Inclusive AI Starts with People Not Just Algorithms

20 Feb 2026 14:00h - 15:00h

Inclusive AI Starts with People Not Just Algorithms

Session at a glance

Summary

This discussion at the India AI Summit focused on scaling human potential through artificial intelligence, featuring leaders from AI Kiran, a community organization promoting women’s participation in AI. The panel included executives from major technology companies like AMD and Automation Anywhere, alongside entrepreneurs and educators working to democratize AI access across India.


Kirthiga Reddy and Lakshmi Pratury, co-founders of AI Kiran, explained how their organization grew from addressing the lack of visible women in AI to building a 10,000-member community. They emphasized the importance of getting inclusion right from the beginning of the AI revolution, rather than trying to fix disparities later as happened with previous technological shifts.


Radha Basu from iMerit shared her journey from establishing HP’s operations in India to running an AI company with over 10,000 employees, 53% of whom are women. She highlighted how AI centers in smaller Indian cities like Kolkata, Vizag, and Coimbatore are becoming specialized excellence hubs for different AI applications, from healthcare to automotive solutions.


The panelists discussed the transformative potential of AI, with Mihir Shukla noting that the next five years will bring changes typically seen over a century. They emphasized that success lies not just in developing AI models but in applying them effectively across industries, particularly in areas like precision agriculture and healthcare.


A significant portion of the discussion addressed preparing the next generation for an AI-driven world. Panelists stressed teaching children resilience, curiosity, critical thinking, and emotional intelligence rather than just technical skills. They noted that AI’s conversational interface makes it more accessible than previous technologies, potentially including populations previously excluded from the digital economy. The conversation concluded with announcements of partnerships to train millions of women and youth in AI skills, demonstrating a commitment to inclusive technological advancement.


Keypoints

Major Discussion Points:

Scaling Human Potential Through AI: The central theme focused on how AI can be leveraged to unlock human potential at scale, with emphasis on inclusive growth that doesn’t leave people behind. Speakers discussed moving beyond just technological advancement to ensuring AI benefits diverse populations globally.


Women’s Representation and Inclusion in AI: Significant discussion around AI Kiran’s mission to increase women’s participation in AI, highlighting how they grew from ChatGPT being able to name only 10 women in AI in India to building a community of 10,000 women. The conversation emphasized the importance of getting inclusion right from the beginning of the AI revolution.


Applied AI vs. Model Development: Multiple speakers advocated for focusing on practical AI applications rather than just chasing the “model race.” Examples included precision agriculture, healthcare AI, and automotive applications, with emphasis on India’s strength in applying technology across various industries and creating societal impact.


Education and Skills for the AI Era: Extensive discussion on preparing the next generation, covering what parents should teach children, how to disrupt traditional education systems, and the importance of developing emotional intelligence, resilience, and critical thinking skills alongside technical capabilities.


Democratizing AI Access and Training: Speakers shared examples of successfully training people from diverse backgrounds in AI skills, including rural populations and those without traditional tech backgrounds, demonstrating that AI can be more accessible than previous technologies and can skip traditional digital literacy requirements.


Overall Purpose:

The discussion aimed to explore how AI can be harnessed to scale human potential inclusively, with particular focus on ensuring women, youth, and underrepresented communities are active participants in the AI revolution rather than being left behind. The conversation sought to provide practical insights on education, workforce development, and building an equitable AI ecosystem.


Overall Tone:

The tone was consistently optimistic and empowering throughout the discussion. Speakers maintained an enthusiastic, forward-looking perspective while acknowledging challenges. The conversation was collaborative and solution-oriented, with panelists building on each other’s ideas. There was a strong sense of urgency about acting now to shape AI’s development inclusively, but this was coupled with confidence about the possibilities ahead. The tone remained inspirational and action-focused from beginning to end, with speakers sharing concrete examples and encouraging audience participation.


Speakers

Speakers from the provided list:


Lakshmi Pratury: Former Intel employee, venture capitalist, philanthropist, brought TED to India, co-founder of AI Kiran, focuses on scaling human potential and showcasing talent globally


Kirthiga Reddy: Former first woman partner at SoftBank, invested over a billion dollars, now on entrepreneurial journey at Optimize.io, co-founder of AI Kiran


Radha Basu: Former HP executive who brought HP to India in 1987, founder of iSupport (early unicorn), currently runs iMerit (AI company with 10,000+ employees, 53% women), pioneer in AI for 10 years


Mihir Shukla: CEO and Chairman of Automation Anywhere, author of upcoming book “A Five Year Century”, company runs nearly half a billion AI-powered digital workers


Speaker 1: AMD representative, focuses on infrastructure and technology development for AI


Anurag Hoon: Runs Manzil Mystics, works with 60,000+ children across 900 schools teaching music, uses mobile music school van, teaches intellectual property and human rights through music, Inc. Fellow


Audience: Multiple audience members who asked questions during the panel


Additional speakers:


Anupama: AI Kiran member, data scientist turned technical lead, works with banking and financial institutions on AI and automation solutions


Hemendra: Professor teaching AI and sustainability at IIM Udaipur


Anjali: Representative from Tech Mahindra, works on connecting creative and technology aspects


Bina: AI Kiran member, part of ServiceNow, involved in women for ethical AI movement


Full session report

This comprehensive panel discussion brought together technology leaders, entrepreneurs, and educators to explore how artificial intelligence can be leveraged to scale human potential inclusively. The panel, moderated by AI Kiran co-founders Kirthiga Reddy and Lakshmi Pratury, featured diverse perspectives from major technology companies, AI service providers, and grassroots organisations working to democratise AI access.


The Philosophy of Scaling Human Potential

The conversation opened with Kirthiga Reddy’s foundational philosophy: “What would you do if you weren’t afraid?” This question, which appears in Meta offices, encapsulated the panel’s central theme of embracing transformative risk-taking over incremental progress. Reddy argued that if a new trajectory can propel you further ahead, it’s better to start completely over rather than continue on a predictable but limited path—a philosophy particularly relevant to AI adoption.


Lakshmi Pratury complemented this perspective by drawing parallels to the early internet era of 1993-94, when people questioned how anyone could make money online. She emphasised that the current AI revolution represents a continuation of technological transformation spanning decades, not an entirely new phenomenon. However, what makes this moment unique is the opportunity to build inclusively from the beginning, rather than creating problems that require fixing later—as happened with environmental damage during the industrial revolution or mental health issues arising from social media.


Building Inclusive AI Communities Through Data and Representation

The AI Kiran initiative exemplifies this proactive approach to inclusion through a powerful demonstration of how human agency can influence AI training data. When the organisation launched, asking ChatGPT to identify 100 women in AI in India would yield only 10 names. AI Kiran began with 250 named women, immediately transforming this representation gap. The community has since grown to 10,000 women who are self-organising and driving innovation across diverse sectors.


As Reddy noted, they’ve now “added two zeros to the first number that ChatGPT had,” with aspirations to reach one million members. This growth demonstrates how intentional community building can directly influence AI systems’ knowledge base and outputs, creating a virtuous cycle of increased visibility and participation.


Applied AI Strategy: Learning from Historical Patterns

A significant theme throughout the discussion was the strategic focus on applied AI rather than competing in foundational model development. Mihir Shukla, drawing from his experience with Automation Anywhere’s digital workers deployed across 90 countries, argued that India’s strength lies in applying AI technology comprehensively across the economy.


He illustrated this with historical examples: “The printing press was invented in Germany, but the Dutch used it to become a superpower. The industrial revolution started in France, but England applied it to everything and became Great Britain.” This pattern suggests that technological invention and successful implementation are distinct capabilities, with comprehensive application often proving more economically transformative.


Radha Basu, whose company iMerit has been working in AI for a decade with over 10,000 employees globally, provided a nuanced framework describing AI scaling as requiring three interconnected components: AI technologies and models, infrastructure, and human intelligence. Success occurs at the nexus of these three elements, emphasising that applied AI cannot be completely divorced from technological development and infrastructure investment.


Democratising Access Through Innovative Training

One of the most compelling aspects of the discussion was evidence that AI can democratise access to high-skilled work in unprecedented ways. Shukla shared concrete examples of rapid skill development: training 700 women in Africa for six weeks, with 500 finding employment within a week, and a Mississippi Delta worker transitioning from a $12 per hour job to a $120,000 AI position after six weeks of training.


Radha Basu offered an even more counterintuitive insight: it’s easier to train young people from rural backgrounds in AI than to retrain industry professionals who must first unlearn existing approaches. Her company demonstrates this principle at scale, with 72% of employees coming from low-income backgrounds and rural areas, while achieving 53% women representation.


Basu’s personal story reinforced this theme. Growing up in a low-income family, she was mentored by David Packard of HP, who taught her that “if you’re not making mistakes, you’re not trying hard enough.” This philosophy of embracing failure as learning shaped her approach to building inclusive AI workforces.


This democratisation extends to India’s smaller cities, where iMerit has established AI centres of excellence in Calcutta, Vizag, Coimbatore, Hubli, and Shillong, preventing the concentration of AI expertise solely in major metropolitan areas.


Preparing the Next Generation for Continuous Change

The panellists agreed that preparing children for an AI-driven world requires focusing on fundamental human capabilities rather than specific technical skills. Ashna from AMD emphasised resilience as critical: “Children need to learn resilience, how to fail, and that life can be unfair while still learning to survive and thrive.”


Anurag Hoon, who operates a mobile music school reaching over 60,000 children across 900 schools, shared his personal transformation from growing up in a low-income family to finding opportunity through music. His approach grounds children in fundamental human experiences through creativity and the traditional Indian concept of nine emotions (Navras), while also teaching practical skills like intellectual property understanding.


The generational perspective proved illuminating. Radha Basu shared insights from her nephew, an 11th-grade student who observed that “AI is beyond all the parents” and that career plans change so rapidly that last year’s dreams may not lead to viable employment. This highlighted the importance of curiosity and adaptability over fixed knowledge.


