Panel Discussion Next Generation of Techies _ India AI Impact Summit

20 Feb 2026 16:00h - 17:00h

Session at a glance

Summary

This panel discussion at a tech summit focused on how entrepreneurship is evolving in the age of artificial intelligence, featuring three entrepreneurs at different stages: Anirudh Suri (venture capitalist and moderator), Malhar Bhide (young co-founder of AI biotech startup Origin Bio), Navrina Singh (founder of AI governance platform Credo AI), and Arvind Jain (founder of enterprise AI company Glean). The conversation explored how the current AI wave differs from previous technology waves like consumer internet and mobile, with panelists noting that AI enables much leaner startups with smaller teams and lower capital requirements due to AI’s ability to automate many traditional business functions.

A key theme emerged around the democratization of knowledge through AI, allowing entrepreneurs to work across disciplines they haven’t formally studied, as exemplified by Malhar’s biology-focused startup despite having no formal biology background. The discussion highlighted how AI-first companies are fundamentally restructuring traditional organizational blueprints, with unclear roles for humans in many functions. The panelists emphasized that while AI makes it easier to build products quickly, the real competitive advantage lies in creating reliable, trustworthy AI systems that can operate within regulatory frameworks.

Navrina Singh stressed the growing importance of AI governance and policy compliance, arguing that successful AI companies must build trusted technology that works within regulatory constraints rather than just focusing on technological innovation. The conversation touched on whether traditional creative destruction principles will continue in the AI era, with panelists generally agreeing that innovation will still emerge from startups despite big tech companies’ advantages. The discussion concluded with audience questions about AI security, governance ROI, and entrepreneurial opportunities in emerging AI-related fields, reinforcing the theme that new technological challenges create new business opportunities.

Keypoints

Major Discussion Points:

– Evolution of AI-driven entrepreneurship compared to previous tech waves: The panelists discussed how AI entrepreneurship differs from the consumer internet wave, noting that while core entrepreneurial principles remain the same (finding business problems, building teams, having vision), AI enables much leaner startups with smaller teams and lower capital requirements due to AI’s ability to automate many tasks.

– The democratization of knowledge and cross-disciplinary innovation: The discussion highlighted how AI has made specialized knowledge more accessible, allowing entrepreneurs like Malhar to enter complex fields like biotechnology without formal training in that domain, using AI to accelerate learning and research across disciplines.

– AI governance, policy, and regulatory considerations: A significant portion focused on how AI entrepreneurs must now consider policy and regulatory risks as core business functions, not just peripheral concerns. The discussion covered the intersection of AI with government policy, the need for trusted and reliable AI systems, and how regulatory compliance is becoming a competitive moat.

– The role of research in AI startups: Unlike previous tech waves, current AI entrepreneurship requires deeper engagement with fundamental research, as companies like Origin Bio must train models from scratch and conduct original scientific research to create viable products.

– Creative destruction and competition in the AI era: The panel debated whether large tech companies will maintain dominance or if the traditional pattern of startups disrupting incumbents will continue, with most agreeing that AI actually empowers individual entrepreneurs and small teams to innovate more effectively.

Overall Purpose:

The discussion aimed to explore how entrepreneurship is evolving in the AI era, comparing it to previous technology waves and providing insights for current and aspiring entrepreneurs about the unique challenges and opportunities in AI-driven startups.

Overall Tone:

The tone was optimistic and encouraging throughout, with panelists expressing enthusiasm about AI’s democratizing effects on entrepreneurship. The conversation maintained a practical, educational focus while being accessible to the audience of entrepreneurs and students. The tone became slightly more interactive and urgent toward the end as audience questions were incorporated, but remained consistently positive about the opportunities AI presents for the next generation of entrepreneurs.

Speakers

Speakers from the provided list:

– Anirudh Suri – Runs a venture capital fund called India Internet Fund, author of “The Great Tech Game” book and podcast host focusing on the intersection of technology and geopolitics

– Malhar Bhide – Co-founder and Chief Technology Officer of Origin Bio, a Y Combinator startup using AI to make safer genetic medicines for diseases like cancer, college dropout

– Navrina Singh – Founder and CEO of Credo AI (an AI governance and trust management platform), has been advising the White House on AI policy for the past five years, works with governments globally on AI guardrails

– Arvind Jain – Founder and CEO of Glean, an enterprise AI company (about seven years old) that functions like Google or ChatGPT but inside companies, using both world knowledge and internal company data

– Audience – Multiple audience members who asked questions during the Q&A session

Additional speakers:

– Rahul – Mentioned as a 16-year-old speaker at the summit, one of the youngest speakers, was interviewed earlier by Anirudh Suri for a podcast

Full session report

This panel discussion at a technology summit explored how entrepreneurship is evolving in the artificial intelligence era, featuring three entrepreneurs at different stages of their journeys alongside venture capitalist and moderator Anirudh Suri, author of “The Great Tech Game” and partner at India Internet Fund. The conversation brought together Malhar Bhide, a young co-founder of AI biotech startup Origin Bio and UIUC dropout; Navrina Singh, founder of AI governance platform Credo AI with extensive White House policy advisory experience; and Arvind Jain, founder of enterprise AI company Glean. Together, they examined the fundamental shifts occurring in how startups are conceived, built, and scaled in the age of artificial intelligence.

The Transformation of Entrepreneurial Fundamentals

The discussion began with a comparison between the current AI wave and previous technology cycles, particularly the consumer internet boom. Arvind Jain emphasized that while core entrepreneurial principles remain unchanged—requiring ambition, risk-taking ability, and focus on solving genuine business problems—the AI wave introduces unprecedented organizational transformation. “But now with AI, everything changes. In fact, the role of human itself is unclear in what roles seem to exist,” Jain observed, highlighting how AI fundamentally disrupts traditional company blueprints.

This transformation manifests most clearly in the dramatic reduction of resources required to build viable products. The panelists agreed that AI enables significantly leaner startups, with entrepreneurs able to accomplish tasks that previously required large teams. Jain noted that founders now consistently evaluate whether machines can perform work before considering human hiring, creating what he termed an “AI-first mindset” that generates substantial operational efficiencies.

