Just a little background, why Ministry of Panchayati Raj exists at the centre, because rural local governance is a state subject. We are rather new in this business, we came into being in the year 2004. Our objective was, or the purpose why we exist, is how we can empower panchayats, how we can nudge states into having acts that really transform our people into self -governing, responsible local bodies and so on. So, as a part of our job, we also have oversight over how the ministry, how the panchayats spend their finance commission grants. Finance commission grants are devolution grants, they go directly to the people in their… bank accounts and then subsequently… all panchayats, all two and a half lakh of them they are present on eGram Swaraj right from planning to the payment stage, everything is done on a portal which is called eGram Swaraj this portal works in the English language so I will tell you in 2019 when we were starting something called the People’s Plan Campaign, I happened to attend a Gram Sabha in the state of Karnataka I was there for something like 45 minutes and I was felicitated and sat on stage and I didn’t understand a thing and then it struck me I had this thing that how do you expect these people really to relate to what is happening because it is public money Everybody in the panchayat needs to know what kind of plans are uploaded How many works got done that were asked for the plans How much did it cost them to do it And subsequently they can raise issues in the meetings pertaining to the works close to their residences And along came Bhashini I think we had in the year 2023 an event called Manthan Where we invited a lot of people from the industry to tell us how we could conduct our business better And so Bhashini was a revelation And imagine that a person from a panchayat is looking at the expenses page for his gram panchayat or her gram panchayat And then by the end of the month, he has to pay the expenses And by a click of a button, they are able to see it in their own language It was magic That was the starting point.

Yeah, and subsequently, of course, we went from there and we found out through a survey that what really hurts a panchayat secretary is not to be able to produce the minutes of meeting in time, which are very important, which are the only record of a panchayat’s proceedings. And then again, using Bhashani and another tool, we were able to create Sabha Sar, in which if you input the video slash audio recording of your meeting, you are able to get a minuted draft, which you can then edit and upload. So that was miracle number two. And briefly, if I could also address Swamitva, the scheme that you mentioned. The Swamitva is a scheme where. Drone surveys are carried out over all the village habitations, so there are these pictures.

that are subsequently converted to orthorectified images and they lead to property rights for the people living inside those villages. But the way the images have been captured, there is dense point cloud information, all of which was getting wasted. Why? Because we were confining our attention only to the orthorectified images. So we had the AI guys look at that and then they converted all those rooftops that they could see into the solarization potential. As a result of which now, out of the 3 .3 lakh gram panchayats where drone surveys have been carried out, in 2 .38 lakh gram panchayats, you can go to gram Manchitra, and you can zoom into your village and then you can click the icon corresponding to the solar ability potential and it will tell you roof -wise how many panels can you fit there.

We’ve gone further and we’ve integrated that with the PM Surigar Yojana portal. As a result of which, the Gram Panchayat can drive it like a campaign and lead to greater rewards for everybody all around.

Actually, it reaches the last mile citizen when you talk about those benefits. So India’s last mile operates in local languages and dialects, as you mentioned, solving that problem. So in your view, how critical is language AI in ensuring that digital governance platforms are inclusive and participatory and increases citizen trust and participation in Gram Sabhas?

Like I said, people are now able to follow what… what was something that was written in, they could still see it, of course. In the English language, then they’d have to go to the person who they knew to be very smart in the village and they’d have this person read it out to them. Now they can see it at their leisure. Not just people here, but people outside who are working in Mumbai can see what is happening in their panchayats close to Pune or something and immediately they can get active about it. And the militarization tool that I mentioned, that opens a whole new set of avenues now. You can have a record, then against that you can have action -taken reports and then you could have follow -up in the next meeting.

It makes it all amenable to a very systematic representation on portals. So that is what some of the states have already started doing. And it is truly remarkable that, anybody can go in there. And when I say anybody, I don’t mean just the panchayat secretaries. Anybody in a village can drill into their gram panchayat’s record and see that corresponding to the finance commission grants for any year, what was the plan against which how much has been executed, how many bills were prepared against each activity, and what is the status of the payment, whether it has been completed, where the asset exists, the geotags, and then you can zoom in and maybe see it on gram panchayat.

So there are great rewards for everybody all around. And we need to, of course, now intensify it through a capacity building training program. That is something we started doing from the previous year. But it has been an incredible journey. And it is being adopted all over.

So, Alokji, let’s talk about… Let’s talk a little bit about Sabha Saar Impact. let’s let our audience know about it and with its launch on 14th August 2025 MOPR introduced an AI enabled voice to text meeting summarization tool powered by Bhashini ASR services. So as of 4th February 2026 over 1 ,15 ,100 15 gram sabha meetings have been processed. So this is a good number I need a thank you for the round of applause. So what structural changes have you observed in the panchayat functioning after sabha sar?

Sabha sar was one thing that we carried out for the convenience of the panchayats and the panchayat secretaries as opposed to E. Gram Swaraj which was which was our selfish motive we wanted panchayats to plan there and show all their vouchers there so that we could tell that this is how the money has been spent but sabha sar actually came through and As a part of a survey that was carried out using RapidPro by UNICEF, we asked something like 8 ,000 panchayat secretaries all over the country that how do you spend your time? How much of it is spent in inspections and attending programs and meetings and making records? So one thing that came through was the conduct and recording of meetings, meetings was the, in 65 % of the respondents, that was the activity that was sitting, you know, very heavy on their entire time availability.

And so having realized this and having the help of Bhashani, we converted it into a tool. So in Bhashani, it’s very simple. There is no big. Standard operating procedure as it were. So if you’re standing having a meeting, there has to be a recording device. It could well be your mobile phone. And then through audio or video recording, you can just place it each time somebody speaks. And later on, you input this into the Sabasa tool. The Sabasa tool is not something that is a part of the device on which you carried out your recording. So the issue related to connectivity in villages is something that we’ve been able to sidestep. And once you do that, it gives you a draft minute of meeting.

So Bhashani turns it into English. And the English thing is monetized using the AI engine. Again, Bhashani gives it back to them in their own language. And that efficiency. Yes, it’s voila. The person can just make a few changes and upload it. And we have. We’ve had some heartfelt gratitude coming to us from villages. as a result of this.

Okay. So has the structured documentation improved transparency, participation tracking or monitoring of meeting frequency and agenda quality too?

Now that the minute is ready, if there are five items, ten items, so the states that have really gone ahead and adopted it, which is Odisha, which is Tamil Nadu, which is Tripura, all these people are into the second stages now where they are looking at the minutes of meeting and converting it into or refining it into tools that help them keep track of the activities after they have been created. We also realized through our meetings that why is the number just 1 ,15 ,000? So there are a whole lot of people whose languages do not exist on Bhashani. So from there, we ask those states to provide Bhashani with the necessary expertise so that they can train their bots.

And they’re already working on something like 11 more languages, which includes Assamese and Bodo and Maitali and Santal and whatnot. Yes. So those languages are also. So it’s been a very gratifying experience. And then the learning continues.

Yeah, it’s commendable that things have reached to that level. So over to you, Amitji, from an accountability lens, does structured documentation change behavior with the governance systems?

Thank you. So I think, you know, so if you have understood the enormity of the situation, right, what we are talking about, 200. 150 ,000 plus gram panchayats and different kind of languages. so just to circle back if you look at the frugality of the situation right so so so for example if you look at in india we generally people talk about either we live in a bullock cart stage right or we are aspiring for bullet train right so so the point is if ai has to tell us in terms of you know how we learn in the future how will we transform so we cannot i mean leave out 900 plus million people who are living in villages absolutely so the idea is not to make it very very urbanized you know very very kind of elitist idea that you know that ai is only for urban ai is only for industries ai is only for commercial sector so obviously this is a journey right so you have to start somewhere so for example i mean the frugality what i was talking about that we did not ask gram panchayat to invest anything right all they need to have is a lot of money and they have a mobile phone which any which way they have right and the idea is just to kind of record and upload obviously there will be some you know challenges and kind of resistance also in the beginning But, you know, once they get used to it, so for example, today we are asking them to kind of, you know, upload your recording, right?

The rest is done by system. And system also has a provision of, you know, human in the loop so that we can go and correct it. Now tomorrow we see the next step what we will be doing, what we can do perhaps, right? When the next meeting happens, we can also populate the agenda from last meeting, right? So what was discussed last time, what was committed, whether you are doing or not doing, right? And then everything goes to kind of public domain. So generally the people who live in city, they know that, you know, when there is a RWA meeting, nobody goes and attend, right? But they all, you know, wages, warfare in the WhatsApp group, right?

So same in the village also, it’s not easy to bring people, right? But once they start getting the hang of it, right? That okay, there is a meeting, I am getting the mom and it’s available in the public domain. We are using AI, AI is for good. AI can do it. AI can also be leveraged for rural sector, right? Why it has to be very, very elitist only for passport, say, wallet, say, right? Right. So so that’s just a beginning. It’s just a journey. Right. And also, if you see from an idea point of view, I mean, this is a phenomenal idea for Ministry of Panchayati Raj. Let me congratulate sir and the entire team to think of something like that.

Right. Because the AI is all about idea and use case. Right. If you have the right idea, you can do wonders. But you have to have idea and kind of, you know, muscles to execute it. So that way, I believe that in this whole documentation will do wonders for them. Graham Panchayat will also realize something which was missing in the most part of the word that, you know, the record keeping accountability, transparency, so on, so forth. Because generally these decisions were taken by some people only and executed by some. And the large population was largely kept out of it, knowingly or unknowingly. Right. So I think that’s what I said, that, you know, it will change the way they were.

it will change the way they think because this is only for a you know kind of we are starting only with a let’s say meetings but now they will start thinking and there will be demand from states and otherwise right what more can be done with AI so broader case would be achieved yeah Sabasa is an example like Praman we are doing we have launched this Pancham you know bought also for all elected and selected representatives so I think it’s a great you know kind of experience efficiency would obviously help them adopt I mean let me tell you in our own corporate meetings we are still some of us making notes right despite being on teams despite using co -pilots despite having all tools at our disposal but we are still using it right we expect a junior guy to take notes and circle back so that’s a cultural change which you have to also see and these changes and these changes couldn’t have been possible if we wouldn’t have the infrastructure like Bhashni right because ministry on its own how ministry got benefited, we have infrastructure like Basni, right?

We have the you know, GPUs got available to us through the NDIA mission, right? Otherwise, you know, procurement itself could have been a big challenge, right? So we have a team to kind of build applications. So I think you know, it takes a village to move something, right? So that’s what has happened here.

Thank you for sharing your thoughts. In fact, just continuing with that, the Department of Drinking Water and Sanitation has actually approached us that the meetings of their village VWCs village water committees they want to use Bhashini for that and there has been some initial interaction between the two.

That’s commendable, I would say. That’s awesome. So Alokji, let’s talk of some implementation challenges in rural India with AI. AI in rural governance is transformating but complex. So what are the biggest operational challenges, infrastructure, though a bit, I think Amit you were about to share that, but then infrastructure, training, dialect diversivity and connectivity. So what challenges are you facing? How receptive are panchayat functionalities and rural citizens to AI -enabled systems?

Challenges, of course, there are many and you would have anybody tell you. What we have found out, the adoption of eGram Swaraj by our villages is gram panchayats. A case in point, Uttar Pradesh has got something like 59 ,000 gram panchayats. And for Uttar Pradesh to onboard eGram Swaraj seemed like an impossible task because it involved registering your digital signing certificates and then everybody agreeing to completely dispense with checkbooks. All your payments were then going to be… Can you imagine Uttar Pradesh did it in 40 days flat, all 59 ,000 gram panchayats. So my point was that if you are ready with a product that addresses their needs and it is friendly and it meets, of course, my need was that I needed the money well accounted for and their need was a system that could make it very easy for them to do it.

So we met halfway and if UP can do it in 59 ,000, I am not prepared to hear an excuse from any other state in the country. It’s a trial by fire. Likewise for Sabasar. Sabasar, again, I said initially that there was a demand that was indicated from the state. So when we set out to meet that, we were clear what is it that we are looking for and people were so forthcoming. In fact, Bhashini also enabled me. to write letters to the states in their languages and people were gushing with affection and what not. I got a letter in Telugu for the first time and all that. So there are challenges but then the Ram Panchayats are predisposed to meet you halfway.

So you need to begin that journey and we have seen that with regard to a number of things. There have been campaigns every year they carry out a campaign from 2nd October to the 31st of December which extends to January typically where all two and a half lakh Ram Panchayats prepare their Ram Panchayat development plans and upload it on the portal. So 2 .5, 250 ,000 Ram Panchayats all of them planning for the next year and so before you enter the next financial year their plans are ready. I mean we don’t… We don’t do it in the departments, in the ministries. And all these Ram Panchayats have… not done it once, twice. They started in 2018. They’ve continued to do it ever since.

In the COVID year, there was a request that campaign. So there was a massive pushback from the states that no, we want to do it. The inertia was so great that they still did it. So there are challenges but if we make an application like you were saying that this is a simple recording device, this is a mobile phone, there aren’t things that you need to procure to set it up. So if you make a simple tool, people would grab it with both hands. So I think that is the embracing of challenges rather with the response we are getting with Bhashani.

So for ministries delivering last mile services such as Ministry of Rural Development and the Ministry of Agriculture and Farmers Welfare, what lessons from MOPR’s AI journey would you share? How important is open architecture and in your sense?

That is dangerous territory. I am not in a position where I could start advising anybody because they’ve got pretty robust systems of their own. If you look at Manrega Soft and the PM Avas Yojana, because they are running schemes which are very pointed. Avas Yojana is just about houses. Manrega is a scheme where there is, of course, it’s as large as the things that you do in the Finance Commission grants, but it is fairly well organized. And in all of these, typically, the beneficiary is the individual. In Panchayati Raj, there are individuals at the end of it, but our emphasis is on the institution, the panchayat, and not just E. Gram Swaraj and the things that we do for their accounting and planning.

We also hooked up with the… Meteorological Department… and there are daily forecasts being generated for every gram panchayat. This people are able to see on their phones and all with the similar ability as they are able to see everything using Bhashini. So it’s a great enablement all around and it can only get better.

Absolutely. So, Amitji, over to you. How critical is open architecture ensuring long -term sustainability and avoiding vendor lock -in?

If I can take a minute and talk about the previous question also.

Sure, please go ahead.

Sir rightly mentioned that different ministries have got a different mandate. It’s not an apple to apple comparison. But see, you also have to see the panchayati raj, the main role of panchayati raj, what I understand is a mobilization. because they are not running major schemes on their own compared to others. And generally the best practices doesn’t have to be in form of technology or architecture only. The idea is that if you go down from top, there are two different ministries and if you go to the village, you will see the same infrastructure, same set of people are only working from both departments. So the idea is if one can do, others can also do. So there is a lot of learning in terms of method that how we could overcome, how could we mobilize, how we could implement some of these solutions.

And I am sure we know that RD and agriculture are also doing a lot of things, but their mandate is much bigger. But they can also take a lot of pride or learning from the success which we have. What was the second question? The second one was that how? Critical is open architecture in ensuring long -term sustainability and avoiding the window. So you must be hearing this word called sovereignty quite a lot, right, nowadays. So the whole idea of, you know, being sovereign in any part of the, you know, technology, be it defense, be it IT, be it any way, is the survivability, right? So the idea is despite, in spite any kind of, you know, geopolitical risk, we should survive.

Our system should run, right? So for that, generally people confuse sovereignty with also making India local, et cetera. So that’s not the case, right? We will always have some technology from outside. But we have to design in a way that it is kind of ready to shift, right? So either from a technology point of view, we have the interoperability, the standards which we have chosen, the models which we have chosen, the infrastructure which we can move around, and the teams which we can control, right? Right. So the data residency has to be within India and data is with us. So obviously if we have trained on one, we can train on another, something else also.

So the idea is also to look a little bit long term. See, what has happened that when we started, obviously, there were a lot of POCs. Nobody knew, right, how AI will behave. Still, we don’t know. Still, we don’t know, right? I mean, so obviously, that you have to start somewhere, right? And then you have to also ensure that in future, when we start with one use case, it becomes easy, right? When the department itself becomes fully AI enabled and we have 10 AI use cases running, then it becomes a problem, right? Problem of management. So that’s where I think we need to plan better for future so that, you know, we plan. I mean, it’s not that a use case is defined, then we found an easy method of procurement of infra or the model which I knew.

So going forward, I think there will be a platform approach, right? So where we have to think for future also that, okay, these AI cases are likely to come in future as well. Different kind of AI, right? DL. DL. DL. DL. DL. DL. DL. DL. DL. DL. DL. DL. DL. and accordingly we have to have open architecture like the way we did in a normal digital transformation. Even digital transformation, there used to be time where we created our own independent monolith applications. But now we are creating applications, you know, which are more API -based, can integrate with anybody, right? And futuristic, can scale our modular. So same concepts have to be used for AI

Well said. So I think adoption comes with responsibility and that’s what you are scaling at, looking at. Swalokhji, Sabha sir demonstrates how language AI can power grassroots governance. After Sabha sir’s success, what deeper integrations do you envision with Bhashini and what does the next phase of collaboration looks like? Let’s talk about that.

About 16 have already started providing all those common minimum services. So minimum se nahi chalega. We wanted more. So now we had like a model list, union set, if you will, of all the desirable services that were being delivered. And the ministry carried out an exercise through an expert committee. And we have a much bigger list now. So we are not satisfied with the minimum. Now we are working towards that. But I think that AI has great potential in helping us. Thank you. So service delivery is something people don’t know to expect. and we would like through and people are going to be speaking in any number of languages. I think the next step, my government is something that has always been very invested in providing services to making ease of living easier as it were and providing all manner of things.

Everything is finally a service. You need to look at a doctor. You need your road fixed. You need a street light to be working. You want the log water to be drained or something. She needs more attention than us. Okay, over to you. So people should come to expect. they should demand these services from their Gram Panchayats. There are mechanisms of doing that because Gram Panchayats don’t have a lot of resources in terms of manpower, in terms of people who are at their beck and call to carry out the activities that are flowing from the Charter. So there are systems in a lot of these villages. You have common service centres in some states. They have their own system of common service centres like UP, like Bapuji Seva Kendra in Karnataka, like Me Seva.

