Powering AI Global Leaders Session AI Impact Summit India
20 Feb 2026 16:00h - 17:00h
Powering AI Global Leaders Session AI Impact Summit India
Summary
The summit opened with acknowledgments of partners and a preview of a video on AI-driven talent matching before introducing Chris Lehane’s talk on OpenAI’s work in India [1-10]. OpenAI’s AI recruiter, currently supporting English and Hindi, was presented as a tool that could later expand to provide financial, educational, and governmental services [11-13]. Lehane thanked the organizers, noted the presence of the Prime Minister and CEO Sam Altman, and highlighted their shared emphasis on “democratic AI” [27-33].
He explained the “capability gap,” where rapid AI acceleration creates a divide between a small group of power users and the broader population [34-40]. Research shows power users generate roughly seven times the economic value of non-users, underscoring the urgency to close this gap [41-48]. Lehane argued that education is the primary means to bridge the gap, focusing on three pillars: access, literacy, and agency [53-55].
He emphasized that widespread free access in India-hundreds of millions of users and an affordable paid tier-provides the foundation for inclusive participation [56-69]. Literacy, he said, involves not only basic reading and arithmetic but also hands-on AI use, encouraging experimentation even in unconventional domains such as astrology and sports betting [70-78]. The most challenging pillar, agency, requires individuals to view AI as a tool for owning and monetizing their own labor rather than merely selling it [80-86][101-104].
Drawing a historical parallel, Lehane compared AI to the printing press, noting that in Europe the technology spurred democratization of knowledge while in China it was suppressed, foreshadowing a choice between democratic and autocratic AI [112-124]. He asserted that India, as the world’s largest democracy with massive AI adoption, is uniquely positioned to shape a democratic AI future [124]. OpenAI therefore views India not just as a market but as a strategic partner essential to fulfilling its mission of building AI that benefits all humanity [125-126].
The session concluded by thanking attendees and emphasizing the significance of this moment for both India and the global AI landscape [129-132][131-132].
Keypoints
– Democratizing AI requires three pillars: access, literacy, and agency.
Chris stresses that widespread, low-cost access (free tools and a $3.99 /month model) is the foundation for participation in the AI-driven economy [55-64][57-69]. He then outlines the need for AI literacy-people must start using the tools, even in unconventional ways, to become proficient [70-77]. Finally, he highlights “agency” as the hardest piece: users must intentionally employ AI as a productive partner rather than a shortcut [80-86].
– A “capability gap” is emerging, where power users generate far greater economic value.
The rapid, recursive acceleration of AI creates a subset of “power users” who act as assistants, coaches, and multipliers, delivering roughly a 7× productivity boost compared with non-power users [34-49][44-48]. Closing this gap is presented as essential to ensure the benefits of AI are shared across society.
– Education must evolve to bridge the gap, drawing on historical analogies.
Chris likens AI to a general-purpose technology comparable to the printing press, noting how divergent outcomes in Europe (democratization of knowledge) versus China (authoritarian control) illustrate the stakes of today’s AI rollout [112-124]. He argues that modern education-originally designed for the industrial age-needs to be re-oriented to give students agency over AI, turning labor into owned, monetizable output [86-94][95-103].
– India is positioned as a strategic partner and global leader in AI democratization.
With hundreds of millions of regular users and an affordable pricing model, India offers a unique testbed for scaling democratic AI [57-69][106-108]. The speaker stresses that India’s role goes beyond being a customer; it is a partner crucial to fulfilling OpenAI’s mission of “building AI that benefits all of humanity” [124-128].
– Future AI applications extend beyond recruitment to broader services.
The brief remarks from the second speaker note that today’s AI recruiter supports English and Hindi and will soon enable access to financial, educational, and governmental services [11-14].
Overall purpose/goal:
The discussion aims to articulate the urgency of making AI truly democratic by addressing the capability gap, redefining education, and leveraging India’s massive user base, thereby aligning OpenAI’s mission with global societal benefit.
Overall tone:
The conversation begins with celebratory gratitude and applause, shifts to an analytical and urgent tone as it dissects the capability gap and educational challenges, and moves toward an optimistic, forward-looking stance emphasizing India’s pivotal role. Throughout, the tone remains constructive and hopeful, ending with a courteous thank-you and a sense of partnership.
