LIVE: Satya Nadella Unveils Microsoft’s AI Vision at Mumbai AI Tour

🎥 Dec 11, 2025 📺 Business Today ⏱ 69m 👁 2093 views

Watch LIVE as Microsoft CEO Satya Nadella addresses the Microsoft AI Tour in Mumbai, unveiling how Artificial Intelligence and human ambition will together shape the future of technology, productivity, and innovation. Nadella outlines Microsoft's latest AI breakthroughs, India’s growing leadership in AI adoption, and the massive opportunities emerging across industries. From enterprise solutions to everyday tools, Nadella explains how AI will transform work, creativity, and the global economy. Join us for real-time insights, expert commentary, and exclusive highlights from one of the world’s m...

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About Satya Nadella

Satya Nadella, chairman and chief executive officer of Microsoft, has been active in public appearances over the past two months, including a live event with The New York Times's Hard Fork podcast, the company's Build 2026 developer conference, and the fiscal third-quarter earnings call. At Build 2026, Nadella announced the Majorana 2 quantum processor, which he said provides a qubit mean lifetime of 20 seconds and operations at one microsecond, and introduced the Surface RTX Spark Dev Box, a device with one petaflop of AI compute. He also discussed a partnership with NVIDIA, including the RTX Spark system-on-chip and the Windows DGX Station, which he described as a "desktop data center." During the earnings call, Nadella said the company expects capital expenditures to increase to over $40 billion in the fourth quarter as it adds capacity for AI demand. In his remarks, Nadella emphasized the concept of a "frontier intelligence ecosystem" where companies can participate by building on top of platforms rather than simply consuming models. He stated that "everyone is a stakeholder" in AI and argued that the technology must deliver tangible benefits to communities, citing data centers in Quincy, Washington, as an example of local economic gains. Nadella also addressed public skepticism about AI, saying that "the perception is terrible" and that companies must "do the hard work" to earn trust. On the podcast, he discussed the need for AI to be economically viable, noting that "the marginal cost of productivity improvement has to match the marginal cost of the token."

Source: AI-verified profile updated from Satya Nadella's recent appearances. Browse all interviews →

Transcript (23 segments)