Mihir Shukla envisioned a future requiring interdisciplinary combinations rather than single-subject specialisation—someone studying both rock climbing and video game design to create authentic experiences, or combining neuroscience with medicine for breakthrough innovations. His daughter’s observation that in the future “there are no worker bees, only queen bees” captured this shift towards universal empowerment.


Addressing Practical Challenges

Despite the optimistic tone, the discussion acknowledged significant implementation challenges. Audience questions revealed persistent gaps between AI potential and practical reality. One grassroots trainer noted that many people still require basic digital literacy before engaging with AI tools, challenging assertions about skipping traditional digital skills.


Questions about trust in AI-generated information revealed concerns about the shift from human-curated to AI-generated content. The overwhelming number of AI platforms creates decision paralysis for individuals trying to develop relevant skills, highlighting the need for clearer guidance on learning pathways.


Educational disruption emerged as both opportunity and challenge. While speakers agreed that traditional models may be inadequate for an AI-driven future, they offered different approaches to reform—some advocating for fundamental system disruption, others emphasising strengthened arts and creativity education.


Economic Transformation and Infrastructure

The discussion revealed AI’s potential to reshape economic participation fundamentally. The technology’s conversational interface makes it accessible to populations previously excluded from digital economic opportunities, potentially enabling massive workforce inclusion without traditional educational prerequisites.


Ashna from AMD emphasised that infrastructure development should support human ambition rather than constrain it, with technology companies building capabilities that enable innovation. While acknowledging resource constraints around compute access and advanced chips, she advocated for creative approaches to utilisation rather than accepting limitations as barriers to progress.


The focus on applied AI across diverse industrial sectors suggests potential for broad-based economic growth rather than benefits concentrated in technology companies. The establishment of regional AI centres of excellence provides a model for distributed development that could distribute economic benefits more widely than previous technological waves.


Moving from Discussion to Implementation

The conversation concluded with a clear call to action emphasising immediate engagement over perfect preparation. The panellists consistently advocated for starting AI learning and application immediately with available tools rather than waiting for ideal conditions.


This approach reflects confidence that human agency can shape AI development outcomes, as demonstrated by AI Kiran’s success in transforming women’s representation in AI from 10 to 10,000 members. The organisation’s growth trajectory and concrete training commitments indicate movement from discussion to implementation at the scale needed for inclusive AI adoption.


Ultimately, the panel presented AI as a tool for amplifying human potential rather than replacing human capabilities. Success requires intentional focus on inclusion, practical application over theoretical development, and preparation of individuals for a future requiring adaptability, creativity, and emotional intelligence alongside technical skills. The diverse perspectives and concrete examples provided a roadmap for achieving these goals while acknowledging the significant challenges that remain in bridging the gap between AI’s promise and practical implementation for all communities.


Session transcript

Lakshmi Pratury

to being the first woman partner at SoftBank, you know, investing over a billion dollars, to now an entrepreneurial journey at Optimize .io. Today we are talking about scaling human potential, etc. So how have you scaled your own potential through all this that landed you in AI Kiran? Why did you land in AI Kiran now?

Kirthiga Reddy

All right, yeah, we’ll all get seated since we have all our fellow panelists seated here. So I’m just so excited to be here. And a first call -out to all of the AI Kiran community members here because that is really the story. Amazing. And you come from where? Where are you coming from? Mumbai? Gurgaon? Jamshedpur? Himachal Pradesh. All right. Just a microcosm of the community that’s now officially 10 ,000 but growing to, very quickly, like, multiplying by two or three -fold, and we’ll be, you know, stay tuned for the announcement with partnerships like the one that we have here. So, yeah, my own journey has been one of I guess if I had to think about a theme, it’s my favorite meta poster, which is an offices all across the globe, which says, what would you do if you weren’t afraid?

And it’s a phrase that I want us to think about. You know, what would you do if you weren’t afraid? And think about what comes to your mind. Right. So it’s about, you know, taking risks and not being afraid to start over again. I had someone come up to me yesterday and say, hey, if their business is on a certain trajectory, but now if they have to move over to AI, if it meant starting over all over again, what would I recommend to them? And I said, start over all over again. Right. Because there’s a certain trajectory that if you are in, it is all about projecting where you will be five years from now, 10 years from now.

And if the new trajectory gets you further ahead, you know, by the way, and even if you fail at that, it’s better to shoot for the stars. And miss versus doing a part that. That feels achievable, but there’s not the stretch in it. And of course, with that comes a lot of assumptions about both, you know, the financial ability, the support that you have from your family to do it. But if you have all of that, certainly go out and stretch to that. So that I would say is what what has been my journey and the inspiration for AI Kiran as well, in that all of the different roles that you mentioned, I was often the only woman in the room, certainly the single digit percentage at the max.

And I think all of the women in this room relate. And it has been about incredible male allies who also helped with us getting to the roles that we are in. And so that becomes a position of privilege and responsibility to give it forward. And then that’s when I met Lakshmi, the fearless Lakshmi, who has been a pioneer both in her own reinvention. She was the OG technology 25 technologist. Connected. builder of, real builder, and someone who’s focused on scaling human potential, just like everyone else here. So Lakshmi, tell us your story, and I can’t wait to hear the stories

Lakshmi Pratury

of everyone else here on this panel. Yeah, so, you know, for me, when I sit here today in 2026, in 1994, 93, 94, we were talking about internet is going to be big, and people would say, okay, what is this? You know, how will anybody make any money in this, etc. So what we are looking at now is nothing new. This is just a reinvention of things we’ve been seeing for the last 50 years, you know. So I’ve been at Intel, I’ve been a venture capitalist, I’ve been, you know, in philanthropy, all kinds of things. But what brought us together to AI Kiran is that for the last 15 years, my work has been about finding amazing people, doing amazing work and get them to tell their stories, because we only hear about the 10 famous people, but innovation is happening everywhere.

So how do you find them, connect them, and get them to tell their stories and teach people how to tell their stories? So I brought TED to India. I mean, I worked at Intel, venture capital, all kinds of stuff. And then I decided for the last 15 years, my journey is going to be how to create a platform to showcase the amazing talent that’s there in India and across the globe that doesn’t get told. So that’s what I’ve been doing. So when I met Kritika and I look at in the AI revolution, there is an amazing opportunity for us to do it right from the beginning. In every revolution, industrial revolution, we messed up the environment, the rivers and everything.

200 years later, we are like, okay, let’s clean it up. Even in the Internet revolution, you know, we have the problems with social media, you know, mental illnesses, all kinds of things, good and bad. But technology is growing. It’s great, actually. You can’t fight it. So how can we be part of this? to make it inclusive from the word get -go. That’s what excites us in this journey. And as she was saying, we have no idea how to do this. You kind of say, we are going to do this. And it’s amazing, like in six months, the kind of progress we had. As she said, you know, one of the things

Kirthiga Reddy

you must say, Kritika, about the chat GPT thing. Yeah, you know, I shared this when we started AI Kiran. And by the way, this is the most you’re going to hear from both of us because the rest of the session, we are going to hear from our incredible panelists. And when we started, if you went to chat GPT and said, can you tell me about 100 women in AI in India, it would tell you 10 women, right? And it will tell you that I cannot answer this question. And these are some sources that you look at. And so over that period of time, so we launched with 250 named women. So right there, we added a zero.

Now it’s an incredible community of, you know, 10 ,000 women who are all taking this on their own, rallying it, self -organizing. And so we’re going to talk a little bit about that. creating new ventures. We just heard about Dark .ai, which Komal is doing that and helping tailors and fashion designers use AI. And you have to Awesome, right? So if we can create a platform to even add a little bit of like that oomph and make it bigger, faster, bolder, I mean, we have done our jobs. And so, yeah, so we have already added two zeros to the first number that ChatGPT had. It’s just about, you know, as they say in a startup, add a zero, add a zero, and we’ll be at that million.

So with that, let’s jump in.

Lakshmi Pratury

So talking about scaling human potential, I have to start the conversation with Radha. I’ve known Radha… I mean, I knew Radha about reading about her first in Silicon Valley. She was one of the first people… people who brought… HP to India in 1987 before anybody thought of the technology corridor. So we used to read about her. And then she started iSupport, which is a software company, which is one of the first unicorns in Bay Area. I was still reading about her. And then through a common friend, Chitra, I met her and been a great friend for the last 25 years. And talking about somebody who reinvents herself all the time to benefit the community that’s been in her, whether it is HP or whether it’s iSupport.

And now she does something called iMerit. And Radha, before, instead of me saying what you do, the kind of work that you do in scaling humanity, the humans in the loop, has been amazing. So tell us about how many people you have, what you’re doing, and what does scaling really mean for

Radha Basu

you? Actually, indeed. I said, indeed. you know I’ve had quite a journey together and sorry by the way I have to say how you know when you say Hewlett and Packard she actually worked with them yes so Lakshmi really dates me as well but that’s okay I work with Andy Grohwal so let’s really date ourselves I grew up in HP I’m originally from Madras and that’s where I did my engineering and you talk about being a woman in the room it was we were 17 girls and 2800 boys in engineering and I really had the opportunity and I went to get my masters in the US and just kind of fell into working at HP labs which was one of the most prestigious places then and the beauty of HP was David Packard particularly and I was really literally did the management by wandering around.

You would run into him everywhere, open offices, and ended up being a mentor. I was so fortunate. The two of them created Silicon Valley, the Silicon Valley we talk about today. And then when I had the opportunity by sheer, I ended up in Europe, ran medical products group for HP in Europe. And then at that point, I was like, okay, I’m going back to the U.S. What am I going to be doing? And there’s this whole thing about what is happening in that country of yours. It’s so behind in electronics, the country of mine, India. And I was so kind of enraged by that comment. I said, that’s rubbish. We have the best mathematicians, all of which is true.

So David Packard said, okay. I’ll give you three months. Go and figure out what you can do in India. And I tell you, it was the greatest opportunity because I ended up in this beautiful garden, sleepy town called Bangalore. And growing up in Chennai was, of course, I’d gone to Bangalore for my holidays. And the talent of, you know, when you’re working with computers, I used to actually at that time, I was working on multi -threaded Unix. And the kind of talent and what you could develop anyway, it wasn’t three months. That extended to about five and a half years. And I set up Hewlett Packard in Bangalore. And the first two multinationals of anybody doing software in India was Texas Instruments and HP.