Speakers
– Speaker 1
– Role/Title: Event moderator / host (appears to introduce speakers and wrap up the session)[S7][S9]
– Speaker 2
– Role/Title: Moderator / chair (appears to moderate the discussion)[S1][S2]
– Affiliation: Affiliation 2 (as indicated in source)[S2]
– Chris Lehane
– Title: Chief Global Affairs Officer, OpenAI[S4]
– Title: Vice President of Public Works, OpenAI (newly appointed)[S5]
– Role: Co-moderator for the session[S6]
Additional speakers:
– Ronnie – Chief Economist and Academic Professor at Duke University (referenced in the transcript)
– Sam Altman – CEO and Co-founder of OpenAI (referenced in the transcript)
– Rupa – Participant who contributed to the discussion on literacy (referenced in the transcript)
– Rana – Participant who mentioned Codex, the developer tool (referenced in the transcript)
– Prime Minister of India – Delivered remarks at the summit (referenced in the transcript)
The summit opened with a brief ceremony in which the Chief Global Affairs Officer was introduced and partners were applauded [1-3]. The host then thanked the partners, announced a short bridging video that highlighted Vahan.ai’s work connecting talent with employment opportunities [7-9], and handed the session over to Chris Lehane for a presentation on OpenAI’s activities in India [10].
Speaker 2 introduced OpenAI’s AI recruiter, noting that it already supports English and Hindi and that additional Indian languages could be added “for each state in the next year or so” [11-12]. He framed the recruiter as a prototype for future AI-driven public services that might eventually provide access to finance, education and government resources that many people have never encountered [13-14].
Chris Lehane began by thanking the organizers, the audience, the OpenAI team, India’s Prime Minister and OpenAI CEO Sam Altman [19-30]. He praised the Prime Minister’s eloquent remarks about how important it is to get democratic AI right [27-30] and described the summit as a “unique and special moment” centred on the pursuit of a “democratic AI” that is widely accessible and responsibly governed [27-33].
Lehane then explained the capability gap, emphasizing the recursive acceleration of AI that is widening the divide between a small cohort of “power users” and the broader population [34-36]. Research he cited shows that power users generate roughly a 7× economic impact compared with non-power users, whether in corporate settings or as self-employed individuals [44-48]. He warned that without closing this gap, AI’s benefits will accrue only to a privileged minority [49].
Education, he argued, is the historic passport for closing such gaps. He cited Ronnie, a chief economist and Duke professor, as an example of academia identifying and addressing capability disparities [50-53]. From this perspective, three pillars are required for AI democratization: access, literacy and agency [53-55].
The access pillar rests on the availability of free tools and an affordable paid tier. In India, a third of the population uses OpenAI’s models regularly [57-58], and hundreds of millions of users engage with the free service [57-69]. The subscription costs about $3.99 per month [65-68], a low-cost model that Lehane repeatedly emphasized as the foundation for mass participation in the emerging AI-driven economy [57-62].
The literacy pillar goes beyond basic reading, writing and arithmetic to include hands-on experience with AI. Lehane urged people to “start using the tools” in any form-whether for astrology, sports betting or other experiments-because repeated use rapidly builds competence [70-78]. He also referenced Rupa’s point about literacy, underscoring the need for practical experimentation [70-71].
The agency pillar is described as the most challenging. Lehane contended that AI is a general-purpose technology that can amplify anyone’s ability to think, learn, create and build, but only if users deliberately employ it as a partner rather than a shortcut [80-86]. He linked agency to a broader re-imagining of the social contract: by using AI, individuals can “own their labour” and capture its economic value, reshaping the historic tension between labour and capital [94-103]. This shift, he argued, requires a new educational ethos that moves beyond the assembly-line mindset of the U.S. industrial-age system [97-101].
To illustrate the stakes, Lehane invoked the printing press as a historical analogue. He contrasted Europe’s fragmented political landscape, which allowed the press to democratize knowledge and fuel the Renaissance, with China’s authoritarian suppression of the same technology [112-124]. He argued that if the world’s largest democracy-India-can democratize AI, it will set a precedent for the rest of the world [108-124].
Consequently, OpenAI regards India as a strategic partner in fulfilling its mission to build AI that benefits all of humanity. He thanked the audience and reiterated that OpenAI sees India as a strategic partner in delivering on that mission [108-124].
While all speakers agreed on the need for broad AI access, they differed in emphasis. Speaker 2 focused on expanding multilingual support as a primary lever for democratization, suggesting future language rollout rather than guaranteeing a schedule [11-12]. Lehane, by contrast, placed universal free access, literacy and agency at the core of his framework [55-64][80-86]. Both, however, concurred that AI can generate substantial economic value and that education is the key mechanism for narrowing the capability gap [44-48][52-53].