So we need to take that further and we need people to be able to talk and find out if a certain service that is available to them, can they avail it in their village? If they are to do that, what is the mechanism? And if they’ve already made an application, that what should be able to tell them that where that thing currently stands? so that is a very wide area like I said that there are a number of services we also learnt of a pilot that was carried out in Guwahati where the bus used to have a camera it used to drive through, capture all number of images and basis that it would assign issue labels to them as it were if there is a drain overflowing so it takes note of that if there is a pothole then it takes note of that and then it assigns it to all these agencies whose job it becomes now to fix that so not that but maybe we have a mobile interface called Meri Panchayat which ports a lot of information from E Gram Swaraj Meri Panchayat also has the capability of capturing images of the issue that is being reported I think the next step is that image it makes sense of the image and it assigns it to the necessary department.

There are people who are mapped whose job it is to carry it out and within a certain amount of time it doesn’t happen, then there is escalation. We need to go deeper into that system. That, I think, is the next frontier. And, of course, because it involves vocalization of your demands, so bhajani is absolutely critical in this. So when we say there is a long way to go, I think that phrase is no more relevant. It’s a short way, but not even a big journey, an intelligent journey to move

So India is building public digital infrastructure for AI at scale. So how do we balance scale with accountability and public trust? We have talked much about how we are building things. But let’s talk about the other side. And can India lead the world in population scale?

Of course it can. I am sure about that. But then multilingual AI for governance, when it comes, you would like to have a short -ended first. So one thing you all have to realize that whatever we do is a population scale and unparallel because of our size. So even our POCs exceed the kind of performance of European countries Our UP sir talked about UP 60 ,000 panchayats If you look at UP maybe it will be in top 10 country in terms of population and size. I think the world is vouching for us when it comes to the use cases So see if you look at that we have got that scale now. We have the experience behind us We did Aadhaar, we did UPI, we did Fastag, we did GST and we did Income Tax.

So now we have that confidence behind us that we can do anything of scale and with the same Prugal approach we will do 10 times cheaper than Western world and certainly not worse, better only. and also from last decade we have evolved right so for example the concept of privacy like dpdp act consent based usage like you know adhar brought so a lot of things have improved from a policy side of it now now once you have policies in place systems are easy because system themselves act as a rule you know once you have policies in place then you don’t need so much of human intervention or discretion so since we have done it since we have kind of you know done so much so now if you look at the very simple case bhashni i remember four five years back and i and amitabh used to i mean kind of debate also whether we need a bhashni okay right because we we had some of the google translate services so on for forth right but the idea is that i mean in the hindsight that was the right call right in future we have to have something called sovereignty word right we have we don’t have to depend on I mean we need to be frugal and we don’t want to use you know the applications which are very expensive from a taxpayer money point of view so similar things we have done a lot right so I think the next step for example if you look at roam around in AI summit you will see how many LLMs and SLMs we are building on our own right honorable ministers talked about five layers application I think we have ample talent to build applications LLMs we use open LLMs but we are developing our own and Basni also like one of the you know common infrastructure energy will take care right infra and chips anyway will have dependency but that’s the rest of the world also has a dependency right not that everybody has a rare earth and everybody is building chips so that way I believe that you know that and because we have that technical know how also I mean that’s our kind of bread and bread and butter nowadays right so we’ll be able to take the learnings from all these systems and we’ll move forward as of now we were a bit slow in last year or two because AI itself was new for everyone so we took some time but now I think from this year onwards we’ll really scale it up because we have tested the blood, we have seen the success and we will

sure, thank you for sharing that so as we come towards the closure of this conversation I would like to leave with the one final thought which is like if Panchayati Raj institutions are the foundation of democracy can AI when built on a public stack and powered by language inclusion become the strongest enabler of participatory governance in 21st century just closing thoughts from you both Alokji, would you

absolutely he was just telling you that that we’ve been able to do things at scale this thing about UP that I told you I wear it like a badge that to have done it in some place so and it’s not an easy ask because there are so many stakeholders they’ve got various kinds of issues of their own you’ve got to engage with them address those things and if my problem is well defined and if I know what kind of a thing is going to help me redress that like Bhashini did for us I think that what you said is going to come true because that is so being able to understand my problem and knowing what parts of the problem can be fixed in what manner using the various tools that are available that is the key and I it’s not an over simplification but good servant bad master so that is something that stays and it is not it’s not going to land you in the right places if you just let it go around like an animal.

But then if you know where to put it, what modules to be inserted, where, what has been used in the background. And so that would make you more confident. I’m not really an AI person, so I’m just speaking on the strength of what I have learned. And the experience thus far has been outstanding, partly because we’ve had a very good partner. But other than that, I am not, you know, I’m not throwing it all open out to AI. I don’t wear T -shirts saying I love AI or something. But I have a problem, and it needs fixing. And I need to be able to know what aspects of AI can help me fix that in the best possible manner.

And that’s my thing on

So like Sir said, you know, Sir is not an AI person, neither am I. So if you look at, you know, that… But he was transparent enough to share that. No, no. So look at that way that none of us were, right? Yes, exactly. Because if you’re talking about AI, I have been doing this, you know, digital transformation for public sector for over 20 years. Yeah. Obviously, there was no AI, even there was no DPI, DPG also, you know, what we kind of retrofitted with the names, right? Right. So if you look at the idea of Panchayati Raj itself is a participative governance, right? That people have to assemble in the Gram Sabha and decide on the money which they’re getting, how to spend and prioritize.

Absolutely. And if AI tools like Praman and Sabha Sar and, you know, Pancham can help that strengthen, what best, you know, you can expect from a participative government, from a democratization point of view. Yes. So I think this sometimes, you know, that technology becomes secondary. Yes. In my view, most of the time, right? The ideas have to be clear in terms of what you want to achieve. and what problem you want to solve, what scale you want to solve, what are the guardrails you have to kind of, you know, also put in place. So, for example, when we do AI, that it cannot be 100 % autonomous, right? Of course. And it cannot be 100 % human in the loop also.

Because if we have each and every transaction being, you know, approved by human in the loop, then it defeats the purpose of AI. And there is no AI, right? Then we are still living in the rule -based algorithms. Algorithms. So the idea of, you know, that AI will be that we also train, monitor, have the mechanism to take complaints, have the mechanism to perfectly, you know, kind of train it better so that we improve our accuracy. So that is how AI journey. So AI journey is slightly different from the previous digital transformation journey, which were more like a transactional systems, right? So that way, I think, if you look at currently also Sabasar, I think whatever I am hearing from people market teams also, So it is giving great accuracy, right, in terms of translation and summarization.

And I’m sure whatever there are little bit areas to improve, it will improve on its own. So we cannot stop it, right? So once we have boarded a flight, then we can only get down at where we have to, right? So I think future is bright. And also from a MOPR experience point of view, it will also, I’m sure, energize and motivate a lot many others. I can say with my experience that if MOPR can do in rural, we can use AI tools. There is no stopping for us as a nation. This is truly an achievement when it comes to MOPR with the government.

So you want to say anything regarding this, Alokji?

I thought of another application that works. That is something we’ve been working on, which was spatial development plans. Okay. we again engaged with a lot of panchayats that were close to the highways okay so typically if a panchayat is on a national highway close to a big city and have a population of 10 000 plus then you were eligible to participate in this program okay so there were 34 gp that we involved and we got the planning and architecture colleges to prepare spatial plans for them spatial plan would be futuristic it would zone and it would you know assign it would look into the future and see how this place was going to grow it would devise road networks or something and tell people what they would become over a period of time we had a conference with the with gram panchayats around bhopal bill and the people were so annoyed We don’t need a spatial plan.

Over a period of time, of course, we told them what it was going to be, but we had this epiphany that people need to be able to see what this spatial plan will help them become. And then we went into the next national conference. We had for each of these 34 spatial development plans a visualization. And we showed people that if you want to become this, you have to do this. And then there was greater enthusiasm. So the people on whom this plan is, who are going to be subjected to this plan, if I could use those words. So these people, if they’re not on board, there is no way you can carry it out. And that, I think, is wide open.

And we’ve had after that. But the entire state of Andhra Pradesh has gone ahead and said that all their planning is going to be spatial plans. So that is something that is amenable to AI tools. And a final thing that I remembered that lots of times we need to convey through audio video messages. He mentioned Pancham. So Pancham is a WhatsApp -based chatbot platform which allows us to have two -way conversation with all the sarpanchas and panchayat secretaries in the country. So all these people. And so if there is messaging that needs to be conveyed, if there are videos that need to be quickly created using AI tools, that is something that would be hugely effective in getting the message across in the quickest possible way.

Thank you.

Thank you so much for such endeavor. insights on the Grampanchayath and how things are working behind. Actually, I’m sure the audience was truly, they were unknown about what’s happening around and this conversation has given a new tangent to how we look at the rural development. Thank you so much Shri Alok and thank you so much Shri Amin for sharing these thoughts on Grampanchayath development. Thank you so much for this fireside chat. Thank you. I would like to call Ms. Deepika. to please felicitate Mr. Alok.

by corporations, by innovators to secure that outcome. And if current trends continue, the majority of AI’s economic value risks being centered in the hands of countries and corporations in the Western economies in China. And some estimates suggest that 70 % of the value could be created and reside in those locations. And I think it’s for us in this context to think a bit about why we don’t need to accept that outcome. It’s by far means not an inevitability. And to democratize the impact of AI, it requires intentional design, it takes international collaboration, and it takes societies coming together to ensure that doesn’t happen. It also takes innovation and research, workforce development, private sector partnerships, and also trust, safety, and security.

And they’re the things we’re going to talk about on the panel today. And my colleagues are extremely well -placed. to share their thoughts and insights on those topics. So let me introduce the panel. We have Amit Chandha, Managing Director and CEO of L &T Technology Services. Good to see you, Amit.

Happy to be here.

Great to have you with us. Amanda Craig -Dekard, Senior Director, Office of Responsible AI at Microsoft. Great to have you with us. Sachin Kakar from India Site Development, Privacy, Safety and Security at Google. Good to have you with us, Sachin. Thank you for being with us. Lee Tedrick, Inaugurable AI Multidisciplinary Initiative Fellow, University of Maryland, Senior Advisor on the International AI Safety Report. Lee, good to have you with us. And last but by no means least, Julian Waits, Chief Experience Officer with Rapid7. Good to have you with us. Good to have you with us. Okay. So without further ado, let’s take a look at international and scientific research collaboration. And, Lee, let me come to you.

Let me pose. Here’s a question. Okay. And, Lee, let me pose. And the second international AI safety report was released just ahead of this conference, something that you’re very much an author of. Let’s start by hearing from you and then maybe, Sachin, I’ll bring you in. What opportunities do you see, Lee, in open international standards to address the technical challenges that we face while also building trust in AI -based systems and services? Which of these, how would you characterize those challenges and which are most critical in a developing country context?

Yeah, thanks for the question, Brad, and there’s a lot here. So the international AI safety report that I worked on with a panel of about 100 experts was just released. And one of the key takeaways from the report is that while we have made a lot of progress over the past year in evaluations and developing evidence, there’s still a long way to go. There’s a gap. And I think, you know, internationally. International standards organizations and similar efforts is a good way to work together to try to fill some of the gaps. ISO has already released one standard, 42 ,001, which is a good start, but we need to accelerate this, and we need to also recognize the fact that standards and evaluation metrics, you know, there’s a tension.

On the one hand, we want them to be able to apply across borders because we want to enable companies to have responsible technology flow across borders. But on the other hand, it’s really important because we all differ in terms of language and culture that we need to be able to customize them for different cultures, norms, languages. And I think, you know, the standards organizations will continue to play an important role. I spent a year working at NIST, the U .S. National Institute of Standards and Technology. One of the NIST projects is working on what we call the zero draft of trying to create a draft that we could then feed into the ISO process, and NIST is trying to collect stakeholder input into that draft.

And I think, you know, more globally, you know, efforts like the Hiroshima AI process, there are sort of all these pre -standards efforts where different stakeholders across different regions can work together. And I think that the ACs, the AI safety institutes across different countries and how they can coordinate. So I think there’s a lot of work to be done, but I think there’s a lot of avenues where we can collaborate together and make sure that we’re addressing the needs of everybody around the globe. Thank you.

Yeah, thanks, Steve. Very well covered. If I can add just a few more points. I think one of the challenges we see is copy pasting the regulations or standards from, you know, international markets to local markets may not always work. So localizing them, understanding the needs and constraints of the local area. Google launch Indiq GenBench. It’s a test bench for fine tuning. And assessing the. LLM models for local languages, supporting 29 Indian languages, 12 scripts, and 4 language families. So that shows an example of how we need to localize things. The second point is one -time audit or certification may not work as AI evolves. We need a continuous scanning and auditing to make sure we avoid any temporal drift in these standards and the applications.

So Sachin, let’s build on that. How do governments and developers collaborate in a way that we get the outcome that everyone desires, which is not to see the developed markets race ahead of developing countries? What does that collaboration need to look like?

Yeah, that’s an interesting question. I think at highest level, the way we think to bridge the gap between AI divide is to move away from traditional, traditional transfer approach. to more co -creation where developers and government coming together and and the underlying goal is that standards and regulations are seen as enablers and equalizers not as barriers or compliance hurdle so three specific dimensions in which we believe developers and government can collaborate and Google specifically focuses on number one is open source frameworks and interoperability and standards second capacity building and third is workforce upskilling and research I’ll quickly unpack each one of them so starting with open source frameworks AI is not new to Google we have been working on AI for past decades and remember Alpha fold and we were the first one to share the transformer paper on which all the LLMs are built when we were building AI we were also focusing on best AI practices and safety practices on AI And we have open sourced all the best practices to keep AI safe.

Safe SAIF, secure AI framework is something we have shared outside. And it is important to understand supply chain risk. And India’s digital transformation is characterized by DPI, the digital public infrastructure on which Aadhaar and UPI are built. So they can actually leverage some of these secure AI framework to make sure the malware attacks and the vulnerability in open source components are taken care. Now, standards is one thing. The collaboration goes beyond to adoption of them. And Google has co -built the COSI, Coalition of Secure AI Framework, with various industry partners. And this is what we are expanding in APAC, including India. Now, we are also committed to capacity building. With the government. And which means we need to provide tools and infrastructure, not just standards.

So we are proactively sharing the threat intelligence. We are building tools like SynthID and sharing with the community abroad. SynthID is a watermark technique which goes into the text, image, video, audio, and it can tell you whether it is AI -generated content. So some of these tools are also helping us to make sure our commitment towards standards goes into actual adoption. And finally, upskilling workforce, digital literacy, working with government to make sure the vulnerable section of the society, like elderly and teenagers, are aware of some of these challenges. And giving grants to institutes like IITs to push the frontier of research, like PQC, post -quantum cryptography, are other areas of collaboration between AI developers and the government and academia.

Let me just ask you both a question. Is there a trade -off between setting global standards and regulation? ensuring the right environment for innovation and collaboration?

Oh, yeah, that’s right. And that’s where you can start with the global regulations but then adapt them to the local constraints. Like we have bandwidth constraints in India. We have linguistic diversity. And therefore, the global standard should not become a hurdle for the young startups in India. Rather, they become co -creators in enabling the innovation that can happen and then evolve from there. So it’s a creative tension, and I think the best way is to be adaptive in this situation and eventually evolve to the international standard.

How do you see this interplay, Lee?

Yeah, I think, I mean, kind of in my work, you know, both in government, academia, and I spent 30 years working with the private sector, I think sort of figuring out the standards and the standards that are in place and the values that are in place. evaluation techniques is really key. You know, how are we going to evaluate these systems so we can, they can meet a certain threshold of safety. And then I think the question kind of comes in, you know, afterwards, once we know what it is, you know, should there be regulation or not? You know, I worry a lot of times that when we go too quickly toward the regulation, you know, the best of intentions may be there, but, you know, the technology is moving so quickly, regulators don’t necessarily know how to style the regulations to achieve the goal.

And I think sort of working from the bottom up with the science, developing the evaluation technique, taking into account that we do need to socialize, you know, customize for local markets is really important. And then we can get to the question of, well, should there be a regulation or not? And that’s where, you know, different countries may have different answers, but at least we’re working from a common technical framework and evaluation framework to assess systems. Thank you.

Thank you both. Let’s make a shift to… The conversation towards more public -private… collaboration, which I think we know is at the heart of driving the success that everybody’s looking for. And Sachin was talking a little bit about capacity building. Maybe we focus on those two elements. And Amanda, I’ll come to you and then to Amit. So there’s a persistent skills gap in AI. It’s very apparent and a lot’s being done to try and bridge that here in this country. How are your, has your organization, and I’ll come to you Amit with the same question, how are your organizations grappling with that challenge and also collaborating with government to help to narrow that skills gap?

Thank you. Yes, skills gap is really important. We see it as part of the sort of foundational infrastructure for what we need to work on together as Microsoft with other industry partners, government partners, other local partners. It’s going to take a whole community really working together to do this at scale. And just to take a step back for a moment briefly before I talk more specifically about skills, you know, we kind of see this as part of a holistic effort where you kind of need to support all of the enabling infrastructure for AI deployment, kind of from from the infrastructure layer all the way through sort of realizing value in local use cases. So we actually published on Wednesday a blog from our president, Brad Smith, our chief responsible AI officer, Natasha Crampton, where we talk about sort of five areas where we’re really focused on investing to kind of close the gaps between AI diffusion and the global north and global south.

So we talk about, like, hard infrastructure investment, right, in terms of connectivity, AI compute capacity, scaling is the second part of that plan. And the third part is really thinking about multilingual, multicultural AI capability. And the fourth is really working with local partners on local AI deployment and really what we can learn and what’s going to serve local communities, also what we can learn through that process around how we need to adapt the technology so it’s ready for those local use cases. And then really measuring diffusion so that we actually understand how things are going and how we can do that. And then really measuring diffusion so that we actually understand how things are going and how we can do that.

And then really measuring diffusion so that we actually have really informed interventions. And then really measuring diffusion so that we actually have really informed interventions. And then really measuring diffusion so that we actually have really informed interventions. So that’s the kind of holistic approach that we’re thinking about for public -private partnership. And looking at skilling more specifically, we actually have a new sort of initiative that we launched last July at Microsoft called Microsoft Elevate, which is really bringing together a number of ways that we engage with a community that is going to also be part of skilling everyone at scale, so sort of nonprofit communities, schools, and actually ensuring that they’re equipped with the technology itself, so with cloud compute access and with access to AI.