The other most amazing thing at that time, I think even more amazing, was those were the years that TCS started. Infineon. HP started. Wipro started. TCS started. And I was just a little bit more experienced. And so we celebrated together the first million dollars of software export from India jointly. And I remember doing that million in 1989. I bring this up because if you, if when, within a lifetime when you can see an industry, technologies completely transform a large country with a growing middle class. And it’s just the creation. I mean, there is no question that IT is the global leader is in India. There is no question about that. So now you fast forward and you come to AI.

AI in turn is changing IT. It’s changing IT in ways that we never believed. It was even possible. And I think that so we started IT. And we’re still doing it. And we’re still doing it. it. It will be 10 years in AI in April. So thinking, and that’s what’s fun about being in the IT industry early on. Then you say, well, what’s happening to this industry? Multi, multi, multi billion dollars. And we started in AI. So we’ve kind of had a ringside seat. It’s also you go through when you start something early enough, you go through its issues. We have done a lot of work in computer vision, not just the language model side, but the computer vision side.

And I’ll talk a little bit about it. But at this point, we have, and many of them are AI Kiran folks. We have about little over 10 ,000 people working in AI. 3 ,500 or so in India. and our in -house talent in India working in AI is about a lot of, most of them are in -house. And we also decided to set up AI centers, not in the metros, because remember what transformed India was the work in Bangalore, Noida, Gurgaon, Chennai, et cetera. How do you then take it and use AI now, it’s the new technologies, but not have a divide? The last thing I want is, you know, like five or ten years from now, we’re all discussing how do we bridge the AI divide, as we’ve been doing, how do you bridge the digital divide?

If we could bridge it now, which is what I love about AI, Kiran, then you are in charge and you grow and you scale. So we started setting up. We started setting up centers in Calcutta, Vizag. Coimbatore, Hubli, Shillong. And so those are our centers. And each center now has become a center of excellence in a particular area. And the three areas that we work in, it was wonderful to hear this yesterday. We work four areas, actually. We work in autonomous mobility and robotics, which is our largest business. And there we have people in Kolkata and Meche, Bruce. And then Vizag is the center of excellence for healthcare medical AI. Coimbatore, and not because I’m Tamil, this is the first thing I’ve done in Tamil Nadu, but Coimbatore is our first center of excellence in Asia, automotive AI center of excellence.

And the way that center has grown, you know. And then our generative AI work is primarily in Kolkata. Shillong, it’s in multiple places. and we work with the large foundation model companies. So then what do you do? You can focus and focus and focus on the large models. How do you take that into applications for precision agriculture, breast cancer screening, healthcare AI, into the different areas that are so critical for societal applications? So we work with the foundation model companies to create what are called small models, small vision models, small language models, and then fine -tuning those models and working in reinforced learning with human feedback, red teaming, that means collaborating with the models, what we call tormenting the models, because how do you find out whether this model works or not?

You torment the darn thing. You torment it till you break it. That’s an actual technical term, let me tell you. You torment it till you break it. Okay? And then you do the data set creation to make it right. So then we will bring in experts. So we have on as scholars, we call them globally, and you can’t just do this in English, PhDs in mathematics, cardiologists, radiologists. They’re called scholars. Interventional, something, something. I found out more about this. Agronomists. Agronomists in Germany. Agronomists in the U.S. Agronomists. And this is where the beauty of AI and this potential. It’s not potential for me anymore. It’s real. It’s a 10 -year -old company. We run a fairly large business.

It’s cash positive, earnings positive. It’s got all of that stuff. But it’s business that drives the inclusion. And bringing in these experts means. You not only are inventing technology in Silicon Valley, Bangalore, et cetera, you have a global set of people and experts who are contributing to AI. So for me, let me end by one thing, which I know is most important. It’s 53 % women. 53 % women. And I’ll say one thing. I believe in this, really. If anybody asks you, how do you run a company with 50 -50 women, look them straight in the eye and say, have you seen the world lately? It’s about

Kirthiga Reddy

50 -50. And there should be no reason why AI technology cannot be 50 -50. Thank you. Beautiful. Well, that sets the stage beautifully for maybe the next question to me here. Where you’re a new author. and this is a topic that you spend a lot of

Mihir Shukla

I applaud the vision because as Radha rightly said the idea of getting it at the beginning is the right idea and I’m a big fan the book that you referred to is called a five year century isn’t available it will be available soon available for pre -order because we are going to see the change what happens normally in a hundred years within the next five years now fortunately we have seen this kind of change at least once before in the recent past around 1900 when electricity radio, automobile and planes came in about the same 10 -15 years time frame, imagine you went to sleep and you woke up 10, 15 years later, it would look like a different planet in every way possible.

It worked out for the most part. So we are about to see all of that now in five years. And in my role as a CEO and chairman of Automation Anywhere, we see the world through a very unique lens. We have about nearly half a billion digital workers that are powered by AI today run on our platform. It will reach a billion soon. The human worker to a digital worker ratio is 1 to 20. There’s 20 digital workers for every. And it is happening across 90 countries. We have customers in 90 countries across every industry. So when we saw all of this, we decided to write a book and say, it is time to tell the world what is happening, what is coming, and what is the leader.

playbook looks like.

Kirthiga Reddy

Incredible. And maybe, Ashna, we’ll go to you. You represent another iconic company, AMD, that has been at the heart of this revolution. As we think about scaling human potential and as we think about the opportunity globally and in India, what do you feel are the limiting factors or the enablers? Is it talent? Is it capital? Is it compute? How do they interact?

Speaker 1

You know, just to build off what both Radha and Meha said, there is no debate about the transformational nature of what we’re all experiencing. But change inherently is always personal. And what happens when you see either people who are super positive or super negative about something, it’s because they’re internalizing what they think it means to them or what it means around them. And so when you talk about… infrastructure or assets or how the world is shifting, these are all going to happen. I mean, we have, as a generation, relied exclusively and maybe I would say not exclusively, but at least extensively on human intelligence. Human intelligence has done the most brilliant things, but human intelligence has also made way for artificial intelligence.

And it’s about a model of coexistence as this develops that has to be evolved. And so from an infrastructure perspective, when we think about it, our goal is to make sure that the innovation that we as humans have ambition for is fully supported in what we build and what we deliver for the world. That’s simply put. How that ambition gets realized ultimately is in our hands, right? And so I think that’s where we have the ability to shape it early. We have the ability to drive success. and we have the ability to learn from history. Now, I will say that having been a history buff growing up, you always want people to learn from history, but people never do.

And so you should just expect that this is going to be the most interesting time that we are living and experiencing. And I would encourage and challenge everyone to make the most of that challenge of what it means to them personally and how you drive it. I mean, that’s my personal view. We will continue as a company to go build the best technology out there to support and drive and be the best partner to the businesses we work with. But ultimately, it comes down to the ambition each of us sets, each of the corporations set, each of the organizations set on the kind of change you want to drive.

Lakshmi Pratury

No, I think it’s beautifully put. I think it’s very different people coming together, people in hardware, software, services, training, all kinds of things coming together. And that’s why for us, at AI Kiran bringing very diverse forces is important and one of the biggest things for us is youth. When we look at AI Kiran, we say what can we do to get women into the fold and what do we do with youth and how do we make sure it’s safe for youth and it furthers the knowledge. It’s not just consumption but creation. So I think we have a program called Fellows Programs. Every year we pick 20 amazing people from different disciplines and put them together and I always say that that’s a great way to adopt children without carrying them.

So we have over 250 of them and Anurag is one of our Inc. fellows and he runs something called Manzil Mystics and the reason we wanted to bring this perspective is working with youth and creativity is extremely important. So Anurag, you’ve been in the music field for a long time and you’ve been in the music field for a long time and right now you’re working with over… 60 ,000 children across 900 schools teaching music. They have taken on one thing. They said, we’re going to teach music. And you actually have a van that you take to different schools and teach them. And tell me a little bit about, you teach things like intellectual property and human rights, all kinds of these things through music.

So tell us about that journey a little bit.

Anurag Hoon

Yeah, and thanks, Lakshmi. Lakshmi, I remember eight years ago, like seeing this dream with you. And she used to see my eyes glittering when I used to talk about this mobile music school. And it’s a reality now. And what I would say, for me, it’s less about AI. It’s more about HI, heart intelligence, because we’re talking about human. And what makes us human is a heart pumping and making us alive. And the heart is learning all the time. And so, and we. Thank you. and i personally saw like my story um i grew up in a low -income family in delhi studied in a government school got 52 hence no college started learning music and i in within a year i started my band i was in the u .s in seattle learning marketing and sales and how did it happen um it happened because music helped us learn that but because i create my original songs based on ideas of kabirji and gandhiji and first thing was what if someone steal my work and this this thing was there like what what if someone steals my idea and and it was very easy for anyone to just take your idea or maybe take your song and sing in a movie or a stage so for us one of the first thing that we teach you how to sing write compose and perform a song it it is very important for us that we may that that they don’t lose their property with their create.