The Democratization of Knowledge and Cross-Disciplinary Innovation

Perhaps the most striking example of AI’s transformative impact came from Malhar Bhide’s personal experience. His five-person team at Origin Bio, which develops AI-driven genetic medicines, includes only one person with formal biology training—and that individual is not among the team’s graduates. “Because of how good AI has gotten, knowledge has gotten a lot more democratized,” Bhide explained, describing how AI tools enable entrepreneurs to rapidly acquire domain expertise and conduct sophisticated research across disciplines they’ve never formally studied.

This democratization extends to fundamental research capabilities. Bhide’s team trains AI models from scratch, conducts wet lab experiments, and engages in cutting-edge biological research despite lacking traditional credentials. They use AI to predict experimental outcomes for cost efficiency, optimize resource allocation, and accelerate the typically lengthy process of biological discovery. This represents a paradigm shift where intellectual curiosity and AI-augmented learning can substitute for years of formal education, though the panelists emphasized this still requires rigorous empirical validation.

AI Governance as Competitive Advantage

A significant portion of the discussion focused on the intersection of AI technology with policy and regulatory considerations. Navrina Singh argued that contrary to the perception that governance constrains innovation, AI governance creates competitive advantages and accelerates business value creation.

“The true moat that is happening for companies like Malhar is not just the technological innovation, because it is, you know, you’re able to do that much faster with a leaner team. But it is how do you do that consistently within the boundaries of the constraints and guidelines,” Singh explained. She argued that companies implementing robust AI governance can adopt third-party AI tools more rapidly, deploy products faster to customers, and build greater customer trust—all contributing directly to revenue growth.

The discussion revealed varying approaches to governance based on company size and market focus. While Arvind Jain acknowledged the importance of AI safety regulations for the industry overall, he noted that Glean focuses on showing “the full trail of where answers are coming from” as part of their safety approach. Malhar Bhide described how his team proactively studies AI safety research and implements guardrails to prevent misuse of their biological AI models, recognizing that regulatory compliance will be essential for eventual FDA approval.

New Security Challenges and Creative Destruction

The conversation highlighted how AI introduces fundamentally new security challenges. Jain identified emerging threats such as prompt injection attacks and the inherent challenge of managing AI’s probabilistic nature in enterprise environments. “AI is a very new technology, and it’s actually very gameable,” he observed, noting that new forms of attacks require entirely new defensive approaches.

Regarding whether traditional patterns of creative destruction will continue despite the massive resources of companies like Google and Microsoft, the panelists expressed optimism. Jain argued that innovation fundamentally originates from passionate individuals with bold ideas, regardless of corporate resources. “Most bold ideas actually come from a single person who wants to actually who’s passionate about solving a problem,” he noted.

Singh reframed the disruption conversation entirely, arguing that the relevant competition isn’t between big tech and startups, but between individuals who master AI tools and those who don’t. “You should not be worried about another person or even like AI taking your job. You should really be worried about a person who’s so good with AI actually replacing you,” she observed.

Cultural Perspectives and International Entrepreneurship

The discussion explored the unique position of Indian entrepreneurs in the global AI landscape. Both Jain and Bhide identified the experience of international relocation as developing valuable risk-taking capabilities that translate to entrepreneurial success. Bhide described how leaving familiar environments creates “some sort of tone and precedence in even the work you do at your startup in terms of just taking risks, the people you hire, the things you do.”

Jain attributed Indian entrepreneurial success to cultural factors, noting “there’s something about, like, in our culture, you know, and where we are as a nation, there is, you know, that drive, you know, that, you know, Indian people have.”

Audience Interaction and Practical Insights

The session included audience participation, with the moderator noting that most attendees were entrepreneurs or aspiring entrepreneurs. Three key questions emerged: finding problems to solve across disciplines, the evolution of AI security and cybersecurity, and the balance between ROI and governance.

In response to the governance question, Singh mentioned that Amazon was Credo AI’s first customer, illustrating how major companies are prioritizing AI governance. The discussion emphasized that while AI provides powerful new tools, success still requires fundamental entrepreneurial capabilities: identifying genuine market problems, building effective teams, and executing consistently over time.

Conclusion

This discussion illuminated how artificial intelligence is rewriting fundamental assumptions about how businesses are built and scaled. The panelists’ insights suggest that while the entrepreneurial spirit remains constant, the methods and requirements for startup success are undergoing significant transformation. The democratization of knowledge through AI, the emergence of governance as a competitive advantage, and the need for AI-first thinking represent important shifts that entrepreneurs must navigate.

The conversation reflected optimism that AI ultimately empowers individual entrepreneurs and small teams to compete more effectively than ever before, despite the new challenges and complexities it introduces. For the audience of entrepreneurs and aspiring founders, this discussion provided valuable insights into how the next generation of technology companies will emerge and compete in an AI-driven economy.

Session transcript

Anirudh Suri

Hi and welcome a very good afternoon to all of you thank you for staying on I know it’s the last day of a long productive summit and I think maybe not the last but the second last session maybe the third last session so thank you for being here I’m excited about this discussion that we’re going to have over the course of the next about half an hour or so, 35 minutes I’ll quickly introduce myself and then I’ll get our panelists to introduce themselves. We’re talking of course about the team of the next generation of tech entrepreneurs, tech founders, tech leaders in the world I’m Anirudh Suri, I run a venture capital fund called India Internet Fund and I’m Anirudh Suri And I’m also an author of a book called The Great Tech Game and a podcast by the same name that looks at the intersection of technology and geopolitics.

So I might bring in a little bit of geopolitics into our conversation, even though we’re talking mostly about tech founders. I’ll start with my left, Malhar. Today, I earlier had the opportunity to interview a very young panelist, a young speaker, Rahul. Who’s, I think, one of the youngest speakers at the summit. He’s 16. We did a podcast with him earlier in the afternoon. And so I’m especially delighted to have another young entrepreneur, college dropout. On my left, Malhar, if you can briefly introduce yourself.

Malhar Bhide

Yeah, thank you. Hi, I’m Malhar. I’m the co -founder and chief technology officer of Origin Bio. We’re a Y Combinator startup that is using AI to make safer genetic medicines for diseases. Like cancer.