Lehane’s remarks were punctuated by several thought-provoking comments: the concrete 7× productivity metric as a warning about widening inequality [44-48]; the three-pillar model that highlights agency as an often-overlooked component [80-86]; the printing-press analogy that frames AI’s geopolitical trajectory [112-124]; and a challenge to the legacy of the U.S. education system, urging curricula that enable students to “own their labour” [97-103]. These points shifted the discussion from a simple showcase of tools to a deeper examination of equity, empowerment and global governance.
In summary, the session progressed logically from an opening acknowledgement of partnerships, through a description of OpenAI’s multilingual AI recruiter, to a detailed analysis of the capability gap and the three-pillar strategy required to democratize AI. The historical analogy and the emphasis on India’s democratic context reinforced the view that the country can lead the world toward a democratic AI future. The talk concluded with gratitude to the audience and a reaffirmation of the collaborative spirit that will guide the next steps [129-132].
The Chief Global Affairs Officer to join us for this moment. Please give a big round of applause to all our partners. Thank you. Thank you so much. Thank you so much. Thank you for your partnership. Thank you. Thank you. Thanks. Next, we have a short video coming up bridging these two sessions. which is what we talked about in the first section with Ronnie and the experts over here about the economics of AI, employability, what we can do with students. There’s a company called Vahan .ai that has done some incredible work in this space to be able to connect talent together with jobs. We have a short video and right after that we’ll have Mr. Chris Lehane giving us a talk about what we do at OpenAI.
Thank you.
OpenAI is the main AI AI recruiter. Today AI AI recruiter supports English and Hindi, but we can have each state in the next year or so. So, we want to focus on today, but in the future we can use this technology to bring people access to financial services or to educational opportunities or even government services that they haven’t heard of. So, there are a lot more that this type of unlock will help us in the future.
Over to you, Chris.
Thank you, thank you. Thank you everyone. Thanks for those who’ve hung out for a little bit longer. I know I am standing between you and probably dinner, and given how good the food here is in India, I am very cognizant that I should be pretty quick because I don’t want to stand in your way. First of all, great panel. It was awesome just to hear those different thoughts and perspectives. And Ronnie, who I think is one of the most excited people here in Delhi for this Impact Summit, your parents would be very proud of you in all seriousness. They were born here, they came to the U .S., and then to have their son coming and doing an event like this is a tremendous story.
So thank you. And Ronnie, thank you for everything that you do at OpenAI. And I really want to thank the OpenAI team that has helped put this together and all the incredible work that’s been done over the course of this week. And really thank everyone here in the room for participating in this summit. It is really a unique and special moment in time here in India. You know, yesterday we all heard from the Prime Minister. We also heard from Sam Altman, our CEO and co -founder. And, you know, the commonality in what they talked about. It was really focused on this idea of democratic AI. I think the Prime Minister, not surprisingly, was incredibly eloquent in talking about just how important it is to get that right.
And Sam, I think, built on that in his remarks. And something that Ronnie mentioned, I think, deserves some unpacking because it’s directly related to this democratizing of AI concept. And Ronnie, you had touched on the capability gap. So let me just unpack that for a couple seconds because I do think it’s at the core of this concept of democratic AI. And so what we know from our research, and really the research that Ronnie and his team do, is that there’s something called this capability gap. And what that really means is the technology continues to accelerate. In fact, there’s a recursive nature to it right now. So that acceleration is potential. going to become even faster and faster.
And what we’re seeing is that there is a subset of users. Think of them as power users. And those power users who are using the technology, and Ronnie I think you did your survey of how people are using it. I’m not sure if the astrologist counts as a power user, but I think some of the other examples, we’re getting there and perhaps it does. But what we’re seeing from those power users, so not just those who are using it for sort of a more comprehensive search function, but they’re really using it as an assistant, as a coach, as a multiplier of their work, is they are effectively creating a 7x economic impact. So put that in really simplistic or reductionist terms.
If you’re at a company and you’re a power user of our tools or AI generally, you are likely delivering a 7x value vis -a -vis a non -power user for your employer. Or if you’re self -employed and using it yourself. And so I think we’re really at this moment in time and we need to begin thinking about how do we close that capability gap, right? Because there’s going to be a subset of folks who left to their own are going to do very well by this, but we need to be thinking about society as a whole as we go forward. You know, Ronnie, in addition to being a chief economist, is also an academic professor at Duke.
A number of the folks up here had academic backgrounds. And we do know that over the course of human history, education ends up being the passport to close these types of capability gaps. And I think as we think about the role of education going forward, there’s really three elements to it here. Some of them are touched on in the conversation. The first is access. I mean, access is core to democratizing AI. You know, here in India, we have a hundred million folks who use this on a regular basis. Think about a third of the population who use this on a regular basis. I mean, access is core to democratizing AI. I mean, access is core to democratizing AI.