Also, they don’t steal anyone’s property, which was there. And I was doing that, translating some English song, putting some Hindi lyrics and making myself cool. But I was like, no, that’s, create AI is there to help us learn things. And that’s what we made sure that every time we go in a classroom and a child learns to write a song or compose a song, they must know that intellectual property is a thing. And it is a big career opportunity right now. All the streaming platform have made sure that people who are like me creating a song get the royalty. But if I create a song through AI, they don’t get money. So we always say, if you want to be, if it’s fun, if you want, then do like create song through AI.

but the streaming all streaming platforms is you cannot earn money so we always say if you want

Kirthiga Reddy

to earn money create a song on your own absolutely well I mean one is so amazing to see the diversity that’s represented on this panel and you know start thinking of your questions we’re going to do one more prepared question but then we want to hear what’s on your mind as well and so let’s bring us back maybe to this historic India AI Summit and I know you know many people many announcements being made by the panelists and you know our attendees here as well on my end certainly you’ll see a number of AI announcements has already started we’ll turn to be here in a few minutes to talk about that as well so there’s AI announcements there’s also my startup Optimize Geo where having helped brands with a move to mobile and social and being relevant there Optimize Geo and I have to say in India it’s generative engine optimization it is not JIO it’s Geo we are helping brands with being relevant because business decisions consumer decisions are being made off of questions being asked by chat GPT perplexity and the like so that’s the platform and we have a bunch of announcements there but Ashna maybe coming to you we are sitting here at this Historic India AI Summit and if access to advanced chips is going to determine who can build powerful models are we at

Speaker 1

service intelligence and complement it with artificial intelligence. And that complementing of artificial intelligence is about how do you then have a thoughtful strategy as a country, as a company, as a startup to build that compute layer and that compute investment structure that gives you the outcomes that you need that complement the human ambition and the human scale you want to achieve. So I think it’s both. I don’t believe it will be a limiting factor for those that want to move fast. You just have to be creative with the resources you have. And believe me, we’re building fast and as quickly as we can to meet all the demand that we have. So Radha, continuing on that about being faster here than anywhere else, you’ve been doing that for 10 years before AI was a fashionable word.

What kind of investments do you think are needed to move people up the value chain of AI in India? And maybe we’ll have to comment on the same because I think it’s a really important question.

Radha Basu

Right. So if you look at the three parts of investments in AI, think of it as a triangle, right? And we’ve heard a lot of this. It’s the AI, let’s call it the technologies, the models, all the stuff, the open AI, the anthropics, the Google, deep minds, et cetera. Then there’s all the infrastructure, and you’ve heard all the announcements, multi -billion dollars of infrastructure. And then there is AI intelligence, and that is the human intelligence. And it’s the nexus of the technology intelligence, the infrastructure to do this, and the human intelligence that really scales AI. So yes, should we be worried about AI taking away jobs? I think we should. But to me, it’s not taking away jobs.

It’s how the jobs are evolving. So you ask me, what are the investments needed? And this is where I think, really, I mean, yesterday, I felt so, I feel very hopeful with young people anyway. Average age of our company is 24 .5. You would never know that looking at me. And the sassiest people in my company would say, if it was not for you, it would be 23. I’ve actually, and that’s that sassy young people from all over India, not from the cities, necessarily, not the IITians. So what is changing in AI? You can take young people from a variety of different backgrounds. And we had some young people come into the iMerit booth and say, we’re in commerce, or we’re in something else.

How do we become AI people? that transformation or that it’s like an equation how do you take a large number of young people and you i don’t want to use the word skilling but they become ai ready so you want to make data ai ready you want to make young people ai ready and you want to make the infra ai ready when you do all those three things the daunting scales the second thing i would say is and this came out quite a bit in the discussions yesterday whether it was daria speaking from anthropic or definitely you know from google sundar talked about this what are the applications of ai that is where we are today we’ve got the large models and of course they are scaling how do you apply it to the big picture and how do you apply it to the big picture and how do you apply it to the precision agriculture because if you do and you can you can actually catch crop failure We work with people like John Deere, and you catch the crop failure in an area like this.

You’ve saved the entire field from just, and they have seen immense amount of production increases because of that. If you can look at breast cancer screening for women, and you can screen people all over, breast cancer in India for Indian women versus Asian versus Caucasian versus black, the smaller models are very different because the parameters are different. If you can use that, then you’re starting to get AI into societal applications and then into enterprise AI because that’s where the big business, any technology scales and gets adapted and adopted when the enterprise. Start to use them, accounting, legal, et cetera. So that is the investment that’s needed. handing it over to

Mihir Shukla

you Mihir I think I’ll cover it in two different dimensions the first is focus on applied AI so I think it is best especially for India it’s good to develop the models but not to blindly chase this model race that’s happening in western world because if you look at the history the printing press was invented in Germany Dutch used it and became a superpower for few hundred years industrial revolution was invented France has all the parameters to succeed a small island of England used industrial revolution in every aspect of the economy became Great Britain making a point that you don’t have to invent a technology the success lies in applying that technology in every aspect of economy and that is India’s superpower if it focuses on is on it.

You have 18 or different industrial hubs in each of them, very specifically applying applied AI like I heard automotive AI, right? Can you create global competitiveness with those models? That’s where the primary investment has to go and it can completely change the economic outlook. The second thing where investment needs to go is an inclusion. I think this is a remarkable technology that can include a vast amount of people that were previously not included in digital economy. Think about the first computers with an English keyboard. You can’t include 90 % of the world population in that interface. Then came the mobile phone that got a little easier. Now you have a technology where anybody can talk, easily participate.

So this is the time to include everybody. And one of the things AI Kiran and we are doing together is we announced a partnership where together we will, in the next five years, we will train a million women and youth on AI and automation together. And I think both sides have to happen. We need to make economic growth and we have to make sure we

Kirthiga Reddy

And tell us a little bit about the wonderful work you do as you also ask your question.

Audience

Hi, my name is Anupama. I am one of AI Kiran members. Professionally, I’m a data scientist. Now moved to a technical lead role where I’m actually helping a lot of banking and financial institutions come up with AI and automation solutions. So I work a lot in building up POCs, use cases, and at the end of them, building up strategies for them to come up with enterprise solutions for them. My question is basically to Anurag you, and this is a little bit of a personal question. We’re talking about AI, and we’re talking about scaling. We’re talking about a new world. My question is, what is it that we as parents should be teaching our kids for the next 15 years when the world is fully automated?

They are already in an AI age because they’re growing in an AI age. They see AI. They hear, do, and in fact, they’re doing everything right. So what are those skills that we as parents should be teaching our kids to be ready? For the next 15 years and, yeah, in the AI automated age. what is it that we should be you know thinking through at this point i mean of course skills will come at a later stage but what is it that we what are what are those blind spots that we don’t see as parents and as people or as professionals who are just busy in building up solutions who are busy in automating things but there’s a human factor out there right uh after 15 years what is it that is going to make them stay

Anurag Hoon

that’s a brilliant question our og mama is here so she can answer better um i guess i when i became an ink fellow i became a father also my son is eight years old i am an ink fellow for eight years uh for before that two years i learned to be a father uh then i became a father so i feel the more onus is on us um i put this is my very personal i feel the five senses um and then nine emotions Navras and India has a lot of literature I guess as a parent I just made sure that my son understand the five senses and nine emotions and then I plan everything according to that it’s not like I don’t want to give phone to my son or I don’t want to do this or that so my son does all those things one of the things he started doing was birthday celebration going on street or maybe going somewhere and making him sense all these things so I guess five emotions, nine emotions five senses if we know it we can

Speaker 1

so basically you are saying that we need to be consistent with the five emotions the five senses and nine emotions like and ensure that this is there at the same time parallelly where we are even automating and we are bringing AI. And you should send us that list of five senses and nine emotions and we’ll share it with the community as well. I mean this is maybe I feel fairly strongly about this. I think we need to teach all our kids resilience. They need to learn to fail. They need to know it’s okay to fail. They need to know life is not easy. They need to know life is unfair. And they need to learn to survive and thrive and learn to be happy in it.

So if they have resilience they will survive all these changes. And I think that’s where you see kids struggle because when kids don’t know how to be resilient that’s when they struggle. When you teach them early and you know you’re there as a support mechanism for them to go through those experiences they will learn. And especially with the change we’re about to experience. even we don’t know I mean we can sit here and speculate as a panel what the world is going to look like in 15 years we don’t know

Radha Basu

that’s something that’s really great you know it can add one thing to this oh yeah it is so she didn’t ask the question she said as parents I’m gonna talk as a grandparent okay hey age comes with this right and it wasn’t so much them asking me it was my asking them and this is my niece and I said Nikki so what is it you think you’ve learned at school he’s a junior it’ll say he’s an 11th and just one more year to go I said what do you think we should be teaching kids at school and he says party and I said what do you think we should be teaching kids at school and he says look I don’t think there is anything you can really teach us at this point because AI is beyond all the parents which I actually agree with and we started talking about it and the thing that came out is being a curious learner because he said and I’m repeating to you not what I said to him but what he said to me he said whatever I learned last year I wanted to go into computer science at Stanford it was my biggest dream hey that’s not going to get me a job and I have to do different things I have to know what’s going on resilience I totally agree I loved your answer to it because it gave a completely from the heart and from the brain and from nature but this thing of knowing what’s around you learning about it, being curious about it because that is really important in AI.

You keep pinging it to make it better, right? And this is part of the intelligence. So thinking critically, curious learners, none of this is going to happen by keeping phones away from them. They’re going to learn to be curious because they want to be and go out in nature and learn it, right? Or wherever. And go out into the field. If you want to work in precision ag and a kid from the city doesn’t know anything about it, or in medical, whatever the thing. So to me, the answers

Mihir Shukla

I was going to quickly say there are three elements, in my opinion. The first is, in my generation, we only studied one subject, like computer engineering. I think today, people are going to do multiple things, right? So combining. And when you combine, the possibilities are limited. less. People who study rock climbing and video game design and when that person creates a rock climbing video game, it will be the most authentic experience you could ever get, right? So things like that, neuroscience and medical, there are just unimaginable possibilities. So that is on the career side, how you progress. I think second thing I asked my daughter, just like you said, you asked them and she said, that stayed with me, she said that the future is that there are no worker bees.

There are only queen bees. I loved it. I loved the spirit of it. You know, the empowerment it embodies, the ambition it embodies and I think if everybody had that mindset, amazing things are possible.

Kirthiga Reddy

You know, I think what we are going to do is actually we are just going to ask the question we are going to combine the questions. So just we’re going to hear a bunch of questions and then the panelists can just pick whichever they want and what they want to do. Okay, question.