And then we are coupling that with investments in skilling. So we have made some big -number commitments around how we are really trying to do this at scale. I would say specifically for India is, you know, we last year, early last year, we made this commitment to scale up 10 million Indians by 2030. This year, we upscaled 5 .6 million Indians, and so we actually doubled that commitment to 20 million people by the end of 2030. And one of the ways that we’re doing that is we’re actually, we just announced this week a new Elevate for Educators in India program where we’re partnering with local schools, with vocational institutes, with higher education institutions to sort of teach the teachers, right? So you can actually work at scale, and we’re working with a number of Indian government ministries in this program to figure out, you know, what, how we can ensure that we have tailored programs for all of those different communities and that we’re thinking holistically about how.

You know, we, across those different sort of educational paths, are really meeting people where they are and equipping them to kind of do the next powerful thing with AI.

Thanks, Amanda. And as a business, L &T Tech Services, I mean, part of L &T originating here in India, but now very much involved in global markets. How are you tackling this in terms of addressing the skills gap?

Sure. So thank you. So before I go to skill gap, I do want to make a point on the regulation part. I do believe that too much of regulation can stifle innovation as well. So we’ve got to be careful on how much we do and where do we take it. And then the second part, of course, is to do regulation of traffic control in Delhi for our next event that we have. I think all of us will agree. Let’s get down to skills in a second now. I had to say that because it was a mess in the last two days. I’ve got pictures of myself in an auto rickshaw as well. So if we get down to skill gap, I want to address this three ways.

So I am responsible. I run a company which is potentially India’s first, engineering intelligence company with about 25 ,000 employees. I’ve been CEO for five years. When I took over, we used to be about 15 ,000 employees. We’re about 14 now, we’re about 25 ,000 employees. So, we look at skill gap and I look at skill levels. Three things you have to think about. Whatever work we’re doing in engineering consulting today, I want to say 40 to 50 % of that is new and built in the last five years, did not exist. I also want to say that whatever we are doing today, 60 % will be gone in about three to five years time. That’s the rate and pace of change. So, while my colleague from Microsoft spoke about skilling school stem as well as colleges, we’re doing two different things to stay current with the changing dynamics or three things.

One, we are actually reaching out to colleges. In the last year of their curriculum and we are making sure that the curriculum is going to be in the last five years. in India is contextual to what the industry needs. So we are sending our employees to teach. We are using CSR hours. We are doing all of that to build that up. We are actually participating with NASSCOM as well to be able to do that in the skill development. The second thing we are doing is upskilling our own employees. Now, again, in a developed economy, it’s very simple that you hear these layoffs that happen all the time and they are not because people don’t have work but because the skill is redundant.

So let’s go ahead and get a new set of skills. In an Indian context, my colleague here spoke about that very nicely. You can’t cut and paste. You fire a thousand people, you will actually end up spending half your working hours plus more with the labor commissioner here locally. You can’t do that. So you have to be able to skill people up while they are in the workforce. Now, one thing is developing curriculum, developing modules for them. to go through but the second part is actually making them do it so and normally in a consulting company you would send people to get get coached and do upskilling when they are not billable we actually doing it while they are billable because when they become non billable that’s not when you want it you want it before that right so that’s and it’s a major shift in how we’ve been operating the third thing that we are tracking as an engineering and a technology company is how much of personal time is the employee spending on technology development efforts beyond billing hours to the client so you come in and spend 40 hours right and that’s what you normally work now if you spend another three hours to write a technology paper you file a patent you actually go speak at a symposium all that is towards technology effort beyond billable hours.

The percentage of workforce within the company five years ago that did that was at 19%. Today, that number stands at 52 % of our workforce spends time, personal time to go spend time on technology beyond billable hours. And the net result of that has been we used to file 100 patents per year. We have gone from there, sorry, we used to file 50 patents per year. We have gone to filing 200 patents per year. So the point is that so again, summarizing, one, reach out to the local ecosystem and do it and spend the last year with them. That’s the hook in. Second, upskill the workforce within. And third, beyond just money, find a bigger purpose like technology or betterment of human race with technology to motivate your workforce to actually spend time on that.

And I think that’s what we’ve been doing and we think will be helpful. One last thing and we keep discussing India. But if I look at the US today, and I’ve lived there for 27 years now, is we will need schools to start mandating a certain level of STEM education that has to be done. Today, both my boys went to public schools in Virginia. I can tell you that in some schools, it’s broken. And we don’t do that in the US. We don’t do it in parts of Europe. We will continue to look at different countries for skills. And that is not where we want to be in 20 years time. I’m sorry. Jump in. Jump in, Julius.

I was going to agree with what you just said. Because Rapid7, like your company, of course, we’re a software company. We’ve basically mandated the use of agentic technologies by our employees, especially the ones in developing countries or countries that aren’t as developed as the United States. What I would tell you also on the education system, which is unique to the US, which is what makes India special. And that’s why we’re in such a wonderful place. It’s because of the technology. we’re so far behind, we’re forced to use labor in other societies that appreciate the use of STEM technology and where it’s embedded in the way that they learn. We have no choice. If we didn’t have foreign workers in the U .S., we would fall behind the rest of the world.

You don’t hear that too often.

Let me just probe a little bit on this. How much is carrot and how much is stick when you’re looking to upskill the workforce and bring them into more of an AI mindset? You’ve got a very bold program at Microsoft reaching across colleges, but you’re also active, I know, in creating the capabilities within the workplace. How much of this, to both of you, is carrot or stick? I was at a dinner in D .C. a few weeks ago where the head of a large media group had told his team they had to be two times more productive by the end of 25 using AI. to stay in their roles and 10 times more productive by the end of 26.

That was an expectation. But it was set very much as a minimum standard and goal. They were putting training programs in place, but there was a clear metric to achieve. What’s your perspective based on how you’ve seen this work?

You mean internally?

Either within Microsoft or within the companies that you collaborate with in training.

In our experience, I think we are much more leaning in the direction of using CareReds. So we have a lot of programs internally that are a mix, I think, in terms of tactics that’s important. Both kind of like, here’s a day -long training or a week -long training program, right? Which I think is really valuable. It gives you an opportunity to really dig in. But also really difficult. Difficult to find the time for. And so we actually have weekly tips. for how colleagues that are in similar roles are using Copilot, for example, internally to have more efficiency in their work. And I feel like that’s the kind of thing where, you know, is that skilling, is that training?

I don’t know, but it certainly is helpful because that’s the kind of thing that in my day -to -day job I can look to and integrate much more easily. And the other thing that we’ve started doing is hackathon -type exercises internally that are not just oriented towards engineering communities, but actually our corporate external legal affairs group, which is not just lawyers, but is a lot of lawyers, for example, having a hackathon that’s really meeting that community where we are and building a Copilot to serve our kind of day -to -day work. And so a lot of, like, different kind of carrot approaches is what we’re doing internally and where we see, I personally can say, like, I feel especially the latter two, it’s just hard to find, like, time to do a deep training program.

But if you integrate sort of into your day -to -day work, make it easy with these kind of carrots, you can really start seeing the impact, and that motivates you to use the technology more.

So, stick is out of the window, you can’t do that anymore, right? But we use carrots and budgets. Okay? When I say carrots, it’s basically appealing to the individual now and their glorification. So if it’s a patent, you’re filing it. The company doesn’t own it, you own it, right? If there’s a paper, you’re writing it. If you’re speaking at a symposium, you’re doing it, right? And that allows them to think. And then we’ve actually spent a lot of time through HR to try and explain that with the pace of change of technology, if you don’t upscale, you don’t change, you actually are facing extinction in about five, ten years’ time. Gone are the days where you can be there on the same technology for 30 years, will not work, right?

So we home in the message, provide that, and then provide the push. we glorify people that file patents, we glorify them within the company so that’s one. Second when I come to budgets, we actually leverage budgets with our segment heads. So they’re given budgets, they’re given training budgets, we also provide them headcount budgets and say can’t exceed. So we’ve been able to actually improve productivity with AI so we used to run on a utilization of productivity basis the metrics all service companies track at about 73 % five years ago. We’re already at 83 % and I think I can push this up another 2 % in terms of productivity levels in the company again leveraging AI and that’s the budget approach that we use but with the seniors.

So it’s a mix of both if I may to be able to manage this and motivate this. But it’s an ongoing exercise.

It’s fascinating maybe we’ll come back to it as we talk to a close. Let me shift gears a little bit and talk a bit more about security and trust and come to you Julian if I can. So I think we’ve recognized and we’ve heard it in different conversations this week that there’s a trust deficit around the use of AI, certainly in a public context. There is some fear, suspicion, and anxiety in a global context. I’m not talking just about India. YouGov carried out a survey in the U .S. last month, and in the context of fintech, they found that less than 20 % of Americans trust AI in financial services. And they’re also sort of struggling, I think, with some of the cybersecurity questions and issues, which you’re very well placed to address.

So if public trust in AI remains fragile and AI -specific cyber risks are growing, which they clearly are, what are the immediate steps that industry should prioritize to counter those threats? And… Things like prompt injection attacks. How can these solutions be scaled? Thank you. particularly for developing countries?

of seven. So other than the incentives that we’re giving you to learn these technologies, which of course is to the company’s benefit, it’s to your benefit because these skills that you’re learning and that you’re going to be using will translate to the next thing that you do, and it makes you that much better. If we do enough of that, not only are we helping the employees, but we’re helping the societies and the ecosystem that they live in, including in India. I wanted to add one additional area that we’re really focused on to address the kind of AI cyber threats, particularly relevant in India and other areas in the global south. I mentioned that one of the areas that we’re focused on is multilingual and multicultural AI capabilities, and one of the most important foundational reasons for doing that, of course, is that you have an AI that works well.

and in different languages and cultural context is reliable performs well. Another reason is also that AI that is not robust and it’s multilingual and multicultural capabilities does have additional security weaknesses. You mentioned prompt injection attacks and you know one way in which you can think about a prompt injection attack is basically if you have an AI system and you have the sort of safety system around that, someone who is misusing the technology can sort of try to break that safety system or get around it and one of the ways that attackers do that is by using languages that are not well supported in that model or system right so if a model or system is primarily prepared to perform well in high resource languages, but not in low resource languages.

Tamil, for example, or some other sort of language that is not really built in to how the model performs, if companies aren’t attuned to that, then an attacker could use that language and jailbreak the system, basically get around the safety system. And so it’s just another reason why it’s really important from our perspective, and we’re partnering with a lot of others in industry and government, so this comes back to a public -private partnership opportunity, to really work on multilingual and multicultural AI capabilities. One of the things that we announced this week is actually there’s a benchmark from an organization called ML Commons, which is a jailbreak benchmark. It’s actually measuring how robust systems are against that kind of prompt injection attack technique.

And we worked with a number of others to really build out the current version of that. which is really English -specific, to include multiple Indic languages and Asian languages in terms of its capability. It’s not going to solve the problem. It’s one step of what we see in the right direction. But I just want to draw that sort of really specific area of focus in India and other areas for thinking about the kind of AI and cyber threats.

That’s wonderful. Thank you.

Can I add a point?

Sure.

So this is about the rise in prominence of AI agents. And we have been constantly investing in self -defending systems, just like a human immune system. As agents grow and they can – the scale and speed at which they can attack infrastructure, the hospitals, the energy grids, we need agents on the other side. And this becomes AI versus AI story, where we are smartly inventing agents. And we believe, first time, with AI. We can reverse the defender’s dilemma. So the dilemma, many of you might already know, attackers have to find just one open wallet in this crowd, but defenders have to protect all the wallets all the time. And first time, AI will give us aggregate advantage to defenders because majority of defenders’ time, 80%, goes in drudgery and skunk work.

And AI can actually automate and uplift that work. So the entire stack of defenders can improve and uplift with AI. And we believe that we’ll be able to build a self -defending adaptive system which can protect us from various vulnerabilities.

Wonderful. Thank you. Well, we’re drawing towards the close of the session, and it’s been a very rich conversation. I just wanted to take a step back and ask you all, you’ve been – most of you have been here all week. And you’ve heard a whole host of different interventions and some very significant investments and initiatives. What are your conclusions? What’s changed? changed in your perspective when you look at AI for the future from your own vantage point? What’s this event given you a new perspective on or crystallized in your minds? Maybe, let me go back to Lee. Do you want to share your thoughts?

It’s reinforced for me, you know, something I’ve seen through a lot of my international work with OECD, with global partnership on AI, just the need for the global cooperation, and not just at the government level, but among all different types of stakeholders, you know, within academia, within industry, within civil society, and working together. And I think, you know, we can sort of pause at this moment and say, you know, if you look at the safety report, we’ve made a lot of progress over the last few years, but we need to continue to work together and not just focus on the harms and the risks that AI can have, but think about the benefits. You know, if we are able to leverage AI, we might be able to, you know, help achieve some of the UN Sustainable Development Goals.

I think one other thing I want to just kind of enter into the mix, you know, the customization of AI for different regions also depends upon data. And a lot of my work has focused on, you know, how do we create voluntary foundations so we can exchange data more easily? Like right now, we don’t have data standardization. So if I want to exchange my data with any of you, my data may be in a different format. As a former lawyer, a lot of my work is also focused on we don’t even have standard agreements. So if we want to exchange data, how can we easily transact and not have all that friction and transaction costs?

You know, we don’t have the Creative Commons licenses right now for data. And if we’re ever going to get to that localization and that ideal point where we’re customizing for different cultures, we’re going to have to have a lot of different tools. we’re going to have to figure out ways where we can voluntarily and responsibly share data. And this has been part of the discussion, but hearing the conversations over the past week kind of underscore the need to continue to advance that work while we work on some of the other topics that we’ve been discussing.

Great. Julian?

More than anything, what this week has taught me is I’m old and this industry is moving.

Okay, so stop saying you’re old. You don’t look old. You look great.

This industry is moving so quickly. Again, skills that are needed and considered to be important today will no longer be necessary in five years. And if the workforce and if the users of the technologies aren’t evolving with it, we all fall behind. So what is a great advantage and opportunity in using AI, the danger is it also cannot. obsolete at the same time. And we need to be very careful of that and how we use it and then how we help, hopefully, to promote this throughout the world in a way that makes it equitable for everyone.

Great. Thank you. Amit, Sachin, any reflections?

Yeah, I think one of my big takeaway from this week was some parts of the world are focused on AI as an influence. Some part of the world is focused on governance of the AI. I think India is focused on impact of AI at the grassroots level. Thinking about how AI will impact a farmer or a small school or an NGO or a small hospital has been the focus. And it resonates with me because mission of my team is to keep everyone safe at scale. And when I say everyone, it’s not just about Google or Alphabet or not just about our billions users. but the entire society, everyone at scale, and how to make sure we become the architect and not just the consumer of AI and make sure it reaches to the grassroots level is one area to think about.

I agree with that. So, of course, outside of the traffic bit, right? What you learn, if you ask me, in the whole week that I’ve seen is that if I, and I’ve been in this business for, I don’t want to date myself, so say a couple of decades and we leave it there. But people used to say India is a back office. That’s how it started in 90s. People said India is a back office. Y2K happened and they said the IT industry will be over, right? Because Y2K, that’s all there is. Today, the IT industry, engineering industry together is $600 billion. We move forward. People said, are you going to take data? And are you going to?

Is data going to get leaked? and then COVID came and India proved yet again there was not a single data leakage that happened from India Inc anywhere. There are some draconian rules. We don’t allow our employees to use USBs, blah, blah, blue, blue. Net result, zero data leakage, absolute privacy and the government comes down very heavily if they get something like this. So they’ve been able to create a safe environment. Move forward. People used to say is India a market? This last week and forget technology companies, if you just walk the floors, you see people like Schneider, you see people like Vertiv, you see others, they are developing products for India. In India, you’re developing products to the world from India and it’s no longer just a cost base.

So if I was to say there’s one thing that I’ve learned in the last week, it is that India is no longer the back office for AI. it is actually the front office for AI for the world and that’s the net summary that I would draw in the entire week that I’ve been here

Thank you, that’s very funny Bill

And I, you know, zooming out to the sort of highest level, one of the things that I really genuinely felt this week that has been very exciting to me is that there is a lot of energy around how to deploy this technology, how to have impact it’s been actually really fun to be in a lot of sessions with students and entrepreneurs that you can really feel the energy and I feel that it has the conversation around governance has come along and felt integrated in a really genuine way as well, if we look at the kind of summit series that kicked off a few years ago at Bletchley, I think it’s fair to say early on the emphasis of the conversation felt very safety and security heavy last year In France, there was a big pivot to trying to think about the opportunity.

And what I see in India this week is a genuine integration of those conversations and a deepening of those conversations. So really, what do we mean when we say impact? What really do we want to see in deploying this technology? And then sort of not taking for granted that, of course, governance actually has to come along with that. You have to really do the deep, hard work around things like multilingual AI. And there’s a real need for a partnership in moving those things forward. And there’s a real need to think about governance steps so that you can have trust in this technology. India actually just passing a law last week thinking about how to mark AI -generated content.

There’s a real sort of recognition that some of those steps are going to be important. And you don’t want to stop or have those steps sort of prevent deployment of the technology or realization of the benefits. But, like, you know, we have to do the deep work together to sort of move. Forward across a dime. A dime. and impact and governance together.

Thank you. Thanks, Amanda. We’ve got a few minutes. If anyone would like to chip in. Great. Hands are going up. The room’s filled, by the way, while we’ve been going along, and it’s been a great conversation. Let’s hand one or two mics out to colleagues around the room, if we can, to the lady here on the front.

Hello? Hello? Okay. Right. Thanks, and I appreciate the comments and the traffic. I think we’ve all got a traffic story. Now, I hear a lot of talk about upskilling, co -creation, which are all very important things. I agree. But what I’m also hearing a lot from, and I’m sure you all are too, is the issue of speed of this technology that could potentially outspace some of this real scenario. So my question to you is, you know, what do we – and this goes to anyone who might want to answer or has some real thoughts on it. What do you think might – be the gaps between that that we would need to address in a transition process between upscaling and real economic displacement.

Who can grab that? Yeah you put the mic Julian you’re gonna give it a go.

It’s a real problem right meaning technology is moving so quickly as I said years ago I would tell young people in technology learn to be the best programmer you can. Now with agentic AI especially with the usage of MCP where you can have multiple agents talking to each other sharing information it’s now learning to be the best user and prompter of the technology understanding the outcomes but there’s gonna be some displacement. It’s you know right now I would tell you AI especially in the security context I can probably eliminate 60 % of the things that humans have to look at today. but there’s still the 40 % where a human has to be involved to make a determination around risk to an entity, whether it’s a government, whether it’s defense, whether it’s a business.