Anirudh Suri

Thanks Malhar. Navrina

Navrina Singh

Absolutely not a college dropout not very young but I’m the founder and CEO of Credo AI we are an AI governance and trust management platform. For the past five years I’ve also been advising the White House on AI policy and work very closely with governments across the globe to really think about what AI guardrails should look like so to your point I think there is a very strong intersection of technology and policy happening right now excited to be here. Thank you

Anirudh Suri

Arvind, last but not least.

Arvind Jain

Thank you everyone my name is Arvind I’m the founder and CEO of Glean. Glean is an enterprise AI company about seven years old and think of us like Google or ChatGPD but inside your company. Glean is a place where you can go and ask any questions or give it some tasks and it uses all of the world’s knowledge just like how ChatGPD does it but also uses all of the internal company’s data and knowledge to help people with their questions or their tasks.

Anirudh Suri

Incredible. I think we have a great set of panelists across various sectors and I think various angles of the AI entrepreneurship market. We’re going to have a focus on how entrepreneurship is evolving, right, in this session. I’m sure in other sessions in this summit you’ve heard a lot about deep tech entrepreneurs. You’ve heard about probably all sorts of AI entrepreneurs. Of course, you’ve heard some of the largest AI companies take the stage, etc., including our very own Sarvam out of India. But now I want to focus on how entrepreneurship is evolving. Before I ask my first question to the panelists, can I have a quick show of hands? How many of you here are entrepreneurs?

Big chunk. Wannabe entrepreneurs? Ex -entrepreneurs? People who decided to… too much and went into the corporate world, let’s say? A few. Good. So I think the biggest number is still entrepreneurs and want to be entrepreneurs. I think for some of us who’ve seen the previous waves of technology, innovation, like for example, most recently the consumer internet wave and of course there have been multiple waves prior to that. And for those of you who are not familiar with the history of technological waves, I really encourage all of you to study the previous waves because often you get to learn a lot from how the earlier waves of technological innovation panned out, what kind of entrepreneurs, what kind of companies succeeded.

But a little bit with that historical context in mind, Arvind, I want to come to you first. Compared to the wave of the consumer internet where we saw forms like of course the Googles and the Facebooks of the world, the social media platforms, but then also the cab hailing platforms and a lot of marketplaces and consumer focused platforms emerged. We’ve seen a lot of and at least in India I know this is the period over the last 10 -15 years where entrepreneurship has become a buzzword, a desirable profession, you can drop out of college and your parents will still be happy about it right, compared to that wave how is today’s wave of AI driven entrepreneurship looking to you, could you draw out for the audience and for us how these two waves might be similar for entrepreneurs and how they might be different?

Arvind Jain

yeah, so well first, you know, I think whenever there’s a new technology wave, it creates a lot of opportunities for new companies to get started that’s the right time for somebody to jump into the entrepreneurial journey and, you know, we’ve been through many of these in the past two or three decades, you know, starting with like you said consumer internet to mobile to social and of course now AI, and each one of these opportunities are similar in some ways like, you know, to start a company to be successful at it you have to have, like, first of all, the ambition to make, you know, to make one, to make a company. You have to have that sort of, you know, real deep desire to, you know, to be able to take the risk and have the courage to actually go start something.

You have to follow the recipe, the right recipes, which is finding, you know, the right business problem to solve, like something that actually creates a lot of business value in there. And it’s not so much about the technology trend. It’s, you know, you can use the technology trend as a way to see if you can solve that business problem better, but it always starts with the right business problem. And then, of course, like, you know, do the rest of, you know, the entrepreneurship journey, which is about, you know, building a great team, having a clear vision, working hard, and making things happen, right? So those are, like, you know, those things don’t change, like, you know, through these ways.

But I think one thing that is actually very unique about… the new AI wave is that it’s not only, I think we always had a blueprint in terms of what an organization needs to look like. When we went from consumer internet to mobile as two big technology trends, the shape of your company, how you build it, what kind of people you need to hire, those things were not actually changing that much. The blueprint was clear that you’re going to hire some engineers, you’re going to have product managers, some sales people. But now with AI, everything changes. In fact, the role of human itself is unclear in what roles seem to exist. In some sense, there’s some more challenge for the AI entrepreneurs, but also more opportunity to actually not know the basics.

You can actually start and chart a journey without actually knowing how to start a company. Because reinventing yourself, thinking AI first, can actually help you build an organization, which is very unconventional. And maybe that is what is going to create big success for you in the future.

Anirudh Suri

Do we expect, Arvind, do we expect now startups to be even leaner given AI? Because I’ll give you a couple of examples. I have friends who are second -time, third -time entrepreneurs who successfully started, exited startups in the consumer internet wave. And now when they’re starting up in the AI era, they seem to have much lower number of team members to start with to get to that minimum viable product. They seem to have much fewer people doing the coding for them. Many, I would say, a significantly smaller requirement even for capital as a result, because of course in the early days sometimes employee costs or early employee costs are quite high. So do you expect this to continue, leaner startups?

Arvind Jain

Absolutely. In terms of the product and how far you can go with a very, very lean team, in fact a team of one person, is actually, it’s incredible. can actually build a lot with, you know, with that low cost. So certainly, like, you know, that is, that is a, I would say that, you know, but it’s not like, you know, ultimately when you build a company, you know, with scale, people actually are your asset. And at some point you’re going to start growing, but you can do a lot before. And I think one of the reasons why companies will be more lean now is because it’s always, you know, on an entrepreneur’s mind, you’re always thinking about, especially when you don’t have enough resources, enough funding, you’re always thinking about any piece of work that needs to happen.

You know, can the machine do it? Can AI do it? And so that sort of like that mindset of like, you know, like, hey, you know, I’m going to actually use AI to do most of my, most of the work that needs to get done in this company. It is actually, that is what is going to actually create significant efficiencies and a way to defeat like, you know, the incumbents.

