transformation, Togo, is going to join us. His Excellency Nezar Patria, Vice Minister of Communications, Indonesia. His Excellency Rafat Hindi, Minister of Communications, Egypt. We are expecting our other guests to join us very soon as Ms. Deepti Gauri, Distinguished Fellow, NITI Aayog, is going to moderate this conversation. And this will also give us an insight into the countries of the Global South, how they are adopting artificial intelligence, what are the challenges before them, and how the world has to come together. This global cooperation is needed so that nobody is left out of the touch of artificial intelligence, the benefits of artificial intelligence. And that's when the honorable Prime Minister says it's AI for all. This is what we mean, that it should reach each and every person of the continent of the world, and AI should bring a change into the people of the Global South too. Only then we can say that we are moving ahead in the right direction. So keeping that in mind, ladies and gentlemen, this ministerial conversation is going to be of utmost importance when we talk of AI Impact Summit because this conversation will also bring to the fore those points on the basis of which we can say that AI is making an impact into the lives of people, especially the people of the Global South. And when we talk of the challenges, the difficulties which face Indians, our countrymen, that is the time when we can say that if you are able to find low-cost AI solutions to our problems, they will also be the solutions which can be adopted very, very easily by the other countries of the Global South. So here we are bringing to you this ministerial conversation. Our guests are here, and this elite panel from these countries, from Togo, Egypt, and Indonesia, will bring before us those aspects on which they've already been working, the challenges which they think they need cooperation from other countries as well, if they want to counter these challenges. Because when you talk of Global South, ladies and gentlemen, unless Global South develops, unless Global South adopts artificial intelligence, it cannot bring a change in the world. And that is what this summit aims at, that we must impact the lives of common men. Nobody should be left behind. And when we say this, we say 'Sarvajan Hitay, Sarvajan Sukhay', which means it's AI for all. Everybody should be benefited. So ladies and gentlemen, please welcome our elite panelists. Here we have Her Excellency Cina Lawson, Minister of Digital Transformation, Togo. Please welcome her. His Excellency Nezar Patria, Vice Minister of Communications, Indonesia, and His Excellency Rafat Hindi, Minister of Communications, Egypt. It's over to you, Ms. Deepti Gauri.

Thank you. Thank you very much and good afternoon everyone, and thank you to all of those who are here. So we are all finally here, and as you can see, this is truly a very power-packed panel. So since this is about the AI Impact Summit, and since we are gathered from all over the world to talk about the creation of impact by AI, I want to first start with you, Mr. Patria. You know, when you think about the journey that we've had till now, the global community has had till now with AI, a lot of the focus has been on building the infrastructure. So how do you think we have really done on putting that infrastructure to work to create impact? If you had to rate it on a scale of 1 to 10, what would you give the world? What score would you give the world?

Thank you, Deepti. This is really a challenging question, actually. If I had to give a number, I would give six.

Six.

Out of 10.