✨ AI-enhanced transcript with speaker attribution

Satya Nadella0:00

So we always start there right with the customer experience. Now you can think about and reimagine it. Whether it's the employee experience, whether it's the operational efficiency, whether it's the rate of innovation, if you're a drug company, can you really get through clinical trials faster? Can we get more new drugs out there? That to me is ultimately moving of the frontier that we are all chasing. And to do that though you kind of have to embrace a new approach even right what worked previously in some sense you have to do this hard job of unlearning and learning what's possible right sometimes we sort of pattern match too much from what worked in the previous era may not necessarily work in fact there's a new frontier so when I think about that it starts with that mindset freeing ourselves that there's a new approach. For example, when it comes to AI, right? If you look at even a building of an AI solution, you don't start with a spec, you actually start with the test, right? I mean, when people there fancy new words talk people talk about evaluations, right? You create these rubrics to do eval outcome, then you create a learning system, then you hill climb on that learning system. Guess what? That's kind of literally inverting the process of building an information system. You start from the outcome. You create a robust eval and then you spec versus going left to right. But the key thing is that means you got to pick up new skills all of us. And in order to pick up the new skills, you kind of need a new tool chain that you are using every day. And to be able to then have all of your data that is being brought to harness this new tool chain, this new skill set with the new mindset. That's really the way we want to approach it. So to facilitate this, right, this can't just be an abstract framework. This has got to be an everyday practice for all of us. You know, it's an information worker today or a software developer. All of us are going to be using essentially the same approach to realize that we've built a tech stack and I want to just literally walk up this or walk down this tech stack. So the starting with the experience layer where we have taken this idea that you know let's bring this AI co-pilot right where you work right you may be in outlook you may be in word you may be in excel you may be in teams you may wherever you are doing your work how do we bring the co-pilot there and think of co-pilot though as not just a request response right that's what we've been doing now nearly for two years, right? You know, we know now that hey, we can ask it any question. It'll come back with a better answer than anything that we have previously experienced in let's call it an information retrieval search type experience. But now we have agents. In fact, think of co-pilot as your browser for the agentic web. In fact, right inside of co-pilot, you have very powerful agents built in. Like one such agent is your researcher and researcher with computer use is a real breakthrough. It's literally like having 24 by 7 someone very sophisticated who is your research assistant who can go take any topic and then because they have a computer right so they just are not like think of it as not a single shot like I go and bring back information after thinking they can the researcher can use a computer to do research right so it's not only you have a computer your researcher has a computer so that's the way to conceptualize same thing with analyst. So I can load a whole bunch of Excel spreadsheets and give it to an analyst and it's kind of like giving it to your data science department, right? Or to the data scientist. So it's again having a 24x7 data analyst who can then go give you insights. And lastly, it's like one of the things that I'm very very excited about is what happened in software development is going to happen with Excel and Excel agent. Right? So I in fact had a chance to participate recently in the Excel world championship. By the way, ESPN and even broadcast Excel Championships. We have an honest to god great way to sort of celebrate the Excel province. And so I was able to participate in it. You the digital challenge using this Excel agent. It is so cool to be able to see and I worked on Excel all my life essentially and to be able to sort of see how the agent mode understands deeply the entire semantics of a spreadsheet right so it's not just a one shot I created a great model but it's the ability to iterate on a pretty sophisticated model continuously using this agent mode just like how we do in software engineering so it's just exciting to see this and also it's really to me at the end of the day all these tools are like the new