Mihir Shukla

Sorry, I remembered the third one. I think the third thing is the power of the question. So this amazing thing AI that we have, it knows many answers, but it doesn’t know what are the right questions. And it is not likely to know anytime soon. And so having the right questions, I share this example with you on our family dining table. I do this experiment to learn from the younger generation because they instinctively know what the future is, right? They know better than us. So we made a rule once and said, you know, we’re going to talk about a subject and you can’t tell me anything that Alexa, Siri, or ChatGPT would tell me. So they said, okay, bring it on, Dad.

I said, okay. So we talked about some bird with the longest wingspan or something. And they said, Dad, that’s not fair. The question itself is, bias towards chart GPT. Ask me something that is, they said it nicer than this, but they said, ask me something that is worthy of human. So I said, okay. So I said, the Patagonia has the ecological imbalance after all the industrial development. In order to restore it back, it’s a complex thing. How do you introduce new species and complex problem and so how do you bring it back to its original state? That dinner conversation went on for three days. Various tools were used and together as a family, we came out with a plan on if you were to do it, what would that look like?

Now imagine those conversations happening on every dining table, if we have the right questions.

Kirthiga Reddy

Amazing. All right. Just quick spattering of questions and then we’ll have the panel just take yes, yeah, question.

Audience

Hi, my name is I’m founder of an AI company. We work with global higher education institutions. So I actually led my life very differently when I went to IIT. I never studied. And I look back and I say I did the best thing. So my question right now is that with the disruption that we are seeing and pretty much like IQ is gone by AI, the only thing that we are left with is EQ. And if you look at the education system and the system here, we actually hold on to something. Like we hold on to some exam, some college, and then some company. Then eventually we grow. So I want to hear from you guys how would you like to now disrupt at the fundamental levels, which is K -12, going into higher education, in order to support what is happening.

Disrupting education at fundamental levels. Hi, I’m Hemendra. I teach AI and sustainability at IIM Udaipur. And quick question. We. A lot of countries are now banning multimedia because the harm is obvious, because we didn’t have the guardrails and things came along. AI is only going to amplify the harms, just like it’s going to amplify the power. We heard about the power, and we know maybe AI can be used. The guardrails that we need for the younger generation is just connected to the question, follow -up to him, is what do we need to protect our kids from the harm while we give them the power? Thank you so much. This is Anjali. I represent Tech Mahindra.

I have been doing throughout my career, you know, connecting the left brain with the right brain, which is creative in technology. So hence, you know, AI is very close to my heart as well. So, ma ‘am, the question that I have for you is basically today in the world, people are getting overwhelmed and confused. There are so many platforms. coming over, so many methods coming over, right? If somebody has to ideate and strategize what to learn first and what next, right? How to go about it? Because so much is happening. There’s a lot of panic around Last question. Bina, AI Kiran member, part of ServiceNow, also a woman for ethical AI movement. How do we build trust in the internet?

Earlier you had provenance via people curating the internet. Now people are turning to ChatGPT and trusting those answers over human answers. How do you build provenance? That’s the main question. Last question, sorry. I do grassroots training with people for AI, but their digital gap is still very high. I have to go back and teach them tech before I can teach them AI. How do you solve this? Because we are having a lot of conversations around the youth and the power of the question, etc. All of you are fermented with wisdom. the application of AI and what you bring to the lens, how do you crunch that wisdom cycle of the youth? Because at the end of the day it is information age.

There’s so much information coming. So facts, figures, information, you’re brilliant at. But how do you build that wisdom to infer, to ask the right questions and to interpret? Can you crunch that wisdom?

Speaker 1

So we’re going to give like 30 seconds to each of the panelists as they close. I mean, I think on learning you just start. There are incredible tools. I mean, it’s amazing how quickly the tools and the capabilities to learn in this space have developed. And how fast you can learn. I mean, if any of you were paying attention to the series of events, TCS did a hackathon where they got women from all over the country. This was 1 ,200 women, right? Non -native, they’re not English speakers. They come from different walks of life. And in four hours, they were able to do brilliant things with the training that they received. I mean, these are the kinds of things.

So the potential is massive. So I think anybody, and that’s the beauty of what we have in AI and the positive side, is you can just take it and run with it and learn. I’m an optimist. So I believe you can always find what doesn’t work. But I think if more of us focus on what works, we can do a lot more good a lot faster than what can go wrong. This is the only panel where nobody has asked us about impact on jobs. So I’ll leave it at that.

Mihir Shukla

I’ll take the aspect of how do you teach them digital skills and then the AI skills. I think there is an opportunity here to skip some of the old digital skills because they weren’t very friendly. I think that in the new… In the new world, we have seen… I’ll give you a few examples. We train… We trained 700 women in Africa for six weeks, and 500 found a job within a week. We trained people in Mississippi Delta, which is a very poor part of the U.S. There was somebody flipping burgers at $12 an hour. Six weeks later, they had a $120 ,000 job in AI. This is a technology that doesn’t require you two or four years training courses, which normally the people who are needed the most can’t afford to have it.

So the fact that you can provide this kind of mobility on this technology is arguably the best thing about this technology.

Anurag Hoon

I guess for EQ, education disruption, EQ, to work on EQ is arts, and that’s a disruption. I’m glad AI came, and hence Invest India just shared that the 3 trillion Indian rupees, it’s going to be that’s the market size, because… for media and entertainment sector because the world has recognized that if you want EQ to be developed, invest in arts. Live music classes are increasing drastically and that’s where I’m here. We can talk more about this.

Radha Basu

So for me, this is not a question for the future. 72 % of the people who work at iMerit come from very low -income backgrounds and come from the hinterland of India. So it is absolutely possible to be able to… You start as though they haven’t been skilled before at all. You know, AI is new. There’s no baggage. It’s wonderful. As Mihir said, there’s a whole new way of doing it. And they learn and they are… They use AI to learn and what they learn, they teach AI. It’s really… It’s really interesting to watch. You have young women in a place called Meteor Bruce who came from tailoring and those kind of backgrounds. Why are they a center of excellence for computer vision?

Because the focus on that single pixel level accuracy is something that they have, and they learn the other skills. I would finish by saying you also have a foundation called Anudip, and this is really working across. And 630 ,000 young men and women, 50 % being women, have been skilled, have been skilled in AI literacy. Literacy, just knowing what is AI, how do you use it. I know it doesn’t address the IRM part, but I’m just talking about at the grassroots level. And when they learn how to work with AI, it’s not an enigma. It’s harder. I would say the last thing I would say, and I love my industry colleagues. it’s harder to take somebody from industry and train them in AI because they have to unlearn first than to take a young person out of some place in Odisha who comes from a second tier or even villages and be able to skill them in AI as to how to be working with AI so it’s the nexus of AI technology and that human and I’m such a believer that we can do this here.

Kirthiga Reddy

Awesome, so with that let’s give a huge round of applause for our panelists one, two if you want to get involved in the AI moment around women, youth, differently able, we have incredible leaders here, Prerna, Neha Vaibhav, they are truly the heart and soul of making this happen so let’s hear it for them, please ask them their questions and feel free to come grab any one of us if your questions didn’t get answered. thank you I just want to say end up with saying that if you can work with people smarter than you if you can work with people half your age and twice as smart I think we’ll find all the answers and thank you so much for giving your time, thank you you

L

Lakshmi Pratury

Speech speed

172 words per minute

Speech length

903 words

Speech time

314 seconds

Reinvention and storytelling platform

Explanation

Lakshmi explains that over the past 15 years she has been building a platform to surface hidden talent and tell their stories, framing this as a reinvention of long‑standing practices of discovery and narrative. The goal is to showcase amazing people whose work is rarely heard.


Evidence

“And then I decided for the last 15 years, my journey is going to be how to create a platform to showcase the amazing talent that’s there in India and across the globe that doesn’t get told.” [1]. “This is just a reinvention of things we’ve been seeing for the last 50 years, you know.” [9]. “But what brought us together to AI Kiran is that for the last 15 years, my work has been about finding amazing people, doing amazing work and get them to tell their stories, because we only hear about the 10 famous people, but innovation is happening everywhere.” [11].


Major discussion point

Personal journeys & scaling human potential


Topics

Closing all digital divides | Capacity development


Fellows program for youth

Explanation

She runs a Fellows program that selects twenty multidisciplinary youth each year, describing it as a way to “adopt children without carrying them” and to give young people a structured path to develop future skills.


Evidence

“Every year we pick 20 amazing people from different disciplines and put them together and I always say that that’s a great way to adopt children without carrying them.” [124]. “So I think we have a program called Fellows Programs.” [125].


Major discussion point

Education, upskilling, and future skills for youth


Topics

Capacity development | Social and economic development


Inclusive AI from the get‑go

Explanation

Lakshmi stresses that AI Kiran must be inclusive from its inception, using the phrase “get‑go” to underline that gender and background diversity are built into the initiative from day one.


Evidence

“to make it inclusive from the word get -go.” [80].


Major discussion point

Building an inclusive AI community, especially for women


Topics

Closing all digital divides | Artificial intelligence


K

Kirthiga Reddy

Speech speed

176 words per minute

Speech length

1339 words

Speech time

455 seconds

Risk‑taking and starting over in AI

Explanation

Kirthiga encourages taking risks and asks the audience to imagine what they would do if they weren’t afraid, positioning bold moves as essential for thriving in the AI era.


Evidence

“So it’s about, you know, taking risks and not being afraid to start over again.” [16]. “You know, what would you do if you weren’t afraid?” [17]. “I had someone come up to me yesterday and say, hey, if their business is on a certain trajectory, but now if they have to move over to AI, if it meant starting over all over again, what would I recommend to them?” [18].


Major discussion point

Personal journeys & scaling human potential


Topics

Artificial intelligence | Capacity development


Scaling AI Kiran community to 10,000 women

Explanation

She notes that AI Kiran began with 250 women and has grown to a self‑organising community of about ten thousand women, highlighting rapid scaling and grassroots mobilisation.


Evidence

“Now it’s an incredible community of, you know, 10 ,000 women who are all taking this on their own, rallying it, self -organizing.” [67]. “And so over that period of time, so we launched with 250 named women.” [75].