I mean, access is core to democratizing AI. I mean, access is core to democratizing AI. I mean, access is core to democratizing I mean, access is core to democratizing AI. I mean, access is core to democratizing AI. And amongst the reasons why there’s so many people using it here in India, I mean, we have 800 million globally, is because the vast majority are able to access our tools for free. And even the pay version here in India Go is a relatively very affordable model. I think it’s about $3 .99 a month, if I’m remembering correctly, okay. And so that access piece is really important. You have to have access to this if you’re going to have any chance to participate in those economics.
The second piece, and I think Rupa hit on this, is literacy. And, you know, this is literacy in the sense of, you know, reading and writing and arithmetic and AI literacy. And it’s really start using the tools. I might get asked all the time at events like this and other events, you know, which did my kid major in college? Or what? Start. Start using the technology. Start playing with it. Using it for astrology. Astrology. I have friends who use it for sports betting. Just use it in any type, shape, way, or form that you can, because once you start to use it, you will actually become really, really, really good at it. And then the third piece, and the third piece, I think, is really the most challenging and what we all have to get right, is the agency piece.
This is a technology, and this is a sophisticated crowd. You all understand this. But this is a technology that at its core is a general purpose technology. So what are general purpose technologies? We’ve got Ronnie, who’s an economist, who will probably come kick me when I do this description of it. But these are transformational technologies that just change the ability of humans to produce. So if you think about it, humans have been around roughly 200 ,000 years. For the first 190 ,000 of those years, humans produced basically what they could eat. And there was sort of a direct one -to -one ratio. And then about 10 ,000 years ago, you started to get stuff like the wheel. and later on you got the domestication of animals, then the wheel, then you got steam power, and then you got combustion engine, your printing press, electricity, the transistor.
Each one of those drove productivity up higher and higher and drove human progress. This AI is an ultimate leveling tool. It scales the ability of any person, so long as they can talk, to be able to think, to learn, to create, to build, and to produce. But you have to take agents. You actually have to want to use it for those purposes. And one of the things that’s very much in my head, and I’m a lot more familiar with the U .S. public education system than certainly the Indian one, so what I’m going to talk about is a little bit more from a U .S. perspective, although I do think it translates. So in the U .S., the public education system that we currently have was really created at the early stages of the industrial age in the United States.
and it was basically designed to help teach folks to come in from rural areas where they had mostly been an agricultural economy and be able to work in factories so in the U .S. the time that school started sort of aligned with when factories opened the fact that you went from classroom to classroom was basically designed to teach you to work on an assembly line even the bells that you got to move you around was designed to start to get you to understand and think as if you were working in the factory there are also other pieces built in civics courses I’m old enough that we had home ec and wood shop and other types of things that basically taught you core skills to be able to work in a factory well as we enter into this intelligence age what is the version of that that is going to change how people think and understand it’s almost an ethos that we have to build you know Sam often talks about the fact that if you probably look at kids in the school right now about 20 % of those kids actually really do have agency.
They’re excited to learn this. Maybe the other 80 % see it as a really easy way to get their homework done. That’s an ethos that we need to change. We need to get to a place where closer to 100 % of those students are going to really think about this is a technology that can allow me to succeed. It can allow me to actually take my labor and not necessarily have to sell my labor or get paid for my labor, but I actually get to own my labor and make money off of my labor. If you really think about how the social contract has generally worked, it has always been this calibration, maybe a fight between labor and capital.
This technology allows folks who are using their labor to be able to actually own it and participate in it in a fundamentally different way. For us, thinking about that agency piece is really critical. I’ll end this by just saying I think India is in a unique, unique moment to lead on this. The number of folks who are already using it. year. I think, Rana, you may have mentioned that Codex, which is our developer tool, this is the place in the world where it’s growing the fastest. And I’m going to end with a little bit of a historic analogy. I get to sometimes play a technologist on stages like this, and even a little bit of an economist today.
But I was a history major in college, so I get to play amateur historian, emphasis on amateur. Everyone has their own favorite historical analogy for this technology, for AI. The one that I’ve really been thinking about a lot lately, and none of these are perfect. They’re not exact replications. It’s going to rhyme more than repeat. But the one that’s very much in my head these days is the printing press. And I will sort of share two different parts of the world when the printing press came out. So the printing press developed late 1400s. Most of the world was more or less in a very similar economic place. So the printing press was a very similar economic place.