And so it’s really helping them evolve to this next level of user, this next level of programmer, if you want to call it that. And there probably will be some displacement that we just can’t get around.

Gentleman in the front.

I actually have an extension of the same concern that the lady shared. The speed is one aspect, but also I think there’s a whole information arbitrage between the people who are creating and pioneering in the AI space versus the others to whom the information is reaching. And the impact of that on the power polarization and even the democracies. You know, that possibility I sense. And a lot of the conversation that I hear today is assuming that, you know, AI is moving linearly, but I see it moving exponentially. I agree. With a polarizing effect. Yes. Yes. Both. Both the polarizing effect and the effect, you know, like I think 40 % that Serge just spoke about. For me, that 40 % is not really 40%.

It’s just that we want to be very, very careful. But if we were to not care so much about how accurate and how much data standards we have. It could be 100%. You know, it’s very large. You know, I think the displacement can happen very fast. So I’m really concerned about how things are moving. I’m not sure if my concern is being shared by people in the panel.

Anyone want to respond?

I mean, I think we need to focus on AI literacy because, you know, again, the technology is moving so fast. How do we make sure people in their everyday lives? People in the workforce have access to education so they can continue to upskill. and I also think being in academia after having been in the private sector for we won’t go into how many decades but teaching students how to think I think a good student when you’re looking at your career trajectory it’s not just coming out of college with a set of skills but teaching them how to think, how to problem solve and I think it’s really the public -private partnerships that Amanda mentioned with academia is really important because a lot of times the tenured faculty, they don’t know how to teach that to students and bringing people in to tell them this is how you adapt, these are sort of what you’re going to expect in your career and I say this not only from the perspective of being in academia but having two children of my own in their 20s who are just starting their career and sort of expect the unexpected but learn how to be on your toes I think a lot of it is just having the good analytics skills, having good communication skills and if you have those core skills you’re going to be able to adapt and it will carry forward in the future.

Great. I think we’ve got time for one more question. Okay, gentle. Oh, the lady who, sorry, the lady who has the mic. She has the mic.

Thank you so much. My name is Rita Soni. I work with a company that’s operating in small -town India, delivering all these tech services that many of these companies are doing. And my question is actually for Amanda, because I think she was the only one who really brought up the digital divide that continues to exist, both in India and across the globe. I actually didn’t feel like I heard very much about how to actually bridge that. Yesterday I didn’t have one of those special passes to go to the events on the 19th, so instead I visited a local nonprofit called the Digital Empowerment Foundation, which has been around for more than 20 years, doing incredible work in rural India.

And they’re simply talking about last -mile Internet connectivity, let alone the enablement or ease. in the critical thinking that Lee just mentioned. So just a few more words on how it is that we can bridge this digital divide and make it more equitable, because I think the more folks are going to be excluded, the more different kinds of problems that we’re going to have.

Yeah, and I think you may have come in after we talked briefly about some of the work that we’re doing to address the digital divide. And for a lot of words, I would point you actually to we published a blog on Wednesday where we talked about investments in five areas that we’re thinking about to close the gaps that we see. And we actually point to the work that we’ve done using our own telemetry to sort of track these gaps and their trajectory and really lifted up our own concerns about the trajectory. And so among the areas of investment, infrastructure is really foundational. And we actually do talk in the blog about of course, infrastructure in terms of like AI.

compute capacity, but actually the fundamentals beyond, like, in terms of connectivity, energy access as really important as well. And then we talked about scaling multilingual and multicultural AI capabilities, really working with local communities on local use cases and the kind of deep work that we can do to sort of help bring the technology to people and see, like, even in agriculture, for example, we at Microsoft Research have done a lot of projects, like, in close collaboration with local communities and try to see, like, how could this serve you and then also learn from how the technology needs to evolve in order to do so better. And basically then also taking a step back and continuing to study diffusion so we understand, like, are our interventions working?

Are they not? If so, what can we learn and how can we improve how we’re intervening?

Okay, so time’s up, everyone. Thank you so much for your contributions and for joining us at different points during the conversation. Thanks to the panelists for a really rich and diverse conversation. It’s been a real pleasure to have you with us. And I think we end with a sense of optimism that no matter what the challenges of the digital divide and those other elements, there’s probably an AI solution to the AI challenges that we’re creating. Thanks. Thank you. Thank you.

that the race towards artificial intelligence is no longer a theoretical pursuit. As billions and maybe trillions now of dollars are getting deployed to push the frontier of artificial intelligence, the technology is now advancing rapidly. And safety is not keeping pace with it. There are wonderful opportunities on the other side of this quest. There are also big risks. And so that’s the purpose, that’s the reason AI Safety Connect was founded. AI Safety Connect is there to help shape the frontier AI safety and secure agenda towards what I would frame as commonsensical AI risk management. AI Safety Connect has been founded to encourage global majority engagement into frontier AI safety. And AI Safety Connect, has been connected to showcase Concrete’s governance coordination mechanisms, tools, and solutions.

So how we do this? We convene at each AI summit. So last year we started in Paris, this year in India, next year we’re going to be in Switzerland. But we also convene at the UN General Assembly, right? We need a faster tempo for these safety discussions, so every six months we have this global convening. We also do capacity building, and we also do trust building exercises at times behind closed doors. Well, this week in New Delhi has been an intense one, an impactful one. On Tuesday we had a full day of panels, conference, solution demonstrations, and closed -door workshop discussions on some specific nuts to crack to advance AI safety. We, for example, at the privilege of, hosting Prime Minister Dick Schuh from the Netherlands on stage to deliver a special address on the role of top leadership in advancing AI safety.

We also engage with industry, engage with academia. of India and abroad. So we’re an extremely busy week beside our main event. We had this closed -door discussion that I was mentioning yesterday and today, this closed -door scientific dialogues. We’re going to publish the results soon that brought together senior industry leaders to discuss shared responsibility for AI safety. Well, obviously, none of this would happen without partnership. And we want to thank our co -hosts, the International Association for Safe and Ethical AI and its director, Professor Stuart Russell, to whom I will hand over the floor in a few minutes, and the Digital Empowerment Foundation who is anchoring us at the grassroots here with Osama Manzar,. We’ll close the session later on.

And we obviously want to thank our sponsors and supporters, starting with Sympathico Ventures. Eileen Donahoe will moderate that panel and we’re thankful for that. The Future of Life Institute, Ima and Yann, who’s been supporting this effort, and the Mindero Foundation, whose team is here as well with team. And it’s great to have your support and we are thankful for that. So today we’re about to hear from His Excellency Matthias Korman who’s the Secretary General of the OECD We’re going to hear from Her Excellency Minister Josephine Theo who’s the Minister for Digital Development and Information at the Government of Singapore. Thank you for your continuous support, really appreciate that Same for Jann Tallinn who’s the AI investor but also a founding engineer at Skype and the co -founder of the Future of Life Institute And last but not least, we also have Minister Teo who’s going to be with us from Malaysia Minister for Digital Development and Information Thank you Minister as well as Vice President Kim for Digital and AI at the World Bank So an extremely important conversation to have And before we welcome you to the stage I would like to hand over the floor to Professor Stuart Russell to say a few words and to speak about also what’s happening next week in Paris Thank you so much.

Thank you very much, Cyrus and Nico. So as Nico mentioned, the International Association for Safe and Ethical AI, or ICI, the world’s worst acronym, is a global, democratic, scientific and professional society. We have several thousand members and approaching 200 affiliate organizations. Our mission is to ensure that AI systems operate safely and ethically for the benefit of humanity. And as Nico mentioned, our second annual conference will take place in Paris starting on Tuesday. It’s still, I think, possible to register, but we’re already up over 1 ,300 people coming. It’s at UNESCO headquarters in Paris. Thank you. So achieving this mission of ensuring… that AI systems operate safely and ethically is partly a technical challenge. How do we even build systems that have that property?

But also a governance challenge. How do we ensure that those are the systems and only those systems get built? And this panel is mainly about this second challenge. And I think it’s one on which global coordination is essential because the harms, whether it’s psychological damage to the next generation or loss of human control altogether, those harms cross borders. And we must coordinate to make sure that they don’t happen or they don’t originate anywhere. And it’s, I think, fitting that we are having this summit here in India, which has really, among other things, championed the idea that everyone on Earth should have a say. And so with that, I will hand over to Eileen. Thank you very much.

Thank you, Stuart. So Dr. Eileen Donahoe is the founder and managing partner of Sympathico Ventures. She’s also the former U .S. Special Envoy and Coordinator for Digital Freedom and Ambassador to the UNHCR. Eileen? Welcome the speaker on the floor. Please, Your Excellency, Mr. Mattias Korman, Mr. Gobind Singh Deo, Mr. Josephine Teo, and Mr. Jann Tallinn, as well as Mr. Sangbu Kim, join us on stage.

Okay. Given this remarkable panel and the very short time we have, let me very briefly frame our discussion and get right to our speakers. So we’re here to share. Views on the opportunity for policymakers to impact international AI governance. As the race towards AGI and superintelligence intensifies, AI safety advocates face a compounding challenge. The technology is advancing rapidly and being deployed with minimal guardrails, while the risk management processes that do exist are either ill -adapted to the magnitude of the risk, fragmented across jurisdictions, or insufficiently binding on developers, deployers, investors, and regulators. The result is an unharmonized governance landscape that fails to shape the behavioral incentives. Of those building and funding frontier AI. Economies, governments, and societies do not respond well to such mixed signals.

While much of the discourse on frontier AI safety has focused on AI superpowers, there’s an urgent need for deeper international diplomacy on the most… extreme risks. At this juncture, middle powers and global majority states can’t be seen as peripheral actors in this landscape. Through pooled resources, market leverage, normative influence, and regulatory innovation, they can shape the direction of global AI practices and safeties. Leading from the middle may turn out to be a more powerful approach than previously anticipated. Whether or not that collective power is exercised now will determine whether international AI governance moves from the rhetorical level to the real -world impact on safety. This panel will aim to identify present -day coordination gaps in the global AI practice and the global market.

We will also look at the role of global AI in international AI safety and highlight practical steps policymakers can take in the coming months to close them. So to our panel, I’ll start with Secretary General Corman. The OECD has done remarkable work over the past decade, developing consensus on the OECD principles, providing a definition of AI systems that has resonated internationally, and playing an international role in operationalizing the Hiroshima International Code of Conduct. Along with those foundations, we now have the International AI Safety Report and the Singapore Consensus on Global AI Safety Research Priorities. With these principles, definitions, and frameworks in mind, two -part question for you. First, what are the key lessons learned from the process of building consensus and then implementing these frameworks?

And then second, looking ahead, what’s the most critical? What’s the most critical piece of coordinated frontier AI safety infrastructure we should be building now? Some have called for an international incident response center, and we’re all curious whether you think that should be a priority and achievable. Just some small, easy questions.

In terms of what is the key to success, what is the most important lesson on looking back on what we need, trust is built through inclusion and on the basis of objective evidence. And, you know, I think what we’ve learned over the last few years is that bringing together all the relevant actors, governments, companies, civil society, technical experts, is what we need to do. I mean, each has a different perspective and different imperatives. I mean, markets reward the private sector for speed, scale, and innovation. While governments must manage risk and protect the public interest without stifling progress. But a challenge, and it’s been mentioned in some of the opening remarks, a challenge for policymakers in this context is that AI is moving much faster than policy cycles have traditionally moved, which easily then creates gaps between innovation and progress and opportunity, but necessary oversight, mitigation and management of risk.

But all sides in this conversation do share an essential common interest, and that is to ensure that the systems that are developing are trustworthy, because without public trust in the end, even the most powerful AI tools will struggle to gain broad adoption. So that means that occasionally, and it’s not always popular with everyone, but occasionally we should slow down. Occasionally we should actually pause. Pause, test, monitor, audit, share information, and take the time and invest in building confidence that these systems can work as intended and respect fundamental rights. So that’s sort of, I guess, the first point. another critical lesson involves international consistency and this is part of the reason why these sorts of summits are so important is to really facilitate these conversations among countries and among different jurisdictions because national priorities can vary quite widely and there’s of course fragmentation and compliance cost related risks and at the OECD really what we’ve been doing for six decades now across different policy areas is to try and reduce fragmentation and by achieving alignment around key principles, building shared evidence and facilitating the necessary conversations to develop a more coherent better coordinated approach moving forward and on AI I mean we’ve developed the OECD principles which were first adopted in 2019 and which are now adhered to by 50 countries around the world and that was really the first globally recognized baseline for trustworthy AI The OECD’s lifecycle definition of an I .I.

system has since shaped policy frameworks from the EU I .I. Act to U .S. executive orders. And we’ve had just earlier the meeting of the Global Partnership on I .I. co -chaired by Korea and Singapore. We’ve got the OECD I .I. Policy Observatory, which is sort of essentially the broad gamut of all of the different policy approaches around the world to provide countries and industries with data and evidence on what’s being done, facilitating peer learning, and trying to take some of the politics and the rhetoric out of it, but really looking at the facts. Now, looking ahead, and you sort of ask a question here about what to do about the risk. I mean, the most critical piece of frontier I .I.

safety infrastructure is coordinated. transparency and incident reporting. I mean, the Hiroshima I .I. Process Code of Conduct and its reporting framework launched at the I .I.’s Action Summit in Paris last year. You know, that’s a promising step, and we’ve got to continue to develop that. Since their publication, 25 organizations across nine countries have already submitted detailed reports on how they manage I .I. risks, offering for the first time a comparable view of developer practices across jurisdictions. The next stage is to strengthen information sharing on I .I. failures and near misses. The GPI I .I. Common Framework for Incident Reporting aims to help us collectively learn from mistakes before they scale globally, and over time, this could evolve into an international I .I.

Incident Response Center, coordinating alerts between governments and labs without exposing companies to commercial or legal penalties for reporting in good flight. Finally, we do need to scale access to practical safety tools. With global partners, the OECD recently launched an open call for open source safety and evaluation tools hosted in the OECD .ai catalog of tools and metrics to make a trustworthy AI easier to implement in practice. I mean, these are some initiatives to form the foundation of a more transparent, data -driven, and interoperable AI governance ecosystem, and

Excellent. Minister Teo, a number of questions for you, but let me start with the fact that Singapore occupies a very distinctive position in the global geostrategic landscape as a pro -innovation, advanced knowledge economy, with deep commercial and diplomatic ties to both the U .S. and China. Thank you. As the race to AGI intensifies and bilateral tensions mount, is there a role for Singapore and other middle powers to play in bridging the coordination gap to keep scientific and safety channels open? And also, what’s the most important step middle powers can take in the next 12 months to help establish a shared minimum understanding of frontier safety?

Well, thank you very much for that question. I think there is no running away from the fact that for smaller states, and that includes Singapore, the technology that our companies, our citizens are going to rely on do not originate from our shores. So they don’t necessarily come within our jurisdictions. We don’t always get to set the rules. Having said that, I do believe that we’re not without. Thank you. agency. It doesn’t mean that we take a step back and just let things happen to us. There are still things that we can do. One of the most important things I think as policymakers is for us to think about what it takes to translate what we know from science into policy.

And I wanted to just say why this is so important. In our case, as policymakers, the key questions will always be, are the policies that we make effective? And also, policies always come with trade -offs. With the question of effectiveness, there is always a need to understand what actually works, as opposed to what looks good on paper. With the question of trade -offs, it’s about understanding what we lose as a result of whatever safety aspects it is that we choose to put in place. And whether we can minimize them, can we mitigate them? Now, in areas where safety is the objective, we can’t just go with gut. We can’t just go with speculation. You take, for example, in my previous life, I was working on promoting Singapore’s Air Hub.

And we had to deal with a question of aviation safety. We were expanding our airport. It was going to carry many more passengers in and out of the country. But we are limited by number of runways. And in landscape Singapore, you can’t just click your finger and say, let’s build a new one. It’s a long runway. It’s very expensive anyway. Then there is the question of what do you do when you have these jumbo jets like A380s? Because each time an A380 hits the runway. It creates so much of a blast that you really need to create more distance between the A380 taking off and the next aircraft that is scheduled to take off.

Now, this is not a question that the transport minister can just decide on a whim. The air traffic management has to decide on its policy of how much distance is considered safe between landings or rather between takeoffs. And to answer this question, you really need to invest in the research. You need to invest in understanding the tests. So the science is one part of it. But between science to policy, you are actually going to need a lot of time. You are going to need a lot of tests. You are going to need a lot of simulations. you need to understand whether the distances that you decide are safe works well in a thunderstorm, a tropical thunderstorm.

Does it work just as well in a snowstorm? Well, we don’t have snow in Singapore. But you think about the airline that operates this. If each country that they fly into has a different safety distance, that creates some difficulty. So we therefore think that not only is there a need to invest in understanding the science, not only is there a need in understanding what testing looks like, what good testing looks like, there is also a need for us to think about what standards that will eventually be interoperable, what do they look like, which is why we think that international efforts, the collaboration that… that is being carried forward by the OECD through the Global Partnership on AI, the AI Safety Connect effort, and also ICI.

Where is Stuart now? Those kinds of efforts, you can’t do away without. At the outset, there is likely to be a bit of a fragmentation. And the trade -off with not having these conversations is that we are not even going to make advances in AI safety. And I don’t think that that’s a very good place for us to be in. It doesn’t give us the assurance that we can deliver to our citizens. And it does not create a foundation of trust that will eventually help us to push ahead with the use of this technology on a wider scale. So that’s how we are thinking about it, Aileen. Thank you.

So let me turn to Minister Gobind from Malaysia. and note that under your leadership and Malaysia’s 2025 ASEAN chairmanship, Malaysia succeeded in placing AI at the center of ASEAN’s agenda by establishing the ASEAN AI Safety Network. Malaysia is now finalizing its own AI National Action Plan, and Malaysia’s AI Governance Bill is expected in Parliament in 2026. So this dual -track approach of building national capacity while leading regional coordination represents a model of middle power agency that other countries are watching closely. So what lessons do you think other middle powers can draw from Malaysia’s experience? And on the ASEAN AI Safety Network, we have to note that operationalize and it will require sustained political will. technical capacity and resources.

So what concrete steps must ASEAN take in the next 12 to 18 months to ensure that this isn’t just aspirational?

Online fraud, for example, scams, you have deepfakes today, you have huge concerns about certain vulnerable groups that are going to be impacted, children, older folk and so on and so forth. So this is something that stretches across the region. How do we deal with it in a coordinated way and ensure that the conversation doesn’t just stop with the government of the day, but it’s a conversation that expands over a period of time with clear policies that we can actually execute. The second layer that I think we need to think about is in the event there’s a need for execution. When we speak about risks in AI and we speak about how we’re going to govern these risks, we often talk about standards.