word, excel, powerpoint, office, right? That's kind of that's as simple as that. And they're in the hands of everyone here and I see it being used like that, right? So no one is sort of, you know, praying at the altar of these tools. They're just using them. And to me to see the proliferation, the diffusion is probably faster than anything I've seen. Right? I've come to back to India. I've come back to Mumbai throughout every generational shift in technology starting in the early '90s. But when I see now the rate of pace of change, there's no difference quite frankly. I could be in any city anywhere in the world and to be able to see all of these applications just being broadly diffused. To show you some of this in action, let me invite up on stage my colleague Zoe. Zoe, take it away.

Zoe6:17

Thanks, Satya. I'm Zoe, a product marketer on the Microsoft 365 Copilot team. And like all of you, I start my day commuting in and preparing for the day ahead. For that, I'm going to use Copilot on my mobile. Hey, Copilot, what's on my agenda for today?

Copilot6:42

You've got a few things lined up today. First, there is an AI tour India meeting that started earlier this morning. Then at 11:00 a.m., there's a Ktoso sales call. Later in the afternoon, you've got a team sync at 2 p.m.

Zoe6:58

Thanks, copilot. And has my manager sent me any emails?

Copilot7:04

Yes, you've got a few emails from Nicole. Just yesterday, she reminded the team about a Friday mixer happening in the common area. She also mentioned that finalizing the monthly business review should be a high priority.

Zoe7:18

She also thanks Copilot. Copilot doesn't just have my work context. It knows who I am, what I work on, and who I work with. It's why I use Copilot. It's a true AI assistant. Now, I want to take a look at my manager's ask around that MBR updates for my V team. And you'll see I'm actually using GPT 5.2 which we released yesterday and it's immediately available to all Microsoft 365 customers. GPT, yeah, it's exciting. I know what I love about GPT 5.2 is it's allowing Copilot to be even better at finding the most relevant resources. So my responses are very contextually relevant and I'm able to take quick action and it makes a very visual output. Now only copilot is able to combine this constant model evaluation with your work data to provide the most relevant response. Now I want to go and update my existing monthly business review document but I want to change it with my November data. For that I'm going to use agent mode in Word. Agent mode allows the agent to edit, to draft, to format the document, all with natural language, but it still keeps me in complete control. And I can see it's starting to look across all of that work data, right? My emails, my meetings, my team chats, my files. Now, that normally takes me hours to do. I have to find the right information. I have to sift through it. But now you'll see the agent is actually actively applying it on the left hand side. And you'll see that it's actually leaving parts alone that haven't changed month over month like our mission, but rather using this to update everything and keep me on par with exactly the November updates. Now last, I want to make sure I understand our team budget for the next fiscal year. I'm going to again go to Excel and I'm going to turn on agent mode and ask it to get me a little bit more aware of what's been spent, what's uncommitted, what's at risk, and to build a visual dashboard so it's easy for me to understand my data. Agent mode in Excel natively speaks Excel just like Satya said. So, it's not going to create a random number that I don't know where it came from. It will actually build formulas right in my spreadsheet right where my budget already exists and it will even create native objects like charts and tables things that I can continue to manipulate. It also walks through everything it's doing on the right hand side. So that way say my manager Nicole comes to me and asks how did I come to my conclusion? Well, Copilot actually helps me understand what it did. That way I can continue to work with it. I can also ask agent mode to do simple things like conditional formatting which you'll see highlighting things in red that maybe are at risk. All of these things to continue to work with copilot and agent mode in order to get a better understanding. And you can see it's created this dashboard live. I can if I click in I can see these rich formulas that's actually built to give me an answer, the conditional formatting to highlight what's at risk in red and a native graph that actually I'm able to manipulate even further should I want. Now, Copilot, it hasn't just made me better and faster at my job, it's helped me make more impact, and I can't imagine working without it. Back to you, Satya.