Anirudh Suri

Great. Let me move to you, Malhar. We had the opportunity to speak a little bit prior to the session. Thank you very much. And you’ve, of course, started very recently. So you started technically your first startup, I’m assuming, first startup in the AI age. And so talk to us about how you are both viewing entrepreneurship today. Is it any different than maybe, I’m sure you might have read some books or met entrepreneurs who started earlier, venture capitalists who started companies earlier in the earlier waves. What’s your sense on the question I just asked Arvind as well? And secondly, how are you being AI first in the company that you’ve started? How are you leveraging AI, not just in the product itself, but even in the sort of organization, so to say?

Malhar Bhide

Yeah, I think one thing is that because of how good AI has gotten, knowledge has gotten a lot more democratized. And so there’s less of an excuse to. actually be able to work in different fields in this sort of cross -disciplinary nature. For context, my co -founder, Yash and I, we’ve never studied biology. Our team is five people. One of the people from our team has graduated. Only one person has studied biology and they’re not the same people, the same person either. So I think AI has actually allowed us to study a lot more, read a lot more papers, reach out to more scientists, learn from them, reach out to more customers, understand what exactly they want.

And we sort of use AI throughout. We do fundamental research. We train our own models from scratch. We do research in the wet lab. We’re starting a lot of wet lab work where we use AI to actually be able to predict the results of these wet lab experiments so that we can be cost efficient and ensure that we can work with a very limited budget. I think in some sense what hasn’t changed from when we grew up and we were watching movies like The Social Network is even then it felt like the people who succeeded the most were people who didn’t want permission. The example being Mark Zuckerberg. Even if you look at Jeff Bezos starting Amazon, it wasn’t like Barnes and Nobles that started a website to sell books.

I think with AI that sentiment hasn’t changed, but it’s probably easier to materialize and we’ve definitely gotten the benefit of that.

Anirudh Suri

Are you finding that research is more and more critical to your work compared to maybe earlier waves of startups?

Malhar Bhide

Yeah, I think it’s definitely critical. We’re working on using these AI models to actually design novel DNA sequences. They act as switches. This involves training the models from scratch, working with… public data, starting and warranting experiments to actually get our own proprietary private data. So the entire thing actually hedges on the product or our research producing an output that is biologically and scientifically viable. Even when we want to sell to biotech companies and pharma companies, or if we ever want to pursue our own therapeutic program, there are very rigorous requirements for the thing to actually work. An example, of course, being the FDA and needing clearance throughout, but even actually starting the clinical trial process is a lot of work and actually has a requirement of things actually working.

Anirudh Suri

I’m going to keep coming back to this theme of research for a reason, but before I do that, Navreena, I want to bring you in. We, of course, started off the conversation saying about talking about the intersection of AI with, I mentioned geopolitics, you mentioned policy, you said you’re working closely with folks in D.C., in the White House, and otherwise. This intersection of AI and policy. while for policy wonks like some of us I also work at a think tank as a non -resident but other than for us policy wonks who are looking at that intersection of AI and policy talk to us about why for let’s say a Malhar of an Arvind who are not necessarily spending that much time in DC and with folks in the White House and the policy crowd why is understanding or maybe dealing with this intersection of AI and policy and geopolitics why is it important?

Is it? And if it is, why?

Navrina Singh

Absolutely and just by way of background I’m an engineer by training, spent 20 years building AI products in research and development at companies like Qualcomm, Microsoft so it is I do want to ground it in why I think as a technology policy is becoming really critical is going back to something that Malhar said which is really interesting right? It’s when we think about the new AI wave, to actually go from zero to one right now is very, very easy. I think what really becomes really interesting is do you actually get that product to be extremely reliable? It’s robust. Can you explain those systems? There’s a combination of, I would say, scientific measurements to build that trust that needs to happen.

But there’s another thing that needs to happen, which is all about making sure these systems work within the regulatory domains that especially require a lot of risk assessment and management. And so what we are seeing is the true moat that is happening for companies like Malhar is not just the technological innovation, because it is, you know, you’re able to do that much faster with a leaner team. But it is how do you do that consistently within the boundaries of the constraints and guidelines? That’s one of the guardrails that a regulatory ecosystem causes. So just as an example, we work with Fortune 500 companies in financial services, in health care, and they are really finding that they’re depending a lot on third -party AI, like maybe tools like Glean.

But how does Glean work in the context if you are building, let’s say, a customer service chatbot? You want to make sure that the chatbot not only is aligning to your brand guidelines, but it is not toxic. It’s highly reliable. It’s doing the things it’s supposed to do. And if it is within the context of a regulatory sector, it is following, let’s say, HIPAA compliance, et cetera, right? So as you can imagine, now it’s not just about building technology, but it is about building trusted technology that can work in the context that we are talking about. And that’s the exciting intersection of, I would say, policy, governance, and tech that I see.

Anirudh Suri

If I can go a bit deeper on that. So has it changed? Because regulation, of course, regulatory risk, policy risk. all of these risks are always there. So Qualcomm, Microsoft, a Jio, a Tata, you take any large company anywhere in the world, of course they’ll have regulatory and policy risk people and of course that’s a big part of what they are tracking, etc. What has changed, if anything?

Navrina Singh

A lot has changed. And just I think another thing I want to ground us in is it’s not just about regulation. When you start thinking about AI risk, just because of the way these large language models are built, unless you ground it in real data, there are issues of hallucination. Do you actually, are you getting the right outputs? And can these systems be reliable? What kind of evaluation benchmarks do you have? Have you actually done the testing across your entire AI supply chain, etc.? So the thing is now it is not a static tech. It’s actually a very dynamic technology that when it starts to operate in e -commerce, either customer context, or it starts to operate in regulatory context, you have to prove that you can do it reliably.

So I would say that’s the biggest shift that we are seeing with AI and some of the applications.

Anirudh Suri

The other theme that I want to keep going on with this, Navreena, and Malhar, Arvind, please feel free to chime in, is I think at the core of our engagement with AI on the policy front is the fact that the technology is moving so fast and governments realizing the fact that AI as a technology has massive ramifications on people, on existing structures, are saying, hey, listen, let’s rein it in before it goes out of our control. So there’s also a question of control here. So governments want to control so that for both reasons. I think one is governments generally don’t like to give up control to the private sector too much anyways, anywhere around the world.