We often talk about regulation. We even speak about legislation at times for areas that pose higher risks. But ultimately, it really comes back down to you making sure you have an agency that can enforce it, because you can have the best standards. regulations and legislation but if there is no institution that’s really able to implement those standards to ensure that they are properly implemented and also to ensure that rules for failure to implement are enforced then those standards regulation and policies are really going to be just strong on paper but they’re not going to really have that impact that you need. So again, how do you build this mechanism across ASEAN where every country strengthens themselves domestically first and then moves across to the ASEAN member states and hopes to learn from their experiences so that we can together move ahead in this new world of AI and I think the threats that we anticipate in future.

Now the third part which is really important is also ensuring that whilst this goes on, you create those policies, you have institutions that enforce and the discussions persist at an ASEAN level. I think what is important is also to have that expertise looking at what comes next. We must make sure that our countries are prepared for the risks that are to come with the next generation technology. This is important because you don’t want a situation where new technology is adopted and there are risks that come with this new technology, you’re not prepared. I think that’s something we want to avoid and that’s the reason why I come back to where I started off. We really need to look at building institutions that have the expertise and of course are able to sustain as we go along and to build and deliver something that’s impactful.

Sorry, but that’s in short what we’re doing in Malaysia today.

Excellent. Thank you so much. Okay. Let me turn to Vice President Kim and talk about the World Bank, which has been at the forefront of digital public infrastructure, helping countries leapfrog legacy systems. We note that frontier AI systems, though, are arriving in the global south under very different conditions from previous waves of technology and governments are under pressure to deploy AI systems quickly. often using models that haven’t been adequately tested, let alone certified for their context, languages, or risk tolerances. So how can the World Bank help Global South countries move from being passive recipients of frontier AI to active shapers of safety and reliability requirements before the systems are deployed at scale?

Thank you. In one word, definitely we need to make our clients well prepared from the scratch. When they design the AI systems, definitely they need to design the safety architecture within the system. That’s very, in general, that’s very correct. But real challenge is that… nobody can really expect a new type of new threat especially our some countries in a low capacity it is really hard to figure out what that will be so that’s the in order to tackle that type of irony and dilemma we need to very closely working with very developed economies company and government and very high end examples so that we can really well connect those good examples to the developing world so one partnership is one of the good examples we are helping our country for example some big tech company who is running some red teams so that you they are trying very hard to attack their system in advance by fully utilizing AI.

So through that type of practice and experiment, they can learn how to prevent the AI attack in the future, which is pretty much possible. So in this way, it is inevitable for our developing countries to keep track on the new trend and new innovation, even in this safety protection area. It is the only way. So I have to admit that this constraint. But think about this. Some anecdotal story in East Asia, in China and in Korea, there’s two models. Merchant who is selling two products. Number one is. sphere. And then they keep saying that this sphere is so strong so it can get through any kind of shield. So this is one vendor. The other vendor is selling shield.

And then they are saying that this shield is one of the most safe and strong shields. No sphere can get through this shield. This is exactly an ironical situation. If you think about AI, AI attack is the sphere. AI is so strong and smart and really capable so it can get through and hack any system with high -end intelligence and knowledge. But good news is that on the other hand, we also can build strong protective systems. by fully utilizing AI. So this is one good news, but the constraint is that we do not clearly know how AI can really evolve to fully protect those big attacks in the future. So in order to solve this type of ironical situation from the developing world point of view and from the World Bank point of view, this is the only way to very closely work and collaborate and learn from the advanced technology and advanced company and advanced country.

Thank you so much. Last but not least, Mr. Jan Tallinn, you occupy a very rare position in this landscape as a founding engineer of Skype, an early investor in DeepMind and Anthropic, and you’re also the co -founder of the Future of Life, which last October released a statement on superintelligence. calling for prohibition on superintelligent development until two conditions are met. Number one, broad scientific consensus that it can be done safely and controllably, and second, strong public buy -in. Let’s just ask the hard question. What would an effective prohibition look like in practice? How could that work?

Thank you very much. So I think I’m kind of like a little bit different from the people on this panel. And that too, I guess. That I’m kind of, my main kind of threat vector about, my main worries about future are less about like how AI is being deployed and diffused and taken into practice. And I’m way more worried about what is happening in the labs, in the top AI companies. I’m not sure what the future is going to look like. because they are now in a cutthroat race to build something that is smarter than they are. They are in a cutthroat race to build superintelligence. And, like, I mean, we just saw yesterday the picture where, with a photo of it, Narendra Modi, Dario Amadei, and Sam Altman refused to link hands.

I mean, this is, like, indicative. We also saw both Dario and Demis Hassabis call for a slowdown in Davos last month. They just can’t do it alone. And I think there are, like, two reasons why it’s, like, an unfortunate situation. One is that the U .S. as a country is conflicted. They basically rely on AI for their economic and competitive power. So they are, like, very hesitant to, kind of, meddle with now. cutthroat situation in AI companies and the rest of the world really doesn’t understand how big danger they are now. So it’s part of the reason why we did the superintelligence statement is to create awareness that there is increasing political demand to do something about this situation.

We now have more than 130 ,000 signatures which is like many times more than we had done our original six months post letter had in 2023. So yeah, that’s like if there was enough pressure, I think clearly like the rest of the world is still kind of more powerful than the kind of leading AI countries. There are more people, there’s more economic power, etc. So if there was like enough pressure this could be solved. Like the way I put it is that it’s super hard to do like a $10 billion project. it’s impossible to do it if it’s illegal. So having these trillions flow into AI actually makes it easier to govern than harder.

So I’m tempted to follow up with a question about investors and their potential role in this. They are obviously playing a decisive role in shaping the incentives, but they’re largely absent from the governance conversation. So what would it take to bring investors meaningfully into the safety conversation?

So, yeah, I think the answer is kind of simple. I don’t think investors play much of a role anymore because the leading AI companies now are kind of above the level where private investors can influence them. They will now IPO soon. And if you are like an IPO market, there is… like, like, so level playing field, which means that like, if somebody’s not funding, somebody else will. So I don’t think investors, investors could have affected things, but like, five, 10 years ago.

Great. Okay, so since we’re running short on time, I’m going to ask one question, and ask you all to answer it, which is about the 12 month window. Oh, the very shortly, each shortly. Many in the AI safety community believe we have a narrow window, perhaps 12 to 24 months before frontier AI capabilities advance beyond our ability to evaluate and govern them. So what would you recommend is prioritized between now and we’re basically in the next year to two years, each of you to enhance safety? and security?

I think there are two, really. I think the AI safety research priorities need to be refreshed because the field has moved so quickly. The Singapore consensus identified a set, but as soon as they are published, we recognize that they will be out of date. So we need to refresh it. That’s why we’re going to have the second edition, you know, worked on. Hopefully in a few months. The second thing I think is that we can’t just keep thinking about frameworks, you know, and guidelines. At some point, we need to be able to introduce better testing tools. And until we are able to do so, the companies that are developing and deploying AI models, they also don’t have a very practical way of giving assurance.

So I’d like to see in the next 12 months some further advancements. In those two areas.

I’ll be really quick I know there’s always a temptation in these sorts of conversations, what is the one thing that can sort of fix it all and the truth is there’s not one thing we’ve got to go as fast as we can to play catch up to a degree but we’ve also got to go as comprehensive and as deep as we can there’s just no alternative, there’s catch up to be played, we’ve got to put a real effort and it’s got to be right across the board and I don’t think that you can just say there’s the one thing that will make us all safe and it’s going to be okay.

Minister Gobind?

I think as I said earlier, we need to start thinking how we can build structures and perhaps institutionalize this entire conversation about building security around AI and its governance in this regard, we have to understand that things are going to move very quickly and you’re going to see new technology develop very fast which brings new risks as well, so in that regard, you’ve got to build something that’s sustainable and I think in order to do that, institutionalizing it should be a priority.

everyone is really rushing for ai system development ai solution development that means ai is currently ai safety measures currently under invested so i really like to urge all of us to think about this is not free you know things we need to spend some money to protect the system in advance from the scratch when you design the system so that means we should allocate some money to fully invest in in the

Jann Tallinn?

so slow down we really need to slow down that the companies are asking for it and if we like instrumental to that would be basically transparency like more people should know what the leaders of ai companies know in order to basically understand how crucial the slowdown now is

okay great well i believe we have a little bit of a close coming and thank you all so much i wish we had had a day to talk about all of these issues. But thank you so much. Thank you very much.

Thank you very much, Eileen, and this fantastic panel, excellencies, colleagues, friends. What we’ve heard today confirms something important. The coordination gap frontier in AI safety is real, and it is urgent. And as we’ve discussed today, it is closable. And before I hand over the floor to Osama Manzara to close off for a few minutes of remarks and reflection, I’d like to invite you all to the United Nations General Assembly next edition in New York, where we hope to organize the fourth edition of AI Safety Connect, and hopefully with many of the great policymakers and leaders we have heard from today, to carry forward that collective effort. Osama, the floor is yours.

Well, thank you very much. And we are one of those absentee co -organizer in this one. So, you know, because being a local, but I just want to I mean, apart from thanking each one of you who didn’t get up and, you know, go out of the room. And every one of you who gave all the safety remarks before usage of AI on behalf of 40 million people that we have reached out in the last 23 years. And billions of the other people whom we are going to work for. I want to suggest that the entire safety aspect of AI should be more from please save people from AI. Right. Because that’s the safety like it’s a car on the road.

You know, we have to save people before you teach people how to think. So we also have to keep a very, very strong thing. How do we save human intelligence from artificial intelligence? And how do we inbuilt in the safety guards and all the ethics and all the all the, you know, policy playbooks? Thank you very much. Thank you. Bye. Thank you. Thank you.

and resilient supply chain in these critical areas of technology which the world needs.

And that’s actually a great segue to shift to Ambassador Gore, who just arrived in India with a bang. Ambassador Gore, could you help us understand your vision for the opportunities that you see to deepen U .S.-India technology collaboration? Thank you.

Thank you, Jacob. Jacob, look, liberalist potential, those are the two words. And I truly mean it. As I’ve started traveling around this country, and I’ve been to multiple states already, what I have seen here, it’s such a natural partnership. And what the United States has with the best technology and with the innovation that we see here across India, this is a natural partnership. The President and the Prime Minister have a special relationship, and I mean that. And that goes a long way. And I think that’s a great point. I think that’s a great point. I think that’s a long way. You have great elements here in the sense of the technology, in the sense of the innovation.

and in the want. India wants to get involved. But also the magic touch is that special relationship between our two leaders. It’s a friendship that goes back many years. And for those colleagues of mine from Washington to understand the difference that it makes when our president likes you or he doesn’t like you. And with India, our president really, really, really likes the prime minister. And so that makes a huge difference for the next three years. Not only the administration, but the White House itself is open to engaging India. And one of those areas where we can further this to a record is this AI. It’s the technology sector. And so that’s something that I’ll be focused on over the next three years.

Thank you. Sanjay, could you help us understand a little bit, what does the partnership between America and India mean for the security of the supply chains of a company like Micron? Which obviously operates on a global scale.

First of all, Jacob, let me just say congratulations on this India and U .S. Paxilica signing today. This is certainly a tremendous initiative and wonderful to see the collaboration between the two great countries on the technology front, semiconductors, and, of course, resilient, secure supply chains. Micron, as I was mentioning earlier, a global memory and storage leader. And, of course, Micron is headquartered out of U .S., an American company, and Innovation Powerhouse, 60 ,000 -plus patents. We are here in India. We have R &D facilities here in India, absolutely contributing to leading -edge memory design. I should name Secretary Vaishnav earlier. Earlier. We earlier talked about two -nanometer designs. In memory, the most advanced designs in the world are also taking place here in India.

very much in collaboration with our teams in the U .S. So it’s an example, good example, of how we are advancing AI forward. Memory is a critical enabler of AI. Just think of it this way, that if, you know, AI is driving, is the growth engine of the digital economy, then memory is the fuel. And that fuel is being, you know, really developed, is manufactured between collaboration between U .S. and India here with R &D teams here, but also manufacturing. And that’s an important piece with Micron performing assembly and test operations here in the Sanand, Gujarat facility with investments, with the support from the Indian government, with $2 .75 billion of investments, with time that will result in, hundreds of millions of chips assembled and tested here.

And that complements Micron’s manufacturing plan. in the U .S. Actually, as you look at our manufacturing plants in the U .S. on the silicon side, as well as advanced packaging side, the work we’ll do here will complement that. It will add to it. It will contribute to it in terms of AI in manufacturing, in terms of automation in manufacturing, refining and making workflows related to manufacturing more efficient. This will be a win -win partnership with Micron’s investments in the U .S. getting the support and all the learnings of large -scale manufacturing of assembly and test operations here in India as well. So we are really looking forward to it. And it’s initiatives like Paxilica absolutely ensure that there is successful supply chain resiliency and security built in to continue to build the AI infrastructure and advance the technology.

And it’s

Thank you. And Dr. Thakur, could you help us understand a little bit better the special connection between heavy data center investments and edge technology like smartphones and connected vehicles, especially in emerging markets?

Well, thank you very much. And I first want to really congratulate on Paxilica at a personal level. It’s very exciting. We are doing this between our two countries. Truth be told, for my PhD, I went to Oklahoma of hot places. You know, so I’m a sooner and pretty soon I realized that football, I don’t have chance to do silicon, you know, so I worked on silicon. So, but you know, the key is that first transistor built was really built on germanium produced near Oklahoma, germanium transistor. Until we switched to silicon and thank God we did and Shockley made the first transistor in Bell Labs and rest is history. So our industry has always been dependent on this material engineering, ability to work these minerals, deploy them into making the chips.

And as far as the question about data center, I think the enablement of the data centers or AI is hardware driven. Because AI was known long time, but the hardware was not ready. Our ability to compute was just not there. And as you have said, Undersecretary Halbert, that the 20th century ran on oil and steel. The 21st century runs on compute and the minerals that feed it. That is so true. So packed silica is just such a timely change. For us in India, the innovation and the drive we have is tremendous. 1 .5 million engineers are produced every year. 20 % of the global semiconductor industry. 20 % of the global semiconductor industry designed. is done, the chip design is done by Indian engineers here in India.

And we never really had any non -coercive issues in the design space. So I think this is a very, very natural fit. In terms of the progress we are making, I think three years ago, there was no investment in India on the semiconductor side. Today, we have more than $25 billion being invested in 10 different factories, including Micron and Tata Electronics. We are working on the first AI -enabled fab that will be producing the AI -specific chips in India. We are using the indigenously developed packaging technology in Northeast Assam, where we’ll be packaging all of the automotive and other chips that are at the edge, being done for the U .S. companies. Partnership -wise with the U .S., because semiconductors brings us together, we are working with companies like Analog Devices.

Qualcomm, Synopsys, and Inter, where we have memorandum of understanding to work together. to deploy the ecosystem. Sometimes we are the customers, sometimes they are the customers. So at a holistic level, that engagement moving extremely well. On mobile phone, we are producing now, I think this year India produced mobile phones worth $70 billion in the last year, $30 billion of which were exported out. So there is just tremendous push all around in terms of manufacturing. And this initiative today, I really believe it’s going to bring and accelerate the momentum that we already have. Thank you.

I want to end by zooming out and asking a question for all of our panelists that’s a little bit more macro. And as we gather here in India in front of world leaders and business executives, and as the global economy undergoes this incredible change driven by the reorganization of our supply chains and the AI revolution. What is your message to this? And maybe we can start with Secretary Krishnan and work our way down. The message

to this audience is that we need to align and ally on lines which really work for people who share values, for countries that share values, and to ensure that we do not become enslaved or do not become tied down to just one dependence. I think that is the critical thing. That is what we learned. Through the pandemic and through all the geopolitical upheavals. And therefore, we need to have trusted partners with whom we can work and trusted value chains so that technology can work for all of us in organizing this India AI Summit. I think what we have truly managed to do is to democratize an important element of technology. The people have been let into the room, and that needs to continue through.

valuable partnerships.

Thank you. Ambassador Gore, you talked about limitless potential earlier. Can you give us a little bit of a color on what your main top -level message is to this audience?

Look, the message is the AI revolution is here. People can pretend it’s not. It’s coming. And so it’s one of those things, the sooner that people can adapt to your point, the sooner that people can partner with like -minded individuals, that’s a good thing. And so you find in some places of the world, not India, but in other places of the world where they’re going to resist AI, where they’re going to resist this revolution, it’s here. It’s here to stay. Every hundred years, every so often, we see in history something that changes the world. And you always have a sector that resists. When Ford had the first Model T come off the assembly line, the first people that protested were those in a horse and buggy.

But today, nobody would want to go back to a horse and buggy. They would want to go back to a horse and buggy. They would want to go back to a horse and buggy and give up their cars. That revolution came, whether you like it or not. And the same thing is going to happen here over the next few years. And so India and the United States being at the leading, at the cutting edge of this new technology, embracing it, using it for good, and partnering with those who share our common values. We’re the world’s oldest democracy. This year we’re celebrating 250 years. India is the world’s largest democracy. This is a national partnership for both of our nations.

Thank you. Sanjay?

Micron’s vision statement defined several years ago now is transforming how the world uses information to enrich life for all. And that vision is truly coming to life today. This AI summit, the message of Sarvajan Hittai and Sarvajan Sukhai, welfare for all, happiness for all, is very much aligned. with Micron’s vision. U .S. vision for AI in terms of national and economic security, and, of course, the businesses and the global leaders around the globe working toward AGI, artificial general intelligence, all of this critically relies on memory and storage, and Micron is very proud to be at the center of it. More and more memory is needed. Micron is making the investments in order to increase the supply.

But it’s not about just the importance of memory and storage to advancement of AI. It’s not just about investments that Micron is making in the U .S. to advance semiconductor supply chain as well as in India and other locations, but it is also absolutely about initiatives like Pax Silica, that really secure the future of supply chain. and ensure that AI infrastructure and AI capabilities will be there ready to shape the world of the future. We are very proud to be part of this, very proud as an American company to be able to bring up advanced technology capability here in India, which will benefit our U .S. operations as well, and very thankful to the partnership between U .S.

and India to jointly together define the future of AI and shape the future of the world.