Satya Nadella11:06

Thank you so much, Zoe. Whenever I see that Excel demo, I like to think about it that, you know, when I had hair, I loved Excel. And when I don't have hair, I love Excel. I tell you, it's one of those generational things that just gets better and better in spite of my follicular challenges. You know, to me, if you sort of take that experience layer, one of the things that's super important in the age of AI is to think about your data as one of the most strategic assets. But you got to bring that data contextually to the AI. In fact, people talk about it as context engineering. And I think it's a good term for it because in fact a lot of what needs to be done both at this engineering level and even I would say business decision-making level is to think about not the silos of the previous generation but the contextual way you can feed intelligence with data. So to that end for example underneath Zoe's demo is perhaps the most important database in any company that uses Microsoft 365 today right if you think about it the tacit knowledge inside any corporation any organization is the knowledge of people their relationships with other people their work artifacts whether they're spreadsheets documents their conversations in email meetings in teams to be able to relate all that because that's where the tacit knowledge of an organization is and it's in that database and so fundamentally what we have transformed that is into work IQ right so when we say work IQ it's the stateful part underneath M365 that now can be brought to bear in the context of any AI solution you want to build not just copilot any agent you built out there. You can now use work IQ. Think about that. The second thing we've done is in fact one of the other ubiquitous tools all over is Excel and PowerBI. So that means you've taken real great pain over decades building these semantic models to do analysis and now with fabric and fabric IQ you can take all of that data along with all the operational data and make it available to your AI. And then the last one sort of really makes it all come together. So what we've done with foundry IQ is said what people describe as retrieval augmented generation right so one of the biggest things that we have done in the last couple of years as we built these AI solutions is to do retrieval of data and we've now built the next generation retrieval system essentially it does more than retrieval it in fact plans and executes and reasons that plan over that plan on how to retrieve relevant data from work IQ, fabric IQ, and any other blob storage, unstructured storage or what have you, and bring it in the context of your AI application. So that's what this IQ layer is. In fact, it's probably one of the more salient yet important pieces on how anyone who builds any AI solution going forward will be most successful. Right? In fact, direct correlation between the evaluations or the sort of performance of your models will be how good is your data being brought just because in some sense models are becoming quite frankly a commodity right so there is lots and lots of models out there which are very very capable the question is how do you marshal that capability I think it'll come down to having a great experience layer where people can discover the agents you're building and having a fantastic sort of capability around context engineering. Okay, so the next layer for us is really about now that we have an experience layer, we have the data set up, let's build agents, right? And the beauty of building agents quite frankly is like building spreadsheets or writing a document. It's not more mystical than that. In fact, agent builder that's built right into Copilot is like saying, 'Hey, I dock new, right? Or spreadsheet new.' And so we start there. In fact, now we have an app builder. So, in fact, Bill's big thing always for the from ever since I joined Microsoft in the early '90s was why the heck do I have a difference between a document, a website, and an application like in you know his concept was there should just be one thing and it I should be able to transform and guess what we finally have it. Which is app builder can you can go in and just specify the app you want to build and it'll build it. It's kind of like a document. It's kind of like a website. It's kind of like an app, right? So that's the power. Then copilot studio is another way to think of it as build out of your agent. So again, as a using a natural language prompt, you can go build an agent. You can ground it in some data. And you there you have it, you have an agent. And so we are building out foundry in fact without any cliffs to be able to then say, okay, we now have agents. Can I even orchestrate multiple agents and build full agentic systems? Microsoft Foundry allows you to do that as well because the multi-agent frameworks are there. All of the tools that you need in order to be able to build multi-agentic systems are there. We also now of course have all these models. We have 11,000 models. You say what? Why do I need 11,000 models? In fact, even for me this week, it is a great reminder of why having this diversity of models is going to really make this world a better place. In fact, we launched and we announced in foundry as an open weight model a model called Gigatime. There was an article published in Cell and quite frankly it gave me goosebumps when I sort of read about it and learned about it because it's work Microsoft did with both University of Washington as well as Providence hospitals and what it does is if you think about the challenge of someone with cancer today when you sort of try to understand whether immunotherapy will work you kind of have to model the immune system essentially. And so there's a test for that. The problem with that test is it's a complex test. It takes a long time and it costs a lot of money. And so what this particular model does is it does a simulation of the test. So you can literally take a simple pathology of the tumor, right? which is literally like a microscope image of a tumor and then use essentially gen AI to fill in. So it will do the simulation of what is the basically spatial proteomics of the immune system and say you now can have a test. So I was thinking about it right with that model that means some entrepreneur in Mumbai is going to pick it up and say you know what I'm going to build an entire sort of simulation lab in silico and make it available to every city in Maharashtra and in this country right so every hospital can start doing what now today is done in the few tier one hospitals and costs a lot of money I that's in some sense when you're playing the game sometimes you forget why you're playing it. This is why we're playing it. We are playing it so that we can actually use this innovation to make a real difference in the world. So it's exciting to see how this is all coming together. Now we're bringing as I said all this together in this tool chain. This tool chain is going to become what you will use. In fact GitHub is where you would start interfacing with all of this app stack. Right? So if you think of the new app server as foundry the tools are visual studio and VS code and GitHub and talking about GitHub it's really exciting to see the growth of GitHub in India. It's I mean it's tremendous by 2030 India is expected to be the number one country in terms of GitHub participation. You know it's tremendous to see not only just the participation but the ambition level of the projects coming out of India just continuing to improve and you know get better and so it's fantastic to see that now we're building out GitHub by the way as agent HQ so what I mean by that is you go to GitHub and you will have access to all the coding models that you could use in the context of your repo and so that's the idea it's not about sort of having one model but you have your code repo just like work IQ think of this as code IQ right so that's kind of really it like your code is your most important resource you want that and then you want many many models over the years to sort of keep working and creating more of that repo and the repo features and so that's what and by the way the form factors right if people say oh wow will I only use autonomous agents will I use only an IDE with agent mode will I use a command line. Guess what? I use all three all day long, right? I mean, that's it. Like the form factors of how I interface with AI are going to remain essentially always some IDE, some CLI interface and a new chat interface, if you will. And that I think is the way you'll interact with it. But to show you all of this in its full glory, I want to invite up on stage my colleague Karan. Karan, take it away.