Major discussion point

Building an inclusive AI community, especially for women


Topics

Closing all digital divides | Artificial intelligence


Gender parity vision – 50‑50 AI technology

Explanation

She asserts that there should be no reason why AI technology cannot be split equally between genders, reinforcing a commitment to gender parity in the field.


Evidence

“And there should be no reason why AI technology cannot be 50 -50.” [110].


Major discussion point

Building an inclusive AI community, especially for women


Topics

Closing all digital divides | Artificial intelligence


R

Radha Basu

Speech speed

139 words per minute

Speech length

2565 words

Speech time

1099 seconds

AI centers in Tier‑2 cities

Explanation

Radha explains that AI centers have been established outside the metros—in Kolkata, Vizag, Coimbatore, Hubli, Shillong—to bring AI capabilities to industrial hubs and replicate the transformation that earlier IT hubs delivered.


Evidence

“And we also decided to set up AI centers, not in the metros, because remember what transformed India was the work in Bangalore, Noida, Gurgaon, Chennai, et cetera.” [31]. “We started setting up centers in Calcutta, Vizag.” [33]. “And then our generative AI work is primarily in Kolkata.” [34]. “Coimbatore, and not because I’m Tamil, this is the first thing I’ve done in Tamil Nadu, but Coimbatore is our first center of excellence in Asia, automotive AI center of excellence.” [36]. “And then Vizag is the center of excellence for healthcare medical AI.” [101]. “Coimbatore, Hubli, Shillong.” [102].


Major discussion point

Infrastructure, AI centers, and applied AI for societal impact


Topics

Artificial intelligence | The enabling environment for digital development | Social and economic development


Applied AI over model race

Explanation

She argues that India’s strength lies in applying AI to real‑world problems rather than chasing ever‑larger models, citing historical analogies of the printing press and industrial revolution.


Evidence

“I think it is best especially for India it’s good to develop the models but not to blindly chase this model race that’s happening in western world because if you look at the history the printing press was invented in Germany Dutch used it and became a superpower for few hundred years industrial revolution was invented France has all the parameters to succeed a small island of England used industrial revolution in every aspect of the economy became Great Britain making a point that you don’t have to invent a technology the success lies in applying that technology in every aspect of economy and that is India’s superpower if it focuses on is on it.” [115].


Major discussion point

Infrastructure, AI centers, and applied AI for societal impact


Topics

Artificial intelligence | Social and economic development


Gender parity and low‑income inclusion

Explanation

Radha shares that 53 % of iMerit’s workforce are women and 72 % come from low‑income backgrounds, and that 630 000 individuals have been skilled in AI literacy, demonstrating a strong inclusion agenda.


Evidence

“53 % women.” [85]. “It’s 53 % women.” [86]. “72 % of the people who work at iMerit come from very low -income backgrounds and come from the hinterland of India.” [87]. “And 630 ,000 young men and women, 50 % being women, have been skilled, have been skilled in AI literacy.” [90].


Major discussion point

Building an inclusive AI community, especially for women


Topics

Closing all digital divides | Capacity development


Jobs will evolve, not disappear

Explanation

She emphasizes that AI will change the nature of work rather than eliminate jobs, positioning technology as a driver of new opportunities.


Evidence

“It’s how the jobs are evolving.” [47]. “But to me, it’s not taking away jobs.” [174].


Major discussion point

AI’s impact on jobs, economy, and the need for up‑skilling


Topics

The digital economy | Social and economic development


M

Mihir Shukla

Speech speed

155 words per minute

Speech length

1199 words

Speech time

463 seconds

Scale of digital workers

Explanation

Mihir notes that Automation Anywhere powers roughly half a billion digital workers, with a ratio of one human worker to twenty digital workers, illustrating the massive scale of AI‑enabled automation.


Evidence

“We have about nearly half a billion digital workers that are powered by AI today run on our platform.” [144]. “The human worker to digital worker ratio is 1 to 20.” [168].


Major discussion point

AI’s impact on jobs, economy, and the need for up‑skilling


Topics

The digital economy | Artificial intelligence


Partnership to train 1 million women and youth

Explanation

He announces a five‑year partnership with AI Kiran to train one million women and youth in AI and automation, underscoring a large‑scale upskilling commitment.


Evidence

“And one of the things AI Kiran and we are doing together is we announced a partnership where together we will, in the next five years, we will train a million women and youth on AI and automation together.” [69].


Major discussion point

Building an inclusive AI community, especially for women


Topics

Capacity development | Closing all digital divides | Artificial intelligence


Applied AI focus for India

Explanation

Mihir echoes the need to prioritize applied AI solutions over chasing large models, arguing that India’s comparative advantage lies in deploying AI across sectors like agriculture and healthcare.


Evidence

“I think it is best especially for India it’s good to develop the models but not to blindly chase this model race that’s happening in western world because if you look at the history the printing press was invented in Germany Dutch used it and became a superpower… the success lies in applying that technology in every aspect of economy and that is India’s superpower if it focuses on is on it.” [115].


Major discussion point

Infrastructure, AI centers, and applied AI for societal impact


Topics

Artificial intelligence | Social and economic development


S

Speaker 1

Speech speed

170 words per minute

Speech length

987 words

Speech time

346 seconds

Compute layer complementing human ambition

Explanation

Speaker 1 argues that building a compute infrastructure that aligns with human ambition is essential, describing it as a thoughtful strategy that pairs artificial intelligence with human scale.


Evidence

“And that complementing of artificial intelligence is about how do you then have a thoughtful strategy as a country, as a company, as a startup to build that compute layer and that compute investment structure that gives you the outcomes that you need that complement the human ambition and the human scale you want to achieve.” [53]. “And it’s about a model of coexistence as this develops that has to be evolved.” [54].


Major discussion point

Infrastructure, AI centers, and applied AI for societal impact


Topics

Artificial intelligence | The enabling environment for digital development


Teach resilience and ability to fail

Explanation

He stresses that children must learn resilience, be allowed to fail, and understand that failure is part of growth, positioning these traits as core competencies for the AI age.


Evidence

“I think we need to teach all our kids resilience.” [66]. “They need to learn to fail.” [135]. “They need to know it’s okay to fail.” [136].


Major discussion point

Education, upskilling, and future skills for youth


Topics

Capacity development | Social and economic development


Human‑AI coexistence model

Explanation

Speaker 1 highlights that human intelligence has enabled AI and that a model of coexistence is required, suggesting that future progress depends on integrating both intelligences.


Evidence

“Human intelligence has done the most brilliant things, but human intelligence has also made way for artificial intelligence.” [65]. “And it’s about a model of coexistence as this develops that has to be evolved.” [54].


Major discussion point

Personal journeys & scaling human potential


Topics

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


A

Anurag Hoon

Speech speed

142 words per minute

Speech length

686 words

Speech time

288 seconds

Heart intelligence and music for IP education

Explanation

Anurag describes using music as a vehicle to teach children about intellectual property and human rights, framing this as “heart intelligence” that blends creativity with ethical awareness.


Evidence

“It’s more about HI, heart intelligence, because we’re talking about human.” [57]. “And that’s what we made sure that every time we go in a classroom and a child learns to write a song or compose a song, they must know that intellectual property is a thing.” [61]. “They said, we’re going to teach music.” [58].


Major discussion point

Personal journeys & scaling human potential


Topics

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


EQ, five senses and nine emotions framework

Explanation

He advocates for integrating a framework of five senses and nine emotions (Navras) into education, arguing that emotional intelligence is essential for thriving alongside AI.


Evidence

“And that’s a brilliant question our og mama is here so she can answer better … I put this is my very personal i feel the five senses um and nine emotions Navras and India has a lot of literature …” [158]. “And you should send us that list of five senses and nine emotions and we’ll share it with the community as well.” [156].


Major discussion point

Education, upskilling, and future skills for youth


Topics

Capacity development | Social and economic development


A

Audience

Speech speed

164 words per minute

Speech length

825 words

Speech time

300 seconds

Widespread visibility of AI

Explanation

Members of the audience repeatedly note that AI is already visible in everyday contexts, signalling a broad awareness that must be harnessed for inclusive policy and practice.


Evidence

“They see AI.” [1].


Major discussion point

Artificial intelligence


Topics

Artificial intelligence | Closing all digital divides


Information overload and need for curation

Explanation

The audience points to the massive flow of data and information, highlighting the challenge of managing, curating, and ensuring provenance of digital content in the information age.


Evidence

“There’s so much information coming.” [3]. “Earlier you had provenance via people curating the internet.” [11].


Major discussion point

Information and communication technologies for development


Topics

Information and communication technologies for development | Capacity development


Focus on youth empowerment and questioning

Explanation

Audience members stress that conversations are centering on youth and the power of questioning, underscoring the importance of engaging younger generations in AI discourse and capacity‑building.


Evidence

“Because we are having a lot of conversations around the youth and the power of the question, etc.” [9]. “We heard about the power, and we know maybe AI can be used.” [14].


Major discussion point

Personal journeys & scaling human potential


Topics

Capacity development | Closing all digital divides


Industry stakeholder representation

Explanation

An audience participant identifies themselves with a major tech firm, indicating corporate interest and the need for public‑private collaboration in AI initiatives.


Evidence

“I represent Tech Mahindra.” [15].