Thank you so much. Dr. Thakur, any closing thoughts for the audience?

Well, thank you very much. As our Tata Sun chairman, Mr. Chandrasekharan, said yesterday, under the vision of our prime minister, India has treated AI as strategic national capability. So I see. I see the declaration of Pax Silica as a response and an enabler, a codification of trust, and for us. the opportunity to work together. The expectation is laid out from the nations. It is now up to us to deliver on this promise as an industry. So, Honorable Undersecretary Helberg, Ambassador Gore, I really want to thank you from bottom of my heart for Paxilica. We’ll make it work. Thank you. Thank you so

Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. you you Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. you you Thank you. Thank you. you you Thank you. Thank you. And this is the panel partnering on American AI Exports Program. First, I take this opportunity to welcome Mr. Michael Kratios for the keynote remarks to kick off this session. Michael Kratios is the head of delegation for the United States to the India AI Impact Summit. And also, he is President Trump’s National Science and Technology Advisor and the Director of the White House Office of Science and Technology Policy.

Ladies and gentlemen, please welcome Mr. Michael Kratios.

asked to choose between completing the stack and developing a domestic AI, we have established a national champions initiative. We recognize that partners need a chance to build their native technology industries and believe facilitating this will be a critical part of the export program. To facilitate the development of industry -led, open, and secure AI standards and to give the public confidence in this next generation of technology, we are creating an AI agent standards initiative. To empower developing partner countries to overcome financing obstacles as they import the American AI stack, the U .S. International Development Finance Corporation and the Export -Import Bank of the United States, the U .S. Trade and Development Agency, the Millennium Challenge Corporation, and a new World Bank fund have initiated new AI -focused programs.

And to further enable AI adoption in the developing world, the Trump administration is bringing America’s historic Peace Corps into the 21st century. with the launch of the U .S. Tech Corps. This initiative will embed volunteer technical talent with import partners to provide last -mile support in deploying powerful AI applications for enhanced public services. In everything from energy and education to manufacturing and medicine to transportation and agriculture, I’m confident that the American AI stack can be key to unlocking new economic and social benefits for your people. The hope of the United States is that the pursuit of real AI sovereignty, the adoption and deployment of sovereign infrastructure, sovereign data, sovereign models, and sovereign policies within your borders under your control will become an occasion for bilateral diplomacy, international development, and global economic dynamism.

The American AI Export Program exists to make that happen. The U .S. wants to share the American AI stack because this technology presents the opportunity to lead. as our nation’s founders did 250 years ago, a revolution in human history to the benefit of all of mankind. These tools used well will unlock new knowledge for our growth and new sources of prosperity and challenge us to grow the strength of our humanity to match our growing capabilities. American AI is settling a new frontier, but America does not seek to build this new future alone. So I ask you to join us. Thank you.

Thank you so much, Mr. Kratios, for your ideas, your remarks, which are truly enlightening and illuminating as well. Ladies and gentlemen, next I would like to invite the speakers for a panel on partnering on AI exports. Interesting, isn’t it? Well, the moderator is Mr. Sriram Krishnan, the Senior Advisor for Artificial Intelligence at the Office of Science and Technology Policy, and the panelists are Department of Commerce Undersecretary for International Trade, Mr. William Kimmett, and Department of Commerce Deputy Undersecretary for Policy at the International Trade Administration, Mr. Brendan Remington. Please welcome the panelists. Over to you, Mr. Krishnan.

Good morning. How is everyone doing? How is everyone doing? First off, before we get started, I just want to say what a privilege and honor it has been for us to be here the last couple of days. I want to thank all of our hosts. I want to thank the Honorable Prime Minister Narendra Modi. I want to thank the huge team which has made this possible. It has been an amazing privilege. And especially today, when I was roaming the halls and I was here, I was just struck by the honor and the privilege of being here. And I want to thank the optimism of so many of the delegates and attendees here. in particular I was struck by the optimism of so many young people so I’m curious how many of you here are students okay can all of you who are students just please stand up okay can everyone else give them a round of applause because I was just so blown away by the enthusiasm they have for AI and you know and you know the hope and the potential and you know thank you for coming here and I think you need to get back to studying after this but thank you for coming here it really blew me away and so I wanted to say that just because I think that hope and optimism is what we in the Trump administration have really embraced when it comes to AI and I think that’s going to be a core part of when we talk about AI exports so first off I want to kind of introduce my distinguished fellow panelists we have Under Secretary William Kimmett from Department of Commerce we have Deputy Under Secretary Remington Well, before we get into the serious stuff, you’ve been all over India for the last couple of days.

No pressure, but what has been your favorite part? Everyone here is judging you.

My favorite part, I think, it’s been fabulous. We actually did a stop in Bangalore before we came to Delhi, which was really fabulous and really just amazing. I want to echo what Sri Rama said about the excitement and the dynamism we’re seeing in the ecosystem here, and it’s just really remarkable, and particularly the young, talented students here in India. It’s just really been remarkable to see. And I’d say riding in the streets of Bangalore, that was an experience, and seeing the traffic there. But what I noticed while we were driving throughout all the traffic around us was how, well, digitalized the country is. And, you know, I see people on motorcycles, and they’re on the back with their phones, and everybody’s on their phone, and just how digital the country is, and it’s really remarkable.

So I’d say experiencing the streets of Bangalore on the riding side, but also seeing how integrated tech is in everybody’s everyday life here has been really remarkable to see.

Amazing. Anybody from Bangalore or Karnataka here? Okay, a couple of folks. Okay, you need to help show them around next time he’s there. There you go. And Deputy Undersecretary, what about you?

I’d say the energy and the pace. I mean, it’s just unreal. I’ll stick with the driving theme. I think you can see it. It’s both precise and it’s decisive. It doesn’t wait for you. It’s representative of a lot of things, and Indians keep pace. I love the energy.

That’s true. I think the energy has been amazing. And so we’re going to talk about exports, but all of this comes from what President Trump set into motion in his very first week in office, where he did two things. First, he rescinded the Biden diffusion rule, which, as Dr. Kratzio said, made it difficult. It made it near impossible for countries like India to access advanced semiconductor chips. So I think that’s a big thing. I think that’s a big thing. I think that’s a big thing. I think that’s a big thing. I think that’s a big thing. I think that’s a big thing. I think that’s a big thing. I think that’s a big thing. Second, he tasked all of us with coming up with an action plan to deliver on what the country’s, America’s priorities should be when it comes to AI.

And we did that in July, and we have come up with three priorities. First is to build infrastructure. AI needs energy. AI needs data centers. And we’ve been focused on building those in a way that works for America and works for our citizens. Second, we’re focusing on innovation. How do we make sure that we have our entrepreneurs and we have our companies building the technologies that are necessary? But third, I think, is a spirit of partnership. How do we share these technologies that are built in Silicon Valley, in America, with our allies and with the rest of the world? And that’s what we’ve been really focused on. And on that end, and Will, I’d love to start with you.

Could you talk a little bit about the AI? The AI export program that Dr. Kratz has talked about, what it

Absolutely. So certainly, President Trump has made AI a national priority. And so what does that mean? And when you think of the United States and our great tech companies, obviously, we’re doing what we can to support them. And of course, we’re doing that for our national security, our economic security and the success of our great companies. But how do we use that to share that with the rest of the world? And so specifically on this AI exports program, the president issued an executive order last July that tasked the Department of Commerce with standing up the AI exports program. And what that is, is it’s going to call for industry led proposals of consortia that will offer full stack offerings to the world and how we can promote the exports of those full stack consortia.

So it’s sort of a question of what does that mean? What does full stack mean? And so we wanted to make sure we were as thoughtful as possible in this process. us. And so we issued a request for information, asking companies to give us information, tell us what might be helpful, tell us maybe what wouldn’t be helpful. And we got a tremendous, tremendous response from the industry. We got hundreds of submissions, and we have spent the last several weeks digesting those and understanding the dynamics that maybe we weren’t aware of and things we should think about as we craft this program. And we are putting the finishing touches on it. And the next step is going to be a public call for proposals from the industry to submit these consortia and how we’re going to shape that program to do full -stack offerings and maybe other offerings as well.

That’s awesome. And Deputy Undersecretary, if I may come to you, maybe if you can just get into the details. We have guests from multiple countries over here. We have companies from all over the world here. Could you maybe break down a little bit about the next level of granularity? How do these consortia work if I’m a country attending this event or if I’m a company? what should I be doing?

Sure. I’ll start by saying you’ll hear more on how it actually works, but I’ll describe what we’ve heard so far and what people have asked of us. We’ve heard really two motions. One is how can we go outbound to the world? How do we offer, how do we help companies find buyers? And then on the other side for foreign buyers, how do we make it easier for you? And so as we’ve looked at that, we’ve decided, and as we’ve approached it, we’ve looked at a couple of different kinds of consortia. On the one hand, you would think, and what we’ve heard is make it easy, make it simple, like t -shirt sizes, small, medium, large.

I don’t need 100 permutations. I just need to know what’s available. But there are others who do want that special, very, very unique niche kind of thing and to accommodate both of those. And we’ll say in each of these, we’re looking for simplicity. We’re looking for elegant solutions. Our goal here is to make this easy for both sides. for both buyers, whether they are governments, whether they are state -owned enterprises or any sort, and then also for the real companies that we talk to, both the large ones but also the small startups who are thinking, what should I do next? I’m in my Series A, I’m in my Series B. Should I sell abroad? Is this possible to make that feasible for them?

And so if I’m a founder, should I come find you?

Yes.

Oh, there we go. Wow, I like putting him on the spot over there. So find him.

Through the website, not me personally.

He’s the man. I think for the last couple of days, one of the remarkable announcements was the launch of Sarvam’s new model, which I was really blown away by. And if you folks haven’t checked it out, you should check out some of the technical details. It is really, really impressive. And I think that is a good segue to the theme of sovereign AI. We have countries all over the world who want to have a sovereign AI kit. capability. What does it mean when working with some of the programs that we are talking about today with if you’re a national champion or if you’re a country which wants to have sovereign capabilities?

Sure. So I think the program is going to, of course, be built on the American AI tech stack. But then, like I said, what does that mean exactly? And so what it really means is we want to set the foundation for possibilities as we’re exporting to other countries. And so in the context of a national champion, you know, if there’s a great company that wants to use American tech, we provide that foundation and then allow that national champion to build on that foundation of American tech. And so it’s really providing a level of the tech stack to countries so that they can build on that with their great local domestic champions.

I totally agree. I think one thing that, you know, when it comes to the stack, is there are multiple parts of it. There are the chips, the GPUs, the TPUs, whether using NVIDIA or AMD or Google. For example, you know, Servum has done great work working with NVIDIA on training their model. Then there is the model layer. There are agents or applications on top. So I think when we talk about the program and the stack, it is really you can pick as a company or as a country what part of the stack you want to build on. And there’s a whole range of possibilities.

If I could add one thing, we’re trying to facilitate choice. We hear about AI sovereignty a lot. And there are many different versions of this, right? We hear about does every village need their own data center, right? Or does everyone need an LLM for, like, their specific context? Some of them just say I want control over my data. I want to know where it goes. I want transparency. Because there are so many permutations, we want to offer these many choices and allow each context. And we’re trying to do that. And we’re trying to do that. And we’re trying to do that. and each buyer to make those choices.

And that is true. And I think I want to go back to what Dr. Katcha said, and I said about the first week of President Trump being in office, he wanted to make it easy for other countries to get access to our technology, and that set this in motion last January. Next up, I want to move to use cases. A lot of countries all over the world that Dr. Katcha is talking about and who are trying to figure out how to adopt AI, how to provide their citizens a better quality of life, better services. What are use cases that are interesting to you that you think, you know, we are going to see a lot of great progress and work on in the next year or two?

Yeah, so I think the ones that are interesting to me certainly are in emerging markets are both in the health space and the education space and what we can do to bring AI solutions in those crucial sectors in various countries. And so. working with like the Ministry of Health in an emerging market and coming up with a solution that would revolutionize their health industry to the benefit of their citizens, that’s the part of the program that really excites me.

Ben?

Yeah, there’s so many. I mean, it’s so sweeping, but others we’ve also heard have been agriculture, manufacturing, I mean, maritime, you name it. There are a lot of verticals that have so many new use cases and so many new applications coming out all the time. I think back to the simplicity point, organizing around verticals, a one -stop shop, if you come here, this is where you can find offerings, has been something we’ve heard would be very useful.

I think so. For me, there’s obviously many, but I think education is something which has just blown me away. Even this morning, talking to a student, I met somebody from my alma mater and from second year of undergrad who’s just doing amazing things with AI at an age when I was not doing anything at all. And I think that’s something that’s really important. I think that’s something that’s really important. And, you know, that just fills me with hope and inspiration. Imagine every student, whether you could be five years old or maybe you’re 50 years old, and having access to a teacher, a lecturer, a professor who never gets tired, who knows how to speak to you in a local language, can answer any single question.

I think that is going to change so many people’s lives. Okay, one last note. We’re all working on AI. Just on a broad theme, what is something about AI, whether it’s in the U .S. government, whether it is how you’re approaching your work that fills you with optimism?

I’d say for me, speaking, you know, working for the government, we’re talking about helping export USAI tech stack to the world. We actually, in the U .S. government, need to do a good job also bringing it into government in a lot of the work we do. I run the International Trade Administration. As part of that, we do a lot of analysis of supply chains and looking at things, and there are certainly better ways we can. So that’s one area where I think as we’re bringing tech. to the world, we also need to do a good job of bringing it into the U .S. government and helping us become more efficient as well.

I love that. I have to know that the U .S. government, I mean, we’ve done a lot of work. If you look at the action plan, a lot of work on making things more efficient. And you?

I’d say two things. The first, it’s so sweeping. There are very few technologies that change like your personal life and your work life. And they’re both going very quickly. The second is the hunger for this is so high. It’s not hard. We don’t have to sell AI in the sense of, do you want this? People want this. It’s really, how should we best provide it to them? How do we help both sides of this? How do we help the companies and how do we help the buyers? And being in the middle of that and enabling that is very exciting.

I agree. I think it’s a great note to end on. And I think I just want to close out by reemphasizing something that the Ambassador Gore spoke about earlier, which is, you know, these are two great nations. the world’s oldest democracy and the world’s largest democracy. Both countries, I obviously have very deep ties to. And a lot of this has been made possible by the special relationship between President Trump and Prime Minister Modi. And I think today, what you saw with the Pax Silica signing with Undersecretary Helberg and Dr. Kratios, what you saw with Dr. Kratios’ announcement is such a remarkable moment. But for me, it is just the beginning of what is going to be an amazing, enduring technology partnership.

But thank you so much. And thank you for being an amazing audience. And thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you.

Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Hello everyone, welcome back once again. I’m sure you’re all refreshed after this break. And now we’re going to start with the next session and have some wonderful keynote speakers once again with us today. And a great lineup, as I said in the morning as well. So now I’m going to invite our keynote speaker. He is Mr. Jeetu Patel, President and Chief Product Officer, Cisco. Well, Mr. Patel sits at the intersection of AI and enterprise infrastructure. It’s kind of the plumbing that makes it work.

At Cisco, he’s leading the company’s transformation into an AI -native networking and security powerhouse. In a world obsessed with models and algorithms, his reminder that none of it works without resilient, secure infrastructure is both timely and essential. Ladies and gentlemen, please welcome Mr. G.

Thank you. very much in line with the overall theme of the summit. We are looking at the overall aspect of governance of AI, but not as something that will be set aside and looked at through a different lens altogether, but something that can be looked in as an embedded layer of governance that we already govern technologies with. In the interest of time that we have with us, I will request the panelists to be seated on the dais, and I will request AK Chaudhary sir to please begin his keynote.

Good afternoon to everyone. Distinguished policy makers, regulators, industry leaders, members of the FinTech community, and esteemed guests. I will just very closely following last four days how and what are things happening and it was amazing the type of enthusiasm type of excitement and type of budge around AI and this summit and I believe and that whatever is there actually is a real thing which is happening possibly multiple small applications are going to come in coming days which will solve multiple issues and problems in coming days and we’ll have the real leading role actually to play as a country that is the way we look at it we also will have a great role to play on the data side particularly when we are going to train the models for that obviously when we are going to scale up entire thing then possibly there might be some run -throughs some risk also and those risks something is known, something is unknown and for unknown much cannot be done except we need to do take care of the embedding the governance part.

That is the theme of today’s talk, how we need to embed the governance actually the entire life cycle of the AI, the design of the AI. That is the way we have to look at. Yesterday I was again listening our Honorable Prime Minister and the beautiful way that he summarized the entire theme in one word that is called mano, that is called humanity. So possibly in future I am going to use that instead of responsible AI, that is possibly we can talk about human AI because it is going to touch upon moral and ethical systems, accountable governance to sovereign, national sovereignty, accessible and inclusive and valid. All the aspects what we are going to touch upon, everything is covered in this one word that is called Mano.

Now coming back to my address, proposed address, I’m coming back to this now. It’s indeed a privilege to participate in this dialogue at a defining moment in India’s digital evolution. Over the past decade, India has demonstrated how population -scale digital public infrastructure can drive inclusion, efficiency and trust. Systems built with interoperability, transparency and scale at their core have reshaped financial participation by millions. Today we stand at the next inflection point in that journey. A new tech layer is being superimposed upon this digital foundation. AI, artificial intelligence, what we know it, is not arriving in isolation. It is integrating with payment systems, credit and risk management platforms, supervisory frameworks. and cybersecurity architecture that already operate at national scale.

This convergence of scale and intelligence marks a structural shift. Unlike earlier waves of digitalization that automated existing processes, AI introduced adaptive systems, systems that learn, recalibrate, and influence outcome dynamically. In a country as large and diverse as India, such systems do not merely improve efficiency, that see access, opportunity, and systemic resilience. The question before us is not whether AI will transform finance. It already is. The more fundamental question is whether governance will evolve at the same pace as innovation and whether it will be designed into a system from inception rather than appended later as a compliance of the thought. In financial services, trust is foundational. AI system cannot function as opaque black boxes, especially when they influence access to credit or flag financial behavior.

Governance cannot be an overlay applied after innovation has already been scaled. It must be embedded by design. As Peter Drucker observed, quote, management is doing things right, leadership is doing right things, unquote. In the context of AI in finance, governance is not merely about tech correctness. It is about doing the right things at the right time in ways that preserve trust, resilience, and inclusion. Now, looking at AI as infrastructure tool, it has evolved from analytical assistance to shaping financial outcomes. In credit market, machine learning model analyze transaction histories, behavioral signals, and dynamic cash flows to generate granular borrower assessments. In fraud prevention, AI detects anomalous activities within milliseconds, processing volume beyond earlier systems. AI -enabled detection can reduce certain categories of fraud losses by up to 25 to 30 percent at this point of time in high -value payment environment, what we are witnessing in NPCI.