But the other bigger piece here is when the technology, as you were saying, Navreena, is moving so fast, ultimately if some massive harm happens to people, ultimately the governments and political leaders know that they’ll have to be accountable. So it seems to me that it’s the nature of AI as a technology also, and it’s massive ramifications it’s making. policy and geopolitics risk a big part of what entrepreneurs have to keep in mind. The question I have for you though is has this become a function that every team has to have? So any startup has to have a CTO, has to have a CEO, has to have maybe a CFO and then product manager, etc. Is this becoming a role that is critical?

Malhar, do you have someone looking at this? Arvind, do you have people? Of course you’re a larger company. So let me start with Malhar. Do you have someone looking at this kind of risk?

Malhar Bhide

I think we do have the benefit of being a smaller company that’s not entirely putting things out for public use where they can be harmful until we’ve gone through all of the regulatory requirements and until we have tested things out in a setting where it is safe. But I think from a research perspective people who are working on AI biology models such as us they work a lot on ensuring these models are safe whether it comes to other people being able to design dangerous pathogens and they’re not going to be able to be able to So we very actively in our entire team keep up with that research. We study that research. Everyone on our team is technical.

We study how they actually enforce those guardrails. So for when we actually need to start making things and actually turn them into products, we are actually able to implement that.

Arvind Jain

Yeah, so first, like, you know, so we are enterprise focused. And in that sense, like, you know, users of our product, they come to Glean and they ask questions which are serious in nature. It defines, like, you know, what work they’re going to do, what decisions they’re going to make. So first of all, you have to be absolutely sure that even though the core foundation of the AI technology is, you know, it’s a stochastic, you know, modeling, it can make mistakes, it’s probabilistic. You have to sort of work on top of that and ensure that you can actually deliver precise and accurate results. And like, you know, refrain from answering questions or doing tasks if you’re not sure.

So so we like it’s a big part of like our product experience is how do you actually use a safely and securely? How do you sort of, you know, do that constant sort of judgment and evaluation of the work that it produces? And do fact checking so that ultimately, you know, not only are you delivering the right answers or task execution, but you’re actually showing the full trail of like, you know, where the answers are coming from, what are authoritative information is being used that is human generated. So so that is very core to just like in terms of, you know, what product experiences that we deliver. But I think you’re also talking about the question of like is like how important it is to think about policy, to think about like.

You know. like setting, working with governments and actually ensuring that, you know, the right regulations and laws are in place. For us, like, you know, as an enterprise company, you know, that, you know, we don’t actually think a whole lot about that. But it is important to sort of have, you know, these rules and regulations in place because otherwise AI can actually do significant damage, you know, in the industry.

Anirudh Suri

Great. The other dynamic I now want to move on to is, you know, the tech industry, as I think I’m sure all of us have seen, is in many ways, tech and entrepreneurship is defined by this idea of creative destruction. Large companies come as startups. They become big. By the time they get big, there’s a whole new wave of tech coming in and then a whole new set of startups come in and disrupt the incumbents. We’ve seen that again if you go into history, time after time, wave after wave, that’s happening. So my question to all of you. is that principle of creative destruction going to continue with AI? Or are we going to see that the big companies of today, the big tech firms of today, with the amount of capital they have, the amount of talent that they can hire with the kind of balance sheets that they have, the global scope of these companies, et cetera, their ability to shape policy, right?

Is this wave of big tech firms different? Or can we expect that the principle of creative destruction of them getting disrupted sooner than later is likely to continue? I’ll start off maybe, Arvind, with you, and then I’ll come to Naveen and Mahal.

Arvind Jain

Yeah, well, I mean, I think this creative destruction or disruption, rather, you know, it happens, and like always, you will see that, you know, over the last 20 years, companies like Google, you know, Microsoft, you know, these are big… giants and they have all the resources in the world and all the policy making power but yet when you think about innovation that happens in the tech industry often it actually happens outside of those companies and that’s because I think the spirit of entrepreneurism is actually alive, it’s an innate human thing and most bold ideas actually come from a single person who wants to actually who’s passionate about solving a problem and so I don’t think AI is going to actually change that in fact if there’s any indications AI is actually going to make it even more, it’s going to make it easier for people to actually create really interesting products and to serve large players because now there’s more power in their hands you don’t even need to be an engineer, you don’t need to be an AI scientist to actually use these amazing technologies and build and sort of turn your ideas into real products with very few reasons.

resources. So what I expect to see happen is that more and more innovation that is going to happen again in startup land. But ultimately, of course, I think the larger companies are well -established, they have large customer bases, so the model in the industry tends to be that new products are always, innovation comes from startups, but then innovation scales at larger companies.

Anirudh Suri

Malhar, I’m going to come to Navrina in a second, but Malhar, I want to ask you a slightly different question. Navina, did you want to add to that?

Navrina Singh

You should not be worried about another person or even like AI taking your job. You should really be worried about a person who’s so good with AI actually replacing you. So I think so I have started to think about disruption rather than like in context of big tech or startups like individuals. Right. What what are creators and entrepreneurs going to create just when they can unlearn very fast rather than, you know, we don’t have a playbook right now for how you should be succeeding in the age of AI. So can, you know, new set of entrepreneurs use these tools, unlearn very fast old habits and be open and willing to try new ways of building faster?

I think that’s the construct that’s more healthier than thinking in the context of a company.

Anirudh Suri

Great. Thanks, Navina. Malhar, I want to come to you now and ask you, we’ve spoken about how companies or startups are changing both internally. They might look different, might be leaner. more research focused in the age of AI. You’ve spoken about the importance of policy and regulation and especially in the world of AI, but I want to ask you now about the entrepreneur themselves. Given we’re sitting in India, I’m going to ask you the question from the perspective of India. You’re an Indian entrepreneur, grew up in Bombay, working out in San Francisco, part of the Y Combinator batch, dropped out of UIUC. Tell me from your perspective, Malhar, what does the Indian entrepreneur building a startup in the US today look like?

Is it any different from earlier generations of Indian entrepreneurs in the US? One. And do you find some difference that you can maybe point to between an Indian entrepreneur who’s grown up in India and then is working there, starting up there in the US, versus someone who’s grown up in the US?