Major discussion point

The digital economy


Topics

Financial mechanisms | The enabling environment for digital development


Agreements

Agreement points

AI enables rapid skill acquisition without traditional lengthy training requirements

Speakers

– Mihir Shukla
– Radha Basu
– Speaker 1

Arguments

AI learning doesn’t require 2-4 year training courses – people can gain valuable skills in weeks, as demonstrated by successful training programs in Africa and rural America


It’s easier to train young people from rural backgrounds in AI than to retrain industry professionals who must first unlearn existing approaches


The potential for rapid learning is massive – 1,200 women from diverse backgrounds accomplished brilliant things in just 4 hours of training


Summary

All three speakers agree that AI skills can be acquired much faster than traditional education models suggest, with evidence from successful programs showing people can gain valuable AI skills in weeks or even hours rather than years


Topics

Capacity development | Artificial intelligence | Closing all digital divides


Inclusion and diversity should be built into AI from the beginning

Speakers

– Lakshmi Pratury
– Kirthiga Reddy
– Radha Basu
– Mihir Shukla

Arguments

AI revolution presents an opportunity to build inclusively from the beginning, unlike previous revolutions that created problems we had to fix later


When AI Kiran started, ChatGPT could only identify 10 women in AI in India, but now the community has grown to 10,000 women who are self-organizing and creating new ventures


Running a company with 53% women should be normal since the world is about 50-50, and AI technology should reflect this balance


AI enables inclusion of people previously excluded from the digital economy – anyone can participate through natural conversation interfaces


Summary

All speakers emphasize the importance of building inclusive AI systems from the start, with specific focus on gender parity and accessibility for underserved populations


Topics

Closing all digital divides | Artificial intelligence | Human rights and the ethical dimensions of the information society


Focus should be on applied AI rather than just model development

Speakers

– Mihir Shukla
– Radha Basu

Arguments

Success lies in applying AI technology across all aspects of the economy rather than just developing models – focus should be on applied AI


AI scaling requires three components: technology/models, infrastructure, and human intelligence working together at their nexus


Summary

Both speakers agree that practical application of AI across various sectors is more valuable than competing in foundational model development, emphasizing the importance of real-world implementation


Topics

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


Children need fundamental life skills and emotional intelligence rather than just technical training

Speakers

– Speaker 1
– Anurag Hoon
– Radha Basu

Arguments

Children need to learn resilience, how to fail, and that life can be unfair while still learning to survive and thrive


Teaching five senses and nine emotions helps children stay grounded while navigating technological change


Future requires curious learners who can think critically and adapt, as what students learn changes rapidly


Summary

All three speakers emphasize that preparing children for the AI era requires focusing on fundamental human skills like resilience, emotional intelligence, curiosity, and critical thinking rather than specific technical knowledge


Topics

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


Similar viewpoints

Both speakers advocate for embracing risk-taking and recognizing that innovation and talent exist broadly across society, not just among well-known figures or established institutions

Speakers

– Kirthiga Reddy
– Lakshmi Pratury

Arguments

Taking risks and not being afraid to start over is essential for growth – if a new trajectory gets you further ahead, it’s worth starting over completely


Innovation is happening everywhere, not just among famous people – the goal is to find amazing talent doing amazing work and help them tell their stories


Topics

Capacity development | Social and economic development


Both speakers demonstrate through concrete examples and commitments that AI training can successfully reach and benefit underserved populations at scale

Speakers

– Radha Basu
– Mihir Shukla

Arguments

72% of workers come from low-income backgrounds and rural areas, proving it’s possible to skill people directly in AI without prior digital training


Partnership announced to train one million women and youth in AI and automation over the next five years


Topics

Closing all digital divides | Capacity development | Artificial intelligence


Both speakers see the future as requiring interdisciplinary approaches where human value lies in creativity, emotional intelligence, and the ability to formulate good questions rather than providing factual answers

Speakers

– Mihir Shukla
– Anurag Hoon

Arguments

Future careers will combine multiple disciplines, and the power lies in asking the right questions rather than just knowing answers


Arts and creativity are essential for developing emotional intelligence (EQ) as AI handles more analytical tasks


Topics

Capacity development | Social and economic development | Artificial intelligence


Unexpected consensus

Starting over completely is better than incremental change

Speakers

– Kirthiga Reddy
– Radha Basu

Arguments

Taking risks and not being afraid to start over is essential for growth – if a new trajectory gets you further ahead, it’s worth starting over completely


It’s easier to train young people from rural backgrounds in AI than to retrain industry professionals who must first unlearn existing approaches


Explanation

Both speakers, despite their different backgrounds (venture capital/entrepreneurship vs. technical operations), agree that fresh starts are often more effective than trying to adapt existing approaches. This is unexpected because it goes against conventional wisdom about building on existing expertise


Topics

Capacity development | The enabling environment for digital development


Rural and underserved populations may have advantages in AI adoption

Speakers

– Radha Basu
– Mihir Shukla

Arguments

It’s easier to train young people from rural backgrounds in AI than to retrain industry professionals who must first unlearn existing approaches


AI enables inclusion of people previously excluded from the digital economy – anyone can participate through natural conversation interfaces


Explanation

This consensus is unexpected because it challenges the typical assumption that urban, educated populations would have advantages in adopting new technologies. Instead, both speakers suggest that lack of prior technical baggage can be an advantage


Topics

Closing all digital divides | Artificial intelligence | Capacity development


Overall assessment

Summary

The speakers show remarkable consensus on key issues including the need for inclusive AI development, the effectiveness of rapid AI skill acquisition, the importance of applied AI over pure research, and the necessity of focusing on fundamental human skills for children. There is strong agreement on practical approaches to AI training and the potential for underserved populations to benefit significantly from AI technologies.


Consensus level

High level of consensus with complementary perspectives rather than conflicting viewpoints. The speakers come from different backgrounds (venture capital, operations, hardware, services, arts education) but align on core principles of inclusion, practical application, and human-centered development. This suggests a mature understanding of AI’s potential and challenges, with implications for successful collaborative efforts in AI development and deployment.


Differences

Different viewpoints

Approach to bridging digital literacy gaps before AI training

Speakers

– Radha Basu
– Mihir Shukla
– Audience

Arguments

It’s easier to train young people from rural backgrounds in AI than to retrain industry professionals who must first unlearn existing approaches


AI learning doesn’t require 2-4 year training courses – people can gain valuable skills in weeks, as demonstrated by successful training programs in Africa and rural America


There’s a significant digital gap that requires teaching basic technology before AI training, particularly for grassroots populations


Summary

While Radha and Mihir argue that AI can be taught directly without prior digital skills, an audience member working in grassroots training insists that basic digital literacy is still a prerequisite for AI education


Topics

Capacity development | Closing all digital divides


Priority between AI model development versus application

Speakers

– Mihir Shukla
– Radha Basu

Arguments

Success lies in applying AI technology across all aspects of the economy rather than just developing models – focus should be on applied AI


AI scaling requires three components: technology/models, infrastructure, and human intelligence working together at their nexus


Summary

Mihir advocates strongly for focusing on applied AI rather than model development, while Radha presents a more balanced view requiring all three components including model development


Topics

Artificial intelligence | The enabling environment for digital development


Unexpected differences

Role of traditional education disruption

Speakers

– Audience
– Anurag Hoon

Arguments

Education system needs fundamental disruption at K-12 and higher education levels to support AI transformation, moving away from traditional exam-college-company progression


Arts and creativity are essential for developing emotional intelligence (EQ) as AI handles more analytical tasks


Explanation

Unexpectedly, while an audience member calls for complete educational disruption, Anurag advocates for strengthening traditional arts education rather than disrupting it, suggesting different philosophies about preserving versus transforming educational approaches


Topics

Capacity development | Social and economic development


Overall assessment

Summary

The discussion shows remarkable consensus on major goals (inclusion, rapid AI adoption, gender parity) with disagreements primarily on implementation methods and prerequisites. The main tensions are between direct AI training versus foundational digital literacy, and between model development versus application focus.


Disagreement level

Low to moderate disagreement level with high strategic alignment. The disagreements are constructive and focus on tactical approaches rather than fundamental principles, suggesting a collaborative environment where different expertise and experiences inform varied but complementary approaches to achieving shared goals of inclusive AI development.


Partial agreements

Partial agreements

All agree that AI can democratize access to technology and enable rapid skill development, but they differ on implementation approaches – Radha emphasizes systematic training programs, Mihir focuses on conversational interfaces, and Speaker 1 highlights the speed of learning potential

Speakers

– Radha Basu
– Mihir Shukla
– Speaker 1

Arguments

72% of workers come from low-income backgrounds and rural areas, proving it’s possible to skill people directly in AI without prior digital training


AI enables inclusion of people previously excluded from the digital economy – anyone can participate through natural conversation interfaces


The potential for rapid learning is massive – 1,200 women from diverse backgrounds accomplished brilliant things in just 4 hours of training


Topics

Closing all digital divides | Capacity development | Artificial intelligence


All agree on the importance of gender inclusion in AI, but differ on approach – Kirthiga emphasizes mentorship and giving back, Lakshmi focuses on building inclusive systems from the start, while Radha advocates for normalizing gender parity as standard business practice

Speakers

– Kirthiga Reddy
– Lakshmi Pratury
– Radha Basu

Arguments

Being often the only woman in the room creates a position of privilege and responsibility to give back and support others


AI revolution presents an opportunity to build inclusively from the beginning, unlike previous revolutions that created problems we had to fix later


Running a company with 53% women should be normal since the world is about 50-50, and AI technology should reflect this balance


Topics

Closing all digital divides | Human rights and the ethical dimensions of the information society


All agree that children need fundamental life skills beyond technical knowledge, but emphasize different aspects – Anurag focuses on emotional grounding through traditional concepts, Speaker 1 emphasizes resilience and failure management, while Radha highlights curiosity and critical thinking

Speakers

– Anurag Hoon
– Speaker 1
– Radha Basu

Arguments

Teaching five senses and nine emotions helps children stay grounded while navigating technological change


Children need to learn resilience, how to fail, and that life can be unfair while still learning to survive and thrive


Future requires curious learners who can think critically and adapt, as what students learn changes rapidly


Topics

Capacity development | Social and economic development


Similar viewpoints

Both speakers advocate for embracing risk-taking and recognizing that innovation and talent exist broadly across society, not just among well-known figures or established institutions

Speakers

– Kirthiga Reddy
– Lakshmi Pratury

Arguments

Taking risks and not being afraid to start over is essential for growth – if a new trajectory gets you further ahead, it’s worth starting over completely


Innovation is happening everywhere, not just among famous people – the goal is to find amazing talent doing amazing work and help them tell their stories


Topics

Capacity development | Social and economic development


Both speakers demonstrate through concrete examples and commitments that AI training can successfully reach and benefit underserved populations at scale