Compliance functions increasingly rely on automated pattern recognition, while adaptive cybersecurity models respond to emerging threats in real time. The diffusion of AI across the financial value chain enhances efficiency and precision. Yet, when models operate on a systemic scale, even marginal inaccuracy can produce material consequences. In finance, where stability and trust are public goods, the tolerance for systemic error is limited. India’s financial system adds its own complexities. Its scale of digital participation, linguistic diversity, demographic heterogeneity, and income variability are also important. heightened model risk. Although trained on narrow urban centric or historically squid data sets may inadvertently misclassify, misprice or exclude segments that digital finance is intended to integrate. It is therefore imperative that we do not view AI as a peripheral tech enhancement.

It must instead be understood as a component of financial infrastructure which is systemically relevant and should be subject to the same standard of resilience, governance and accountability what we expect of any critical financial utility. When we talk about embedded governance in AI, historically regulation in financial services have often responded to innovation after risk gets materialized. Governance in the AI era must however be embedded into systems design. Embedded governance means integrating accountability, transparency, and risk management into every stage of the AI life cycle. from conceptualization and data acquisition to model development, deployment and ongoing monitoring. It rests on several foundational pillars. I will mention four. One is proportionality, that is the governance intensity should be risk -based.

It should be risk -based intensity. Fairness and non -discrimination. Third is explainability and transparency. And fourth is accountability, which must be clearly defined. While institutions may collaborate with tech providers or leverage shared infrastructure, responsibility for outcomes cannot be outsourced. Potential vulnerability of AI systems that save their operations, board and senior management must understand that logic, limitations, et cetera. Further, and more importantly, in financial AI, algo efficiency should not compromise equitable opportunity. Now, specifically coming to the financial infrastructure, risk -based approach to AI governance, just I’ll touch upon this. A risk -based approach to AI governance acknowledges that innovation and prudence are not opposing forces. They are complementary. Financial authorities globally are converging on principles that emphasize robustness, resilience, transparency, and human oversight.

India’s regulatory thinking reflects this balance, encouraging experimentation while reinforcing institutional responsibility. The objective is not to slow innovation, but to ensure that systemic risk does not accumulate invisibly. Several risk dimensions deserve particular attention as AI becomes integral to financial systems. It may include multiple issues. I will touch upon only four. One is the model integrity. For instance, it can no longer be viewed as a one -time validation exercise. Intelligent systems must be evaluated across economic cycles. And stress against extreme but plausible scenarios. As data patterns evolve and models recalibrate, continuous oversight becomes inevitable to guard against drift, unintended bias, or reinforcing feedback loops. Second is operational concentration risk. I will detail subsequently also. It is an emerging systemic concern.

Diversification and resilience planning are essential to safeguard continuity. Data governance through data integrity, consent management, purpose limitation, and minimization principle is foundational. Financial data is not merely transactional. It reflects livelihood, behavioral choices, and economic participation. And the fourth item is cybersecurity risks that are amplified in the AI environment. As AI strengthens defense mechanisms, it can also be leveraged by adversaries. Institutions must anticipate adversarial AI and strengthen defensiveness. Detection capability accordingly. A risk -based… framework recognizes that governance cannot be static system that learn and evolve demand demand oversight that is equally dynamic as also measured proportionate and forward looking now just touching upon supervisory intelligence as ai permeates financial institution supervisory framework are also evolving supervisors increasingly leverage advanced analytics to monitor systemic pattern identify anomalies and strengthen early warning mechanism this creates a reciprocal dynamic institution embed ai in operation while oversight bodies integrate intelligence into supervision however governance cannot be regulated driven alone institution capability is critical ai literacy at the board and senior management level is no longer optional leaders must understand model architecture validation methodology vendor dependency and ethical limit implications Effective governance requires interdisciplinary capability bringing together tech, risk, compliance and legal experts as well as business leaders together Institutions that integrate AI governance into their ERM framework strengthen resilience Christian Lagarde has noted, innovation and regulations are not adversity, they are partners in progress That partnership must guide the embedding of AI within finance Coming to the inclusion part, what our Honorable Prime Minister has mentioned about the last A in MANO, that is access and inclusion India’s financial transformation has been anchored in inclusion Over the past decades, tech has lowered barriers, reduced transaction costs and brought millions into the formal financial ecosystem AI now offers an opportunity to deepen that trajectory Through granular dynamic risk assessment Thank you It can reduce reliance on collateral heavy models and static credit history.

Transition level data, cash flow analytics and behaviour indicators can provide more nuanced insight into the repayment capacity, particularly for MSME who are presently outside the traditional credit framework. India is expected to account for a significant share of global digital transition growth this decade. If harnessed responsibly, AI can convert this expanding digital footprint into broader formal access to fair financial services and adoption at scale. Yet, inclusion cannot be assumed. It must be intentionally designed. Algo, trained on historically squid dataset, risks perpetuating structural inequalities. In formal sector, income volatility. In terms of the future, of the Gender -based data gas may distort credit outcomes. Without corrective safeguards, technology may reinforce rather than reduce disparities. Inclusive AI thus requires representativeness in training datasets, periodic impact audits, and community -level feedback mechanism.

It calls for institutional mechanisms that allow individuals to seek clarification and redress where automated decisions affect their financial standing. Now coming to the sovereign and resilient AI foundation. AI governance intersects not only with the institutional risk, but with strategic resilience. Concentration in advanced chips and foundational AI models raise critical consideration for economic sovereignty, financial stability, and I can further add, the national security. Dependency on limited supply chains can create systemic vulnerability. If we may look at AI stability. I’m going to go ahead and start with the AI. more granularly. It rests on five interdependent layers. At the base are specialized semiconductor chips we all know. Above this sits the cloud and data -centric infrastructure that provides scalable processing capacity.

And these systems are fueled by vast data sets drawn from public and proprietary sources. On this foundation operate large foundation models adaptable across domain and finally at the top are application and that embed AI into financial services and everyday economic life. In this context we should be conscious of the fact that one firm controls more than 90 % of advanced chips. Three dominate cloud capacity and a handful command foundation models threatening financial stability and economic sovereignty. We must therefore diversify supply chains to the extent possible through domestic innovation and international collaboration to secure resilient AI foundations. Further, if you look at what is the pathway for ecosystem scaling possibly we have to look at the consent based data sharing, shared AI and risk infrastructure investment in AI literacy and governance at all levels including board and senior management and most importantly encouraging home grown tech and AI capable entities.

It may be appreciated that an India first approach is not inward looking. It is context aware. It ensures that governance reflects local realities while remaining global coherent. Now coming to the operationalization of embedded governance, it may involve multiple issues but I am touching upon 5 to 6 one. The life cycle based model governance institutions should embed governance checkpoints from data acquisition to deployment and post deployment monitoring. obviously clear risk classification framework based on the systemic impact that we should have to have independent review and oversight, enhanced oversight on that. It should be auditable and documentation should be there cross functional governance committee will be helpful no doubt on that and continuous monitoring and feedback loop that basically helps in periodic recalibration by way of external audit.

Consumer centric safeguards obviously by way of transparent disclosure clear appeal processes and human intervention mechanism are critical to maintain public trust. These pathway ensure that governance is not episodic but embedded women into operations DNA. Now I will just before concluding I will touch upon the role of India in AI and trust as a corner store of financial AI. Finance rest on confidence that systems are fair, stable and accountable. Deposit trust institution to safeguard asset borrowers’ trust systems to assess risk fairly, and market trust, transparency, and stability. EI has the potential to enhance this trust by improving fraud detection, accelerating compliance and broadening access and inclusion. But if governance is ineducated, EI can erode confidence rapidly.

Trust is built when systems are predictable, explainable, and accountable. Trust deepens when innovation aligns with public interest. And trust endures when leadership anticipates risk rather than reacts to failure. India stands at a pivotal moment, working across all five layers of the EI stack, and demonstrating the ability to deploy application at population scale. It is shaping a global agenda for inclusive EI. The convergence of digital infra, regulatory foresight, and entrepreneurial innovation offers a chance to show that scale and safety can coexist and governace can catalyze inovation.Coming to conclusion artificial intelligance wiil sace the next chapter of financial services. But tech alone does not determine outcomes. Institutional design does. Design choicesmgovernance framework and institutional culture will determine whether AI strenghten finance finacial resilience and inclusion or not.

Embedded governance is not regulatory burden.It is strategic imperative.It ensures that innovation is sustainable, trust is preserved and the system stabillity is protected. If we embed fairness,transparency,anccuntability and proportional oversight into the architecture of financial AI form iception, India can chart distinctive path,one that alligns tech ambition with ethical responsibility. Let as approach rhos moment not with hestitation but with disciplined forseght .Let us ensure that as our financial systems become more intelligent,our governance become more robust, our oversight becomes more anticipatory and our commitment to inclusion more resolute. In doing so, we will not only harness the power of AI ,but we also shape it to serve the broader goals of stability, oppertunity and share prospectively.Thank you.

Thank you, sir. That was very insightful and sets the context for the panel discussion to follow. We could also request you, if you would want, you could join us in the audience. That would be great. Over to you, Priyanka, for introduction to the panelists and then taking this discussion forward.

Thank you so much. Thank you. Our panelists need no introduction. I’m going to keep it very fast so that we can make the most of, you know, capturing their thoughts. First, I have with me Mr. Sanjeev Sanyal. Sir is the economic advisor to the Prime Minister. He’s in the Prime Minister’s office and he needs no introduction. If I actually go by what AI has given me as his persona, AI summarized it as a macro thinker, a historian, a historian of structural cycles and a strategic geopolitical lens. Fortunately, today we have the OG himself in the room. And without any further ado, I want to ask him my first question. So historically, countries that have mastered general purpose technologies, right from the steam engine, early electricity, Internet, they’ve gained outsized economic advantage.

Is AI that inflection point for India? And if so, does early well -designed self -governance accelerate trust or does it deny us of any competitive momentum?

Yes, it is important that you are engaging in it, but let me point out that it’s not always the first movers who benefit from it and it’s not the case that even those who invent these technologies know where they’re headed. I mean, just to give you an example, the European Renaissance, which led ultimately to the Western domination of the world for half a millennium, was based on three technologies. One was the printing press, the other was gunpowder, and the third was mathematics. The first two were invented by the Chinese and the third was invented by the Indians, but it is the Europeans that took it, owned it and dominated the world. So, one important thing to recognize in all of this is that do not try and necessarily guess where this is headed.

But of course, we need to engage in it. We need to engage in these technologies and build on them. Otherwise, you know, somebody will take your technology and dominate you. So it is very, very important that India does participate in this AI revolution. But again, in this context, let me say, that does not mean that we should spend time trying to work out exactly where this is headed. For example, when the social media revolution was happening 20 years ago, when Facebook and all these things came about, the marketing tool of the people at that time was, see, now everybody can talk to everybody, we will all move to the golden mean, because we will all have similar views, because we can all talk to each other, and so on.

But in fact, the algorithms went out of their way to put us in buckets and echo chambers. So in fact, we ended up, social media ended up doing exactly the opposite of what the, you know, the technology experts were telling us social media would do. now why does this apply to AI as well and here I am going to talk about this risk based thing that everybody is talking about let me tell you that you cannot actually put AI or any types of AI into any real risk bucket because this is an emergent evolving thing even more so than social media so consequently if you are saying I am going to do risk based it means that you have some assessment of where that thing will go and I am telling you that it is almost impossible to do this so for example in my view the European way in which they are going about and having you know risk they are the pioneers of risk based systems I understand it is pretty obvious that you don’t want AI to take over our nuclear buttons but other than that the risk levels of most of the other things is utterly unknown this is a bad thing because I am not saying that because I am not saying that because I am not saying that something totally innocuous might go and blow up the whole system because these things are emerging they are evolving, they are interconnecting therefore I actually do not think the risk a system that is largely based on perceptions of risk will work because it is not possible ex -ante to work out what is dangerous or for that matter what is beneficial now what should you do if you can’t tell what is going to happen I am telling you the European system is either going to be strangulate the system by being too stringent or it will open things up because it wants progress but will ultimately the risk based system will not be able to take control of it so the other model that is there is of China which is the state knows best but we know from the experience we had with the Wuhan virus that the state can very often lose control of things that are happening and it can spiral out.

The third model that is mostly the American model is to have a laissez -faire and let anybody do whatever they want. Now the dangers of that are obvious. In my view, the way they control it is through tort laws, i .e. if something goes badly wrong, you will then end up with a billion dollar fine or something like that. So in some ways it works better because it’s ex post rather than ex ante system. It depends on those who are running the system having skin in the game, i .e. your company will go down and you will be jailed and you will have a billion dollar fine on it. If things go wrong, that is how they are doing it.

It’s an ex post punishment. But as you can tell, that is some ways, is an ex post system and if something really bad goes wrong, you know, it will you’ll only find, you know you can punish the person after the horse has already bolted you are going to lock it. So all these systems have their downsides but I’m just telling you that whatever system we design in order to control this has got to be based on being agnostic to how this whole thing works going forward. Now, I know I’m taking up their time but give me a minute. There are other systems that we manage where we have no idea where they are going. Take for example the stock market.

You and I don’t know where the stock market will be in a decade’s time. It’s a complex system just like artificial intelligence but we manage it. How do we do it? Well, we do it by creating a framework which does the following thing. It first of all has institutes audits. And enforces transparency and explainability. if you can’t explain your accounts you can’t be in the stock market two it has systems of shutting things down when things go wrong so there are every stock market will have when things spiral out it shuts down three it deliberately creates systems of separation for example this you know there are the same company cannot you know be a bank as well as being a company that so there are conflict of interest so in the same way AI will need to create compartments I am personally very suspicious of any idea of the internet of everything and the AI of everything that would be a disaster I think we need to be willing to allow compartmentalized AI I think it will be more efficient anyway from an energy perspective but I think it’s also safer and most importantly you need to create skin in the game, i .e.

ex ante tell people who will be held responsible when things go wrong. So, in the case of financial markets, the directors of the company are the ones hauled up when things go wrong, or the CEO. In the case of AI, we will have situations where when things go wrong, the person who made the algorithm will blame the data, the data guy will blame the company, the guy who is the user, all kinds of things will happen. We need to ex ante decide who in the system will be hauled up when things go wrong. That will create skin in the game. But we cannot wait for something to go wrong and then this happens, we need to decide this ex ante.

So, all of these things exist in the case of financial regulation. I personally think a similar system.

Rightly put technology moves fast but trust takes time to build and compartmentalization is a great way to de -risk in some form and also look at it with a focused agenda and attention. With that we can actually bring in Mr. Kamath. Mr. Kamath is from the GIF City IFSC, a compartmentalized global financial hub in a way that India has created and we are very fortunate to have you sir here GIF City actually operates at a unique intersection of innovation and global credibility. It competes with the likes of Singapore, Dubai, London. Can GIF City become a lab for AI governance and we wanted to know your view sir and especially a great segue from Sanjeev sir on how we can look at it differently in a compartmentalized manner.

See if you see a Gift IFSC as a jurisdiction, it is just, it was set up in 2015, so it’s just 11 years old. We are building it up from scratch. Now, when you build something from scratch and when you have a brand new regulator, like IFSC which was created in 2020, you start with a clean slate. So that means you have more leg room and you have more space to experiment. So we don’t have baggage of the legacy systems. So if you see the way we have evolved over the last six years, IFSC, the way regulations have evolved, we have all the verticals across finance, capital markets, banking, insurance, pensions. And we have introduced new verticals, ship build, ship leasing, aircraft leasing, ancillary services and so on.

You know, in line with all of the global financial centers. So with respect to experimentation, when you use the word lab, you imply experimentation. So the appetite for experimentation and the appetite for taking risks, is much higher than other, say, domestic regulators or regulators overseas because of the absence of retail investors. so yes gift city has an immense ability to to come across as a lab uh for ai governance however building a financial center is a is is like a 45 kilometer marathon you know it’s not a 8 kilometer dream run so it will take its time uh we are on the growth trajectory on the upward trajectory and there is a certain gestation period for every financial center that that period gestation period cannot be skipped we are in that gestation period so once we reach critical mass we will we’re going to see a lot of things happening and coming out of gift ifsc.

Thank you actually i will go murli sir and the rbi free ai report or the framework on uh you know any enablement of ethical ai i think it’s very forward looking it is actually building on existing regulatory controls and architecture to bring in you know the principal base ai ecosystem so my question to you is If a company has embedded robust controls, model inventories, bias testing, continuous monitoring, should regulators reward and discipline such companies with calibrated supervisory relief? And in other words, is there a safe harbor for somebody who’s, you know, who’s put in risk -based controls but, you know, has been a first -time defaulter?

Yeah. In fact, in the same report, it was suggested that the entities which put in place all the guardrails and then in case of any labs, if they are doing the root cause analysis, trying to address the problem, they should have a, the regulator should have a lenient supervisory approach. And it should be seen as a, it should be seen as an instrument. It should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a, it should be seen as a over acting risk area so that is something which we recognize so on both friends one is we understand the technology is probabilistic and then it can have lapses but once in terms of governance if you if you put in the guardrails if you put in the processes if you put in the mechanisms across the lifecycle to see that this the the customer doesn’t face the risk so that is the main focus the customer it should be transparent to the customer it should not be a black black box rather than it can be a glass box so so and and it should be understandable to the customers so once all the measures are taken take are taken into consideration by the by the entity in terms of governance as well as the processes you can see that the customer does not face the risk so that is the main focus the customer it should be transparent to the customer it should not be a black black box rather than it can be a glass box so and it should be understandable to the customers so once all the measures are taken take are taken into consideration by the by the entity in terms of governance as well as the processes because of the nature of the technology presently we understand it can lead to some to some aberrations but then as long as it is it is taken in a in a right process you have these incident reporting mechanisms you have the you will have the manual or right so the once you have these controls and the and the right approach the supervision will not should not be used as a as a systemic or or a greater risk you should rather you should allow first time lapse and then in terms of say rewarding it we also suggested that there would be an award for a in finance particularly there are specific works done in in terms

Thank you. I think Vikram your advantage point here because you are a global infrastructure player. You are seeing regulatory trends across the US, UK, Singapore and many other markets. You heard about how the panel has been shaping right from the policy makers to international financial center and also RBI. Want to know as an infrastructure provider how are you looking at cyber security and its evolution in the age of generative AI?