Malhar Bhide

Yeah, I think something that has been quite fruitful for me moving to America is that there’s an entire process of actually leaving where you’ve grown up and going somewhere and setting up things entirely new from there. And I think that sort of sets some sort of tone and precedence in even the work you do at your startup in terms of just taking risks, the people you hire, the things you do. I think in some sense that has perhaps stayed the same over multiple years because that procedure has not really gotten easier. It might be easy to get information, to book flights, to stay in contact with people, but the act itself has still been incredibly hard.

I think that is one big difference, and I think something that also probably contributes for more specifics is someone who’s grown up, let’s say, in America, is more aware of systems in America, how do you sell to people in America, what are talent distributions like in America, and how do you sell to people in America? And I think that’s something that has been quite fruitful for me moving to America. Thank you. someone like me who’s grown up in India. I think if we believe that India has a large role to play in things like drug discovery in the coming decade, I know a lot about how drug discovery works here, how hospitals work here, how data is collected, how many patients are treated, how diverse the patient body here is.

So I think there are those very specific advantages to it as well.

Anirudh Suri

If I go to Arvind to ask the same question, can I just see a quick show of hands? Anyone has questions or quick comments? I want to make the last few minutes interactive if you’d like. Any burning questions or comments in the audience? Okay. So while Arvind’s answering, just raise your hand so I have a sense of the room, and then we’ll try and get to you. Arvind, this is your second startup, so I think you might have some perspective on this.

Arvind Jain

Yeah, well, I think, first of all, in technology, a lot of startups actually are started by Indians, folks in Silicon Valley or, of course, here. One thing which I… I think is interesting in the U.S. and Silicon Valley is the… you know, there is availability, you know, of capital. There’s belief, you know, and specifically in the Indian diaspora in terms of, like, you know, their ability to go and build great companies. You know, today, look at tech, you know, in the tech industry, you know, even in the large enterprises, you know, there are a lot of Indian folks who are CEOs. And I think what has actually made that happen is fundamentally, I think, you know, we are more hungry.

You know, we are, like, you know, I think there’s something about, like, in our culture, you know, and where we are as a nation, there is, you know, that drive, you know, that, you know, Indian people have, you know, and which is what is actually creating, you know, this incredible success, you know, for success stories, you know, for all of us. So I think that that’s one thing that I would say. I routinely, like, you know, of course, you know, I had the same thing, you know, I had the desire to make something. You know, big and, you know, that. continues to drive me, but what I see from, I work with a lot of young folks, a lot of people have actually joined our companies and then went on this entrepreneurship journey and I continue to see that same pattern that it is the folks who actually grew up here and then relocated to the US they are the ones who are most likely to start companies and become entrepreneurs.

Anirudh Suri

I want to quickly open up to the audience, I know we don’t have probably mics there so I’m going to can I see a quick show of hands again? 1, 2 and 3. So we have less than 4 minutes, so what I’m going to ask you is in 15 seconds give us a question or comment. 3 hands I see. We’ll start off here and come to you and then come to you. Hello,

Audience

Yep, I have a question for Malhar. So you have a multi -discipline startup right now, so and you also told that you’re not from biology field like you’re not affiliated from biology field so the question is how did you like find this problem to solve great we’ll take these two also you can just shout out while the mic comes Yeah. So my question is so I mean we had this technology and it became a boon and bane and then what started evolving with technology was cyber security the field of cyber security right so now we have this AI and also we have the fear of how AI is being used for the boon and the bane and also you have the additional fear of hallucinations and of course so all these equivalent to cyber security are you going to have something like AI security or is there a new field that will come up and also how can you handle this hallucination I mean you can give a relevancy score to the output?

Hi, my question is for Navina, actually. I also work in an AI governance company called Protego. I had attended sessions today with Amazon and Zoom, especially these big leaders are saying that if we do governance at this stage, we will not see the ROI from AI, and it’s going to stop innovation in some manner. What’s your take on that? How do you advocate AI governance, especially with your hands -on with G42?

Anirudh Suri

Great. So I’m sorry, but I mean, I’m sure we can speak. I literally have a timer that’s in two and a half minutes. Navina, I’m going to give you less than a minute, and then we’ll go across the room.

Navrina Singh

Yeah, it’s funny. If you were in the Amazon room and they made this comment because they were our first customers, so I’m surprised to hear that. But having said that, you know, it’s actually very clear. We are seeing very clear ROI on AI governance. If you have a very clear visibility, risk management practice, you can actually adopt third -party AI much more faster. And you’re seeing… much more, obviously, productivity gains with that. Secondly, when you have governance, your AI deployment increases, so you can actually deploy more products faster to customer, but also products that can be more trusted by the customers, and as a result of which, you are just adding more to top line.

So happy to share more details from our customers.

Anirudh Suri

I think you can take maybe the cyber question, and then Malhar will come to you for this. Are we going to see a new field of AI and cybersecurity?

Arvind Jain

Oh, that’s right, yeah. So absolutely, I think AI is a very new technology, and it’s actually very gameable. So there’s a new form of attacks, like prompt injection are coming into place. It’s actually a rapidly evolving new field with a lot of entrepreneurship opportunities. It’s about how you actually… So I’m going to turn it over to Malar. control like what data, what information actually goes to AI models so that they actually get to work on good safe data but then also like whatever output comes back from AI the responses that comes back from AI how do you sort of make sure that those are not attack vectors and similarly I think the other thing you mentioned the related point of hallucinations.

The hallucination is actually a core sort of feature of the current AI technology unfortunately like this is how it’s built and so again from a discipline perspective I think companies that actually detect hallucinations that can monitor it, provide observability on it is also again like a good area and a field of discipline.

Anirudh Suri

Good entrepreneur. Anytime there’s a problem there’s an opportunity. Malhar you have something? 16, 15?

Malhar Bhide

I think for my co -founder and I both it started off as this deep intellectual interest more than anything, being college students that was really what we had to go off with. We were always interested in DNA and how your body regulates different cells, how it sort of maintains healthy functioning and what can really be learned by mining the genome and understanding things from that. So it started off with that and then I think after that we treated it very empirically, talking to customers, talking to scientists, talking to doctors who know a lot more in this field. I think that was sort of the start and how it continued.