So the printing press was a very similar economic place. So the printing press was a very similar economic place. So the printing press was a very similar economic place. So the printing press was a very similar economic place. but two places went in very different directions on this one was europe and the other was china in europe because there was a little bit of a baseline of actual literacy from the catholic church and moreover because it was a fragmented continent with different countries that fragmentation really allowed people to use the printing press to spread ideas no one government actually controlled but that was being produced by the printing press and as a result you had the democratization of knowledge and ideas and thinking in a way that humans had never experienced at scale up to that moment in time and there’s a direct through line in europe from the printing press to the democratization of knowledge to the age of discovery the age of science enlightenment to reformation and the economic uplift of europe the other extreme was what took place in china which is under the dynasty at that time there was a real concern that the printing press was going to in fact allow knowledge to be spread and the spreading of that knowledge would potentially generate a challenge to the authoritarian government in place and so as we sit here at this moment in time right there is going to be a huge question as to whether the world is built out on democratic AI or autocratic AI a centralized version of it and India is gonna have the dispositive voice on how that plays out this is the world’s largest democracy if the world’s largest democracy is able to democratize AI here that means we’re going to be democratizing AI around the world so this is a moment in time for this incredible country that’s going to be playing a leading role not just for the people here as important as that is but for the entire world and the entire world and the entire world but for people around the world and so we feel incredibly privileged to be able to be here in Delhi in India at this moment.
It’s amongst the reasons why we don’t see India as a customer. We see India as a strategic partner, and not just a strategic partner for us as a business, but for a strategic partner for us to be able to deliver on our company’s mission, which is building AI that benefits all of humanity. Thank you very much for being here. It’s been an incredible week. Talk to you guys soon. Thank you.
That’s a wrap. Thank you. Thank you.
“Chris Lehane presented on OpenAI’s activities in India at the summit”
The knowledge base lists Chris Lehane as a speaker for the AI Impact Summit India, confirming his role in presenting OpenAI-related content at the event [S17].
“OpenAI’s AI recruiter currently supports English and Hindi and plans to add additional Indian languages for each state within the next year”
A separate source notes ongoing efforts in India to expand language support (e.g., Bhashini adding 11 languages with state collaboration), providing context that language-addition initiatives are underway, though it does not specifically reference OpenAI’s recruiter [S89].
“Research cited by Lehane shows that power users generate roughly a 7× economic impact compared with non‑power users”
The knowledge base confirms the existence of a distinct “power-user” segment and discusses disparities between power users and average users, but it does not provide the specific 7× impact figure, offering contextual support for the concept of a capability gap [S99].
“Ronnie, a chief economist and Duke professor, is cited as an example of academia identifying and addressing capability disparities”
The source mentions Ronnie conducting a survey on how people use AI, confirming his involvement in studying capability disparities [S99].
The speakers converge on three core ideas: (1) AI must be broadly accessible through free/low‑cost tools and multilingual support; (2) AI can generate substantial economic value, but a capability gap exists that needs to be closed; (3) education, AI literacy and personal agency are essential to ensure that the benefits of AI are widely shared. These points cut across access, economic inclusion, and capacity‑building themes.
High – there is strong alignment among the speakers on the necessity of access, the economic promise of AI, and the role of education/agency. This consensus suggests a shared commitment to policies that lower barriers, invest in AI literacy, and design inclusive AI ecosystems, reinforcing the agenda of democratizing AI at both national (India) and global levels.
The discussion shows broad consensus on the need to democratize AI and use it to improve economic inclusion. The main points of contention are strategic – whether to prioritize universal free access, literacy and agency (Chris Lehane) or to focus first on expanding multilingual capabilities and future service integrations (Speaker 2). A secondary tension concerns the role of education versus technological rollout as the primary lever for closing the capability gap.
Low to moderate. The speakers are aligned on the end goal (democratized, inclusive AI) but diverge on the immediate policy and implementation priorities. This suggests that collaborative frameworks will need to reconcile access‑cost models with language‑expansion roadmaps and embed education components to achieve cohesive progress.
Chris Lehane’s remarks served as the engine of the discussion, repeatedly introducing new lenses—economic disparity, a three‑pillar framework, historical analogies, education reform, labor‑capital rebalancing, and geopolitical leadership—that redirected the conversation from a simple showcase of AI tools to a multifaceted debate about equity, agency, and global governance. Each pivotal comment opened a new thematic branch, prompting participants to consider not just how AI works, but who benefits, how societies must adapt, and what role India can play in shaping a democratic AI future.
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.
Related event