Thanks so much Priyanka. I would just make one correction as a cloud scientist. I am a cloud scientist and I am a cloud scientist. I am a cloud service provider and not merely an infrastructure provider. I think one of the things is, for good or for worse, we’ve seen the benefits of generative AI, but we’re also seeing bad actors use generative AI for phishing attacks, for credential attacks, for malicious code. So, you know, with the good comes the challenges. But one of the more important elements is that while it’s serving as an accelerant to existing methods, I don’t think it’s foundationally changing the nature of the attacks. And, in fact, there was a report that came out in 2025.

It talks about how generative AI has lowered the barriers for a lot of these threat actors. But I go back to what I said. It’s because it’s not foundationally changed. The same principles and the same foundations of cybersecurity that held true before gen AI still hold true. So, you know, multi -factor authentication, strong passwords, regular updates, scanning your systems. And I think it is imperative for organizations. To fundamentally, especially in the financial services, who are always. being attacked and India is a country where not only the banks but we have a huge citizenry with different levels of financial literacy so therefore how do you use these tools to actually safeguard the financial system so I think that in that respect you know a lot of sort of kudos to the RBI for also thinking about it on you know these principal lines but also the banks for actually leveraging these technologies and I think that one of the elements that you need to always do is you know trust service providers like us but also banks should verify and that is done through standards like ISO or the NIST and you know independent third party reports validate the various controls that are there and I think that now and it’s a point that I was making a little earlier you have to become an active participant in cyber security no longer can you be a passive passenger in it because the landscape is changing and as more and more people are digitizing so are the people who are willing to and are looking to attack any vulnerability.

So GenAI does provide you with the tools, because, again, I’m also a believer in not, you know, human in the loop, but having AI in the loop. So how do you use these technologies to have faster responses? How do you automate scanning? How do you automate getting reports? To be able to make those value judgments at the right time. So that requires skilling. Again, that requires awareness, not just about something like an AWS or the cloud, but also banks and also, you know, the work that, again, regulators as well as cloud service providers are doing is having these awareness programs to make sure that the more people understand the technology, the better the framework and the groundwork will be for them to adopt.

Thank you.

I think I also referred to our earlier discussion today afternoon, wherein rather than AI thinking, about a human in the loop, humans think AI as a loop to move forward and I think that was a great paradigm shift that we can look at. Sanjeev sir I am going to come back to you but I also want to give a backdrop to this question India has never simply adopted technology we have created it, we have adapted it, we have scaled it and we have governed it in our own way. We did it with identity, we did it with payments and we did it with digital public infrastructure If the governance frameworks around AI are beginning to emerge and they are also being divergent globally like US being innovation led, EU being compliance led, China being state led, where is the access that India is going to strategically position itself and how are you looking at it from your lens?

So I

think I will continue from what I was saying earlier Now, we need to be very, very careful that we don’t end up with a bureaucratic risk -based system. This is an emergent technology. It will evolve in all different ways, and we’ll have to be very, very creative about this. Now, there is a difference between, say, the systems as an architecture. AI is an emerging thing. It’s not just infrastructure in the sense that, say, you can think of UPI as infrastructure, for example, digital identity as infrastructure. It doesn’t in itself have emergent behaviors. AI has emergent behaviors, i .e., it evolves and interacts with other forms of AI, and which is why I said you need to be fundamentally suspicious of anybody who says that they have a very clear idea where this whole thing is going.

We don’t at all have a clear idea. Nobody on the planet has a clear idea where it’s going. So we do need some regulation. We need to be very, very careful about having humans in the loop. as I said right in the beginning you need to have systems switch off buttons you need to create what are called in finance Chinese walls which separate different tracks as I said earlier I am not a huge fan of the AI of everything I think that’s dangerous and will lead to bad outcomes however AI can be run in compartments rather well and why don’t we use that because in any case that’s less energy using in any case it is better at solving bounded problems when you give AI an unbounded problem it tends to hallucinate because unfortunately it has learnt another human trait that it doesn’t like to tell you that I don’t know it rather make up stuff so consequently I think it is better that we deal we give it bounded problems let it solve those bounded problems and get back to us going for this AI or internet of everything which everything is interconnected sounds very good but just it was last July or July before that we saw when one very small code of a Microsoft program which was by the way static it wasn’t even a fluid one it went wrong and you ended up with causing havoc in airports ATMs all kinds of things around the world now imagine the same thing happening in a system where it has emergent characteristics by the time you fix one bit of it it has flowed into some other part of the system so I personally think we need to create firewalls you know forest fire is also an emergent thing and the way we control it is not by predicting where the fire is coming from and where it will go we just have these firewalls from time to time we do that in finance all the time we don’t try to work out what the conflict of interest is, we simply ban situations where conflict of interest will emerge and the same thing is true of skin in the game I think we need to ex -ante work out where in the chain is the responsibility I personally think that it should be done at the level of where the algorithm is made public to use whoever is making it even if their data is wrong you cannot blame the data you are responsible so somebody else may disagree, whatever point of the matter is we need to have very clear points of punishment when things go wrong we need to have audit systems for explainability there is nothing very deep about this after all every company listed in the stock market has got it itself several times a year why can’t we ask major AI companies to be audited?

If you cannot explain why your results are turning up too bad, you shut it down. We do that even with relatively small companies have to go to a chartered accountant several times and chartered accountant has to sign it off. Maybe we have a chartered AI audit for anything that goes beyond some threshold. And I think given how potentially dangerous it is and lucrative it is as well, I don’t think we should be thinking about this as a problem. Rather than doing what I think many others say, okay, they understand it’s dangerous, they will say, but why don’t we have risk -based? Now, ex ante, you cannot work it out. All you will do is you will have technologies that are just, you will end up with regulations that will become just too stringent and will kill the sector.

Rather, along the way, you have a system of explainability audits. With that, let me hand

Mr. Kamath, I’m going to come to you. Economists worry about tourists under regulation that creates instability and over -regulation that will kill dynamism. Where do you see gift city? Because, again, it’s at an intersection of local and I want to hear your views on it.

That’s the problem facing all regulators worldwide across financial sector. Over -regulation repels innovation. Under -regulation repels serious long -term capital. So now, where do you draw the balancing equilibrium point? Let me explain it with an example, simple example. I joined SEBI, Securities and Exchange Board of India in 2008. I was posted to the surveillance department. In 2008 itself, the financial crisis was in full flow. So in our surveillance systems, which are very, very powerful systems, we noticed 1 ,000 orders being entered in a span of couple of microseconds. So we were wondering how is this possible, how can a human enter so many orders. Then we came to know algorithmic trading terminals have been deployed by certain entities in the stock market.

When we dug deeper we came to know that initially it was deployed in 2004 by one entity and then slowly slowly it was the volumes were increasing. I mean it didn’t reach a critical point but they were slowly increasing. Now in 2010 the inflection point came when it reached a critical mass. SEBI came up with guidelines to protect safeguard the retail investors and to preserve financial stability. So here is a perfect example where an innovation in the capital market which is algorithmic trading was deployed by entities for a good six years. It was not regulated, it was being used and the regulator didn’t do anything to stop it. But when the regulator issued the guidelines the necessary safeguards were put in place.

However at the same time there were no breaks applied on the rollout of the innovation. So algorithmic trading even after the guidelines grew exponentially in the Indian capital market to where it is today. So in the same manner, we hope to facilitate innovation in gift IFSE. We have sandboxes in place for startups as well as established entities. They can roll out their AI pilots in the sandbox. The goal is to cap the risk. Like sir said, it’s very difficult to identify all the risks. But whatever possible risks can be identified, let’s cap the risk without going into the technical mechanics, you know, the internal mechanics. And then see how it flows out. Based on the data that you receive in the experimentation, accordingly the regulations can be tailored.

Thank you.

I know we are at time, but I’m going to still extend because I have such a prestigious panel by another few minutes. Could you come back to you with a quick rapid fire? If you could tell us one risk that we are underestimating when it comes to AI. No, in

general we would not like to talk about risk. So that is our approach. Our keynote speaker, Ajay Choudhury, was also at the helm and the department was formed. So risk is maybe underestimating the risk. That is what I can say. That can be addressed only through the governance, particularly in the present emergence of technology. Actually, I

like what Sanjeev sir was telling us. It’s never going to be risk -free, but we’ll have to move forward. We’ll have to figure it out and we’ll have to do it in as much as possible compartmentalized manner. So any risk that we are overestimating, anybody from the panel who wants to talk about any risk that we are overestimating. Let’s give Vikram a chance. I

mean, I think the fundamental nature would be there is no zero risk. It’s how do you equip yourself. to handle risks because I think a point that Mr. Chaudhry Mr. Sanyal also made is as a regulator or a regulated environment, how do you create the tools to be nimble to adapt as the technology adapts and I think that that is the important element. Right now the tools are there, there is so much we can do that we’re not, maybe we’re not doing as well, so maybe we can focus very well in the here and the now and equip ourselves to be nimble enough to deal with anything that comes because anybody who’s telling you what’s coming with a certain amount of certainty, I take that with a pinch of salt.

I think that the future is a little unknowable at this point of time but there are so much that is known and we should be able to tackle that right now. I

think that’s great. Sanyal sir I’m going to again come to you. One reform that India must prioritize, what is your view on it? That’s

Copyright law. Who is the owner of a particular innovation? At which point do you call it an innovation? And is that innovation owned by the person who put the prompt in? Is it owned by the person on whose data it got trained? Or it belongs to the algorithm that created that innovation? So all of these I would say that we need to begin to think of a judicial system that can deal with these kinds of problems. We already have a cloud judicial system. But do remember that these very different kinds of, and I would almost call them philosophical problems, are going to turn up at our doorstep very, very quickly. And we need to be thinking about them.

Thank you. When UPI came in, I think about a decade ago, and we have the benefit of having the NPCA chairman himself being in the room, I think it was more than payment. It was trust in an invisible system. and today AI is becoming that invisible system that is sitting quietly in our credit underwriting decisions, our onboarding flows, grievance redressal systems, even regulatory reporting and I think that’s, it was a great discussion to talk about how do we embed trust in an AI system that is fast evolving because at the end of the day we’re thinking about the theme of the summit which is people, planet and progress all in the same breath. People, how do we protect them from opaque systems or bias?

Planet, how do we scale sustainably and responsibly and progress because it doesn’t have to be only fast innovation, it has to be fair innovation. So I think a lot of great thoughts today that came in the panel discussion and I’m extremely grateful to everybody who made time to have this discussion. Sanjeev sir, we could have some closing thoughts from your side. Well, you mentioned trust. Let me say that… while it is fair to trust UPI, but as I said it is relatively speaking not an emergent system. Deliberately in fact, you don’t want the UPI to be innovating on the interface. It can innovate at the back end however much you want, but you don’t want any surprises.

I send somebody 100 rupees and he gets 120 rupees or 80 rupees or on average you will get 100 rupees. That can’t be the basis of a UPI. So in that sense the UPI based system isn’t backbone infrastructure. It is not deliberately emergent. But AI systems are emergent. It can give you different answers at different points in time depending on what it’s trained for, what is the context, what is the things you have and in fact that is the innovation. If you fix it in a box to start with then you won’t get the innovation. But on the other hand if you give it some open ended thing yes, presumably it will improve but sometimes it may deteriorate, sometimes it may lie to you so in that context what I am trying to say is that in the case of artificial intelligence we should use it but we certainly should not trust it in fact its future is based on a certain level of skepticism, healthy skepticism that we must have about its capabilities it will do amazing things but in my view we should be clear that it is probably much much better at solving bounded problems it can play chess for example very very well but I doubt it can plan your career it’s an unbounded problem so if that is how you think about AI then what you need to do is to as I said begin to think this through in terms of how you apply it in particular boxes and where it has a clear set of things that you are trying to do.

So as I said, bounded problems and even there, verify.

With that, we have audience questions. We have one question from Aditya, the founder of First Tile.

Thank you. Good evening. That was an incredible set of points that came up. Actually made some really interesting notes about the capital markets equal in Sanjeev that you drew. I thought that was a really interesting way of looking at AI and we’ve been in so many summits. I think this is a very, very interesting way that you’ve put it about risk and ex -ante versus post -ante. I had one question for you and I had two suggestions or requests. For Praveen and Davis. From an AI stack perspective, every summit or every conversation across different countries is looking at all the different components of the stack. And there are two things that kind of come up in most of these conversations, which is around sovereign data asset and leverage that comes out of it in terms of tools and models and so on.

Where is India’s perspective in all of this from a sovereign data asset utilization, the model leverage? And I think different countries are looking at their stack as their stack in which they’re going to give you access and so on and so forth. So I think that is something that will be great to get your perspective.

So obviously, India, with its very large population, has stacks of information on all kinds of things, from health to consumer behavior, et cetera. So in some ways, this is a good place for a huge amount of data for experimentation on human behavior and so on. But of course, you know, if data is the new thing, the new oil, the new… we need to be clear that we own… those rights if it’s our data I mean I’m not even getting into the privacy issue I’m assuming here that it’s all that has been taken care of so we are using anonymized data but even then we should at least have the rights to that data and also to some part of the processing of it there’s no point in saying that you know that we have the data but we neither have the rights to it nor do we have the oil rigs to pump out or the refineries to process the new oil so this is the context in which you may have seen in the latest budget we announced almost quarter of a century sort of tax holiday for putting up data centers in this country that’s not a trivial thing to do why are we doing it well basically because as I said data centers are the oil rigs of this new kind of oil.

And then, of course, we need new companies that will process this oil. Those are the new… We have created one, EI -LLM, but frankly, everybody gets very excited about LLM. LLM is only a very limited, in my view, not even the most interesting usage of artificial intelligence. It just happens to be that it is linguistically talented and consequently, you know, we use it for that. But there are many, many more interesting uses of AI. And as I keep coming back to you and stating that we need to create an ecosystem and that ecosystem, we all say, oh, you need to have, you know, half a trillion dollars of investment to create. Actually, no. Much of where you will end up with this use of these refineries, so to speak, will be quite… bounded problems in certain spaces.

So there is more than enough space for startups with much more modest budgets to do interesting things in AI. And I’m not just talking about people building use cases on other people’s. I’m saying literally bottom -up uses of AI. So I think there’s a lot to be done here. It’s an open space. This is basically like discovering the Americas. But, you know, yes, Spain did have an initial sort of starting advantage. But the great empire in the world was actually built by Britain, which was actually a late starter. So there are many, many countries in the world who you do not think today to be a particular player in this game, who will also turn up here.

And one of them could do much, much better than the guys who you think are at the cutting edge today. So this is an emergent situation with all kinds of unintended consequences, uses, positive and negative will happen out of all of this. I think the key here is to be nimble, keep your eyes open, including on the regulatory find, and do not have set ideas where this whole thing is headed because, frankly, we don’t know.

No, thanks for that. You know, I’m the founder of First Eye, which is a customer data platform. We work with a large number of enterprises on data, all consent. And so we get a ringside view to the application of all of that that you’re saying. And this kind of leads me to the suggestion. As a supplement, we have AI course, which is a repository of data sets, which is growing. And then for the financial sector as well, we are looking to, say, aggregate, to start with synthetic data and then maybe take up, take correlated data from the regulated. entities with their concepts so that would come into use. Okay, awesome. Actually, that kind of goes towards my suggestion bit for the two of you, which is I think, you know, Praveen, when you spoke about the sandbox from an IFSA perspective, I think the ability to extend that beyond just IFSA to, you know, also the other regulators is something I think will be very, very interesting for at least folks like us because we work with a number of entities which cut across different regulators and an associated point is, you know, today there are so many regulations that come in and I think there’s a lot of, there are two opportunities that I see exist.

One is there is different interpretation of the regulations by different entities and second is as a large data processor, not a data owner, but a data processor, I think there is stakeholder, we are one of the stakeholders in that whole process and today we may not have the adequate access or a seat at the table from a regulatory interpretation standpoint. And there, there is, I think, an opportunity for us to define something which is like, you know, what is a consent -backed API for data consumption, for example, and having a regulatory definition of that with participation from a data processor like us. And we’d love to kind of see if there are processes that allow somebody like us to engage with the regulators.

We are open to that idea, but you have to remember one thing. IFSA is a jurisdiction, you know. It has its set of rules which are different from domestic India. So there is an interoperable sandbox mechanism in place between IFSA, RBI, SEBI, and IRDAI. So a solution that spans across the four regulators can be tested within the sandbox. But the issue is not technological. It’s not fiscal or financial. It’s legal. For example, in India, INR transactions are the norm, right? In IFSA, INR transactions are not permitted. You have 16 foreign currencies that are enabled. and you have to do transaction in those 16 currencies. So if your solution is not compatible across these areas, just to give you an example, then the sandbox experimentation will not go through.

So there are a lot more nuances like this which affect the rollout of pilots within the intraoperable sandbox. So just to give you an example. With respect to movement and processing of data, I will not comment at the moment because there are certain things in works in IFSA. So I leave my RBI colleague for that.

So just like my colleague said, we already have an intraoperable sandbox across regulators and it is on tap. So earlier it was team -based, but then now it’s on tap. Any type of product can be tested in the sandbox. But just to clarify on the sandbox, it is only when the regulated entity feels that the existing products or services is violating one of the regulations. So there are… very few number of entities which come to the sandbox because in general they are not required to be, required to come to the sandbox if they feel they are compliant to the regulations there is no need to come to the sandbox but then we are also thinking of another sandbox where we also provide some more than in terms of monitoring the regulation we can provide, we can support the innovation in terms of say compute data or tools so that is that is also in the thought process.

We have been one of the beneficiaries of the sandbox and the hackathon at 5Money and the process has been phenomenal the way the RBI fintech teams engaged so maybe Aditya I can share some notes with you offline. but I think thank you this has been a phenomenal panel and great discussion on embedded governance when AI is making space in all things financial services how do we make space for governance in AI that was the theme of the discussion and I am very pleased to hear the views of this panel and I am grateful for making time thank you everyone applause thank you I am actually not going to say anything more apart from the fact that thank you and we will have a quick give of the mementos from India AI mission so my my colleague Kriti will do that so starting with applause applause applause applause applause applause applause applause applause applause applause applause Thank you.

Thank you. Thank you. Thank you. Thank you. Thank you.