Anirudh Suri

Great. I think we are out of time, but I do hope that all of you have taken something away from the session. I hope that this summit has been a two -way conversation. I think it’s more important that, and I want to end with this remark, it’s very important that people sitting on the stage, whether it’s us or other panels, listen to all that you have to say and ask and show. because I think the summit must be a two -way conversation. I think that’s a very important piece, especially since so many students and so many entrepreneurs and would -be entrepreneurs have come here. So please do take the time to find the panelists if you want subsequently.

And now let me end with one best of wishes to all of you in your entrepreneurship journeys and to you. And we hope to see all of you back again here soon. And thank you all for staying here.

Anirudh Suri

Speech speed

166 words per minute

Speech length

2279 words

Speech time

820 seconds

Importance of learning from past technology waves

Explanation

Suri urges entrepreneurs to study earlier technology cycles because they contain valuable lessons about which business models and founder traits succeeded. Understanding these patterns helps founders anticipate challenges and opportunities in the current AI wave.

Evidence

“And for those of you who are not familiar with the history of technological waves, I really encourage all of you to study the previous waves because often you get to learn a lot from how the earlier waves of technological innovation panned out, what kind of entrepreneurs, what kind of companies succeeded” [1]. “I think for some of us who’ve seen the previous waves of technology, innovation, like for example, most recently the consumer internet wave and of course there have been multiple waves prior to that” [2].

Major discussion point

Importance of learning from past technology waves

Topics

The enabling environment for digital development | Capacity development

Arvind Jain

Speech speed

172 words per minute

Speech length

Emerging AI security challenges (hallucinations, prompt injection)

Topics

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

Malhar Bhide

Speech speed

187 words per minute

Speech length

Indian entrepreneurs building startups in the US

Topics

The enabling environment for digital development | Capacity development

Navrina Singh

Speech speed

179 words per minute

Speech length

Emerging AI security challenges (hallucinations, prompt injection)

Topics

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

Audience

Speech speed

173 words per minute

Speech length

253 words

Speech time

87 seconds

AI security as a new discipline (hallucination & prompt injection)

Explanation

An audience member asks whether AI will spawn a dedicated security field to address threats such as hallucinations and prompt‑injection attacks, indicating growing concern over AI‑specific cyber risks.

Evidence

“So my question is so I mean we had this technology and it became a boon and bane and then what started evolving with technology was cyber security the field of cyber security right so now we have this AI and also the fear of how AI is being used for the boon and the bane and also you have the additional fear of hallucinations… are you going to have something like AI security or is there a new field that will come up and also how can you handle this hallucination I mean you can give a relevancy score to the output?” [122].

Major discussion point

Emerging AI security challenges (hallucinations, prompt injection)

Topics

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

Agreements

Artificial intelligence | The enabling environment for digital development

Similar viewpoints

All three speakers agree that AI democratizes capabilities and levels the playing field, allowing people without traditional technical backgrounds to build sophisticated products and compete effectively. They emphasize that AI removes traditional barriers to entry and enables new approaches to problem-solving.

Speakers

– Arvind Jain
– Malhar Bhide
– Navrina Singh

Arguments

AI makes it easier for non-engineers to create products and compete with large players using fewer resources

AI democratizes knowledge and enables cross-disciplinary work with smaller teams and limited resources

Success requires unlearning old habits and trying new approaches since there’s no established AI playbook

Topics

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

Both speakers emphasize the critical importance of building trustworthy, reliable AI systems, especially for enterprise use. They agree that despite AI’s inherently probabilistic nature, companies must implement mechanisms to ensure accuracy, traceability, and regulatory compliance to succeed in the market.

Speakers

– Arvind Jain
– Navrina Singh

Arguments

Enterprise AI must deliver precise results despite probabilistic foundations, with fact-checking and authoritative source trails

AI governance creates competitive moats through reliable, robust, and explainable systems that work within regulatory constraints

Topics

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

Both speakers, as Indian entrepreneurs who relocated to the US, agree that the combination of Indian cultural drive and international relocation experience creates ideal conditions for entrepreneurship. They see the challenge of establishing oneself in a new country as developing valuable risk-taking capabilities that benefit startup ventures.

Speakers

– Malhar Bhide
– Arvind Jain

Arguments

Indian entrepreneurs bring risk-taking experience from relocating internationally, which translates to startup boldness

Indians who relocate to the US are most likely to become entrepreneurs due to their cultural background and determination

Topics

The enabling environment for digital development | Capacity development

Unexpected consensus

Arguments

For us, like, you know, as an enterprise company, you know, that, you know, we don’t actually think a whole lot about that. But it is important to sort of have, you know, these rules and regulations in place because otherwise AI can actually do significant damage, you know, in the industry.

AI governance creates competitive moats through reliable, robust, and explainable systems that work within regulatory constraints

Smaller companies benefit from not releasing products publicly until passing regulatory requirements and safety testing

Summary

Arvind suggests enterprise companies don’t need to focus heavily on policy considerations, while Navrina argues governance creates competitive advantages, and Malhar emphasizes the benefits of regulatory compliance for smaller companies

Topics

Artificial intelligence | Building confidence and security in the use of ICTs | The enabling environment for digital development

Impact of AI governance on innovation and ROI

Speakers

– Audience
– Navrina Singh

Arguments

Questions about multidisciplinary problem-solving, AI security fields, and governance ROI reflect real entrepreneurial challenges

AI governance shows clear ROI through faster AI adoption, increased deployment, and improved customer trust leading to revenue growth

Summary

Audience members expressed concerns that AI governance might hinder innovation and ROI (citing Amazon and Zoom leaders), while Navrina argued that governance actually accelerates business value and shows clear ROI

Topics

Artificial intelligence | The enabling environment for digital development | Building confidence and security in the use of ICTs

Unexpected differences

Necessity of dedicated policy roles in AI startups

Speakers

– Anirudh Suri
– Malhar Bhide
– Arvind Jain

Arguments

AI entrepreneurship may require dedicated policy and regulatory risk management roles similar to traditional C-suite positions

Smaller companies benefit from not releasing products publicly until passing regulatory requirements and safety testing

For us, like, you know, as an enterprise company, you know, that, you know, we don’t actually think a whole lot about that

Explanation

While the moderator suggested policy expertise might become as critical as technical roles, the panelists showed varying levels of engagement with this idea, with some dismissing its importance for their specific contexts

Topics

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

Overall assessment

Summary

The discussion revealed moderate disagreements primarily around the role and importance of AI governance and policy considerations in startup operations, with speakers having different perspectives based on their company size, target markets, and regulatory environments

Disagreement level

The disagreements were constructive and reflected different business contexts rather than fundamental philosophical differences. The varying perspectives on AI governance’s role suggest that the field is still evolving and different approaches may be valid depending on the specific startup’s circumstances and market focus.