Speakers

– Radha Basu
– Mihir Shukla

Arguments

72% of workers come from low-income backgrounds and rural areas, proving it’s possible to skill people directly in AI without prior digital training


Partnership announced to train one million women and youth in AI and automation over the next five years


Topics

Closing all digital divides | Capacity development | Artificial intelligence


Both speakers see the future as requiring interdisciplinary approaches where human value lies in creativity, emotional intelligence, and the ability to formulate good questions rather than providing factual answers

Speakers

– Mihir Shukla
– Anurag Hoon

Arguments

Future careers will combine multiple disciplines, and the power lies in asking the right questions rather than just knowing answers


Arts and creativity are essential for developing emotional intelligence (EQ) as AI handles more analytical tasks


Topics

Capacity development | Social and economic development | Artificial intelligence


Takeaways

Key takeaways

AI revolution presents a unique opportunity to build inclusively from the beginning, unlike previous technological revolutions that created problems requiring later fixes


Success in AI lies in application rather than just model development – focus should be on applied AI across all economic sectors


AI can democratize access to high-skilled work, with people gaining valuable skills in weeks rather than years through new training approaches


The future workforce requires curious learners who can combine multiple disciplines and ask the right questions, as AI handles analytical tasks


Building resilient, inclusive AI communities requires representation (50-50 gender balance should be normal) and supporting people from diverse backgrounds


AI scaling depends on the nexus of three components: technology/models, infrastructure, and human intelligence working together


Children need to develop emotional intelligence, resilience, and curiosity while learning to coexist with AI technology


Arts and creativity become more important as AI handles analytical work, making emotional intelligence (EQ) a key differentiator


Resolutions and action items

Partnership announced between AI Kiran and Automation Anywhere to train one million women and youth in AI and automation over the next five years


AI Kiran to continue growing its community from 10,000 to potentially millions of women in AI


Sharing of the list of five senses and nine emotions framework with the AI Kiran community for child development


Continued expansion of AI centers of excellence in non-metro cities across India (Calcutta, Vizag, Coimbatore, Hubli, Shillong)


Focus on applied AI development in India’s 18 different industrial hubs to create global competitiveness


Unresolved issues

How to effectively bridge the digital gap for people who need basic technology training before AI training


Building trust and provenance in AI-generated information when people increasingly trust ChatGPT over human answers


Managing the overwhelming number of AI platforms and learning paths – guidance needed on what to learn first and next


Protecting children from AI-related harms while giving them access to AI’s power and benefits


Fundamental disruption needed in K-12 and higher education systems to prepare students for an AI-driven world


How to compress wisdom development cycles for youth in an information-saturated age


Addressing the panic and confusion people feel about rapid AI changes and multiple emerging platforms


Suggested compromises

Skip some traditional digital skills training and move directly to AI-friendly interfaces that use natural conversation


Focus on building what works in AI rather than dwelling on potential problems, while maintaining awareness of risks


Combine human intelligence with artificial intelligence in a coexistence model rather than viewing them as competing forces


Balance giving children access to AI tools while teaching them resilience and emotional intelligence through arts and nature


Invest in both economic growth through AI and inclusion of previously excluded populations


Start learning AI immediately with available tools rather than waiting for perfect conditions or complete understanding


Thought provoking comments

What would you do if you weren’t afraid? And it’s about, you know, taking risks and not being afraid to start over again… if the new trajectory gets you further ahead, you know, by the way, and even if you fail at that, it’s better to shoot for the stars. And miss versus doing a part that feels achievable, but there’s not the stretch in it.

Speaker

Kirthiga Reddy


Reason

This comment reframes failure and risk-taking as essential elements of growth rather than obstacles to avoid. It challenges the conventional wisdom of playing it safe and introduces a philosophical framework that permeates the entire discussion about scaling human potential in the AI era.


Impact

This set the tone for the entire panel discussion, establishing a theme of bold transformation that other panelists built upon. It created permission for speakers to discuss radical changes and ambitious visions throughout the conversation.


When we started, if you went to chat GPT and said, can you tell me about 100 women in AI in India, it would tell you 10 women… So right there, we added a zero. Now it’s an incredible community of, you know, 10,000 women… we have already added two zeros to the first number that ChatGPT had.

Speaker

Kirthiga Reddy


Reason

This comment brilliantly illustrates how AI systems can perpetuate invisibility and bias, while simultaneously showing how human action can correct these gaps. It demonstrates the recursive relationship between AI training data and real-world representation.


Impact

This shifted the conversation from abstract discussions about AI potential to concrete examples of how human agency can shape AI outcomes. It provided a tangible success story that grounded the discussion in practical action.


It’s 53% women. And I’ll say one thing. I believe in this, really. If anybody asks you, how do you run a company with 50-50 women, look them straight in the eye and say, have you seen the world lately? It’s about 50-50. And there should be no reason why AI technology cannot be 50-50.

Speaker

Radha Basu


Reason

This comment cuts through complex diversity arguments with simple, irrefutable logic. It reframes gender parity from a ‘special initiative’ to basic demographic representation, challenging the assumption that tech naturally skews male.


Impact

This comment energized the discussion and provided a powerful counter-narrative to typical tech industry demographics. It influenced subsequent speakers to focus on inclusion as a natural state rather than an aspiration.


Change inherently is always personal. And what happens when you see either people who are super positive or super negative about something, it’s because they’re internalizing what they think it means to them… it’s about a model of coexistence as this develops that has to be evolved.

Speaker

Speaker 1 (Ashna)


Reason

This insight recognizes that technological adoption is fundamentally about human psychology and personal impact, not just technical capabilities. It shifts focus from the technology itself to how individuals process and adapt to change.


Impact

This comment redirected the conversation toward the human element of AI transformation, influencing subsequent discussions about education, parenting, and individual adaptation strategies.


The future is that there are no worker bees. There are only queen bees… if everybody had that mindset, amazing things are possible.

Speaker

Mihir Shukla (quoting his daughter)


Reason

This metaphor from a young person captures a fundamental shift in how work and value creation might evolve in an AI world. It suggests empowerment and leadership becoming universal rather than hierarchical.


Impact

This comment became a memorable anchor point that influenced the discussion about preparing youth for the future, shifting focus from job displacement fears to empowerment possibilities.


It is so much easier to take somebody from industry and train them in AI because they have to unlearn first than to take a young person out of some place in Odisha who comes from a second tier or even villages and be able to skill them in AI… it’s the nexus of AI technology and that human.

Speaker

Radha Basu


Reason

This counterintuitive insight challenges assumptions about who can succeed in AI, suggesting that lack of prior experience can be an advantage rather than a disadvantage. It reframes ‘disadvantaged’ populations as having unique advantages.


Impact

This comment fundamentally shifted the conversation about AI education and access, influencing discussions about grassroots training and challenging conventional wisdom about prerequisites for AI literacy.


AI is beyond all the parents… whatever I learned last year I wanted to go into computer science at Stanford it was my biggest dream hey that’s not going to get me a job and I have to do different things… being a curious learner because… You keep pinging it to make it better, right?

Speaker

Radha Basu (quoting her nephew)


Reason

This perspective from a young person reveals how rapidly AI is changing career landscapes and highlights the inadequacy of traditional educational planning. It emphasizes curiosity and adaptability over fixed knowledge.


Impact

This comment influenced the entire discussion about education and parenting, shifting focus from teaching specific skills to fostering adaptability and curiosity as meta-skills for an uncertain future.


Overall assessment

These key comments fundamentally shaped the discussion by establishing several important themes: reframing failure as opportunity, demonstrating concrete action over abstract ideals, challenging demographic assumptions in tech, emphasizing the personal nature of technological change, and highlighting the advantages of fresh perspectives over established expertise. The comments created a progression from philosophical frameworks to practical examples to future-oriented thinking. Most significantly, they shifted the conversation from typical ‘AI will change everything’ rhetoric to nuanced discussions about human agency, inclusion, and adaptation strategies. The interplay between established leaders and youth perspectives created a dynamic that emphasized both wisdom and fresh thinking, ultimately producing a more holistic view of scaling human potential in the AI era.


Follow-up questions

How do we build trust and provenance in AI-generated content when people are increasingly trusting ChatGPT answers over human-curated information?

Speaker

Bina (AI Kiran member, ServiceNow)


Explanation

This addresses a critical challenge in AI adoption where traditional human curation of internet content is being replaced by AI systems, raising questions about reliability and verification of information sources.


How do we solve the digital gap when training people in AI who still need basic technology education first?

Speaker

Unnamed audience member doing grassroots AI training


Explanation

This highlights the challenge of AI education in communities where basic digital literacy is still lacking, requiring a foundational approach before AI concepts can be effectively taught.


How do we crunch the wisdom cycle for youth in the information age – building wisdom to infer, ask right questions, and interpret beyond just facts and figures?

Speaker

Unnamed audience member


Explanation

This addresses the need to develop critical thinking and wisdom in young people who have access to vast information but may lack the experience to properly interpret and apply it meaningfully.


What specific guardrails do we need to protect children from AI-amplified harms while still giving them access to AI’s power?

Speaker

Hemendra (IIM Udaipur professor)


Explanation

This builds on concerns about social media harms and the need for proactive protection measures as AI amplifies both benefits and potential negative impacts on young users.


How do we fundamentally disrupt K-12 and higher education systems to support the AI transformation, moving beyond traditional exam-college-company pathways?

Speaker

Unnamed AI company founder working with higher education


Explanation

This questions whether current educational structures are adequate for preparing students for an AI-driven future where traditional learning and career paths may be obsolete.


What is the strategic framework for individuals to decide what AI skills to learn first and in what sequence, given the overwhelming number of platforms and methods available?

Speaker

Anjali (Tech Mahindra)


Explanation

This addresses the practical challenge of navigating the rapidly expanding AI learning landscape and creating a structured approach to skill development.


What are the five senses and nine emotions (Navras) framework that should be shared with the AI Kiran community for child development?

Speaker

Implied by Ashna’s response to Anurag’s parenting approach


Explanation

This would provide a concrete framework for parents trying to balance human development with AI integration in their children’s lives.


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