Partial agreements

Both agree that AI creates new security challenges requiring specialized solutions, but they focus on different aspects – Arvind emphasizes new attack vectors and entrepreneurship opportunities, while Navrina focuses on the need for comprehensive reliability testing across AI supply chains

Speakers

– Arvind Jain
– Navrina Singh

Arguments

AI creates new attack vectors like prompt injection, requiring new cybersecurity disciplines and entrepreneurship opportunities

AI’s dynamic nature requires proving reliability across the entire AI supply chain, unlike static technologies

Topics

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

Both agree that AI enables smaller, more efficient teams, but Arvind focuses on operational efficiency and cost reduction, while Malhar emphasizes knowledge democratization and cross-disciplinary capabilities

Speakers

– Arvind Jain
– Malhar Bhide

Arguments

AI enables much leaner startups with fewer team members, less coding staff, and lower capital requirements

AI democratizes knowledge and enables cross-disciplinary work with smaller teams and limited resources

Topics

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

Similar viewpoints

All three speakers agree that AI democratizes capabilities and levels the playing field, allowing people without traditional technical backgrounds to build sophisticated products and compete effectively. They emphasize that AI removes traditional barriers to entry and enables new approaches to problem-solving.

Speakers

– Arvind Jain
– Malhar Bhide
– Navrina Singh

Arguments

AI makes it easier for non-engineers to create products and compete with large players using fewer resources

AI democratizes knowledge and enables cross-disciplinary work with smaller teams and limited resources

Success requires unlearning old habits and trying new approaches since there’s no established AI playbook

Topics

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

Both speakers emphasize the critical importance of building trustworthy, reliable AI systems, especially for enterprise use. They agree that despite AI’s inherently probabilistic nature, companies must implement mechanisms to ensure accuracy, traceability, and regulatory compliance to succeed in the market.

Speakers

– Arvind Jain
– Navrina Singh

Arguments

Enterprise AI must deliver precise results despite probabilistic foundations, with fact-checking and authoritative source trails

AI governance creates competitive moats through reliable, robust, and explainable systems that work within regulatory constraints

Topics

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

Both speakers, as Indian entrepreneurs who relocated to the US, agree that the combination of Indian cultural drive and international relocation experience creates ideal conditions for entrepreneurship. They see the challenge of establishing oneself in a new country as developing valuable risk-taking capabilities that benefit startup ventures.

Speakers

– Malhar Bhide
– Arvind Jain

Arguments

Indian entrepreneurs bring risk-taking experience from relocating internationally, which translates to startup boldness

Indians who relocate to the US are most likely to become entrepreneurs due to their cultural background and determination

Topics

The enabling environment for digital development | Capacity development

Takeaways

Key takeaways

AI-driven entrepreneurship enables much leaner startups with smaller teams, lower capital requirements, and democratized access to knowledge across disciplines

The fundamental entrepreneurial principles remain unchanged (ambition, risk-taking, solving real business problems), but AI uniquely transforms organizational structures and human roles

AI governance and policy compliance are becoming competitive differentiators, not obstacles – companies with robust governance can adopt AI faster and build more trusted products

Research has become more critical to startup success in the AI era, with teams needing to prove scientific and regulatory viability

Creative destruction will continue despite big tech advantages, as innovation still originates from passionate individuals who can now leverage AI tools more effectively

Indian entrepreneurs bring unique advantages including cultural drive, risk-taking experience from international relocation, and deep understanding of local markets

New cybersecurity disciplines are emerging around AI-specific threats like prompt injection and hallucination detection, creating entrepreneurship opportunities

Success in the AI era requires continuous unlearning and adaptation since established playbooks don’t exist yet

Resolutions and action items

Entrepreneurs should adopt an ‘AI-first’ mindset, consistently evaluating whether machines can perform tasks before hiring people

Startups should invest in AI governance early as it enables faster deployment and builds customer trust leading to revenue growth

Teams should focus on building reliable, explainable AI systems that work within regulatory constraints rather than just technological innovation

Entrepreneurs should engage empirically with customers, scientists, and domain experts to validate problems and solutions

Companies should implement fact-checking mechanisms and authoritative source trails for AI outputs to ensure accuracy

Unresolved issues

Whether every startup team needs dedicated AI governance/policy roles or if this can be distributed across existing team members

How to balance innovation speed with regulatory compliance requirements, especially for early-stage startups

The long-term implications of AI democratization on competitive moats and sustainable business advantages

Specific frameworks for detecting and managing AI hallucinations across different use cases and industries

How smaller startups can compete with big tech companies that have vast resources for AI safety and governance infrastructure

Suggested compromises

Smaller companies can delay public product releases until regulatory requirements are met and safety testing is complete, allowing them to operate with less formal governance initially

Startups can leverage AI governance as a competitive advantage rather than viewing it as a constraint on innovation

This comment introduces cultural and socioeconomic factors as key drivers of entrepreneurial success, moving beyond purely technical or market-based explanations. It suggests that hunger and drive stemming from cultural background may be more important than technical expertise or resources.

Impact

This observation added a cultural dimension to the entrepreneurship discussion and validated Malhar’s earlier point about the advantages of relocating and taking risks. It helped explain why Indian entrepreneurs have been particularly successful in Silicon Valley beyond just technical skills.

Overall assessment

Explanation

This topic was touched upon but could benefit from deeper exploration of cultural, systemic, and market differences affecting entrepreneurial success

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.