Karan31:23

Thanks Satya. A few weeks ago at GitHub Universe, we announced agent HQ, which is an agentic platform that unites every agent, making them native to the GitHub flow you're already familiar with. So let me show you a demo of what that looks like. All right, so I have a demo app here that's a storefront for some of the nostalgic toys which might have been common in many of our households. However, as you can see, the app doesn't really have any search or filter options, and I want to add that functionality. So, I have my code repo here on GitHub. With the new agents panel, I can now kick off an agentic task from anywhere on GitHub by just describing the task and delegating it to the copilot coding agent. So, copilot starts working on it in the background. I can assign a task to copilot from anywhere I work on github.com in VS Code in the CLI or even on my mobile. All right. While working across multiple repositories and tasks, I have delegated many of these tasks to copilot and I want to know what's going on with it. So now I can see all of my agent sessions in a single mission control view both ongoing as well as completed once over here. Not just that, I can also start off a task from right here while using custom agents that I have created or have been built by partners. So these custom agents are domain experts which extend the copilot coding agent across all of your tools and workflows. All right, so let's dive into the session that we just kicked off and see what Copilot is working on. So I can see the progress of copilot here on the left and also the draft PR on the right. So I'm a developer. So which means I am still in control. So I can even steer a ongoing session midway to have copilot work in a slightly different direction. So this will take a few minutes. So I'll let Copilot continue working on that in the background, but I want to show you one of the agent sessions I kicked off earlier for the same feature. So I can see it's completed. And then there's a summary as well. And ooh nice screenshots as well thanks to the Playwright MCP. I can also take a look at the files it has changed over here and also ask it for any change if I need right over here. All right, amidst all of this if I want to have a chat with copilot to ask it something or so I can jump into copilot chat right here as well. So copilot provides me a choice of various different models from different providers including GPT 5.2 we just launched last night and already available on GitHub copilot. It's how fast it is. And yeah, all right. Not just that, I can also bring in my own models from Microsoft Foundry. So, I have a few models that I've deployed on Microsoft Foundry, including a couple of them that I had fine-tuned myself. And I have brought in all of these models to copilot by connecting them to my deployments in foundry. So now I can actually use all of these models directly within copilot be it on GitHub or VS code. Now I was just doing something and I fine-tuned one of the model just for fun to see if I can converse almost like a developer you know in Mumbai. So I just ask it something simple saying what is Kubernetes your pods notes and this is coming and it says simple language this is what containers are this is what kubernetes is and it's so awesome right because this is coming from my own model that's deployed on foundry which I can use in copilot right that's pretty awesome all right So speaking of deployments and everything I had also created a PR to implement a new product detail page you know sometime earlier and I can see that copilot has already reviewed my PR and also left a few comments on it. So let's take a look at some of these suggestions it has left like this one here which speaks about DB connection pool exhaustion or you know this one right here which speaks about type safety. So this is the new agentic copilot code review which combines LLM detections tool calling and also deterministic scans that help you with smarter reviews. Not just that, I can actually ask Copilot to help me implement all of these suggestions in a single PR which will again kick off an agentic task for me. All right, we all know how important security is, right? So thankfully I'm also a security admin for this account on GitHub. So with the new integration between Microsoft Defender for Cloud and GitHub Advanced Security, I can now specifically filter for runtime risk issues in production that have been identified by Defender. All right. Right here. So that's really nice. And a campaign to address all of these alerts was created. And oops, I see some of them in my repo as well. But not to worry because copilot can also help me fix these security issues. So I can just select all of these and then say assign to copilot and then copilot will go off and then create a PR to address all of these security issues. All right? you know, so now we have multiple different agents working on different tasks in the background, but I want to write some code myself as well. So here is the agent session for the search and filter function that we were looking at earlier and I want to make some changes to it. So I can continue iterating with this by opening this directly in VS code which will open up the session for me. So I can either check out the branch or even apply the changes directly in my current branch and I can continue working. So I will open up the familiar chat interface here in VS code and I'll switch to my agent mode. probably use one of the models I deployed from foundry and I will ask it to make one small change which is I also want an autocomplete feature for the search bar as well. So this can continue working in the background and you would have seen that just like on github.com I also have a mission control view in VS code as well where I can see all of my local agents my cloud agents my background agents which is running as well. All right. So, I want to implement a new feature. The toys are great, but I want to make a bundle of it and almost gift them as a playbox. I know many of you would love that as well, right? But I need to plan how to go about implementing it. So with the new plan agent in VS Code, I can ask Copilot to create an implementation plan and also keep iterating with it until I am confident and ready with it. So I had created one of you know this plan earlier as well which I'll just open up right over here. So you can see it gives me a detailed plan for all the steps that needs to be accomplished. So whenever I'm ready, I can kind of continue coding this or I can hand it off to an agent as well to work on it in the background. So I can hand it off to the CLI agent and I will say include the changes. That's fine. And this will start working on this agent in the background. All right. So some of this will take a bit of time to complete. So meanwhile if when all of this task would have been completed let's see how our app would look like. So it will look like something like that with all of the filters that are there and also my search and autocomplete feature and I can go start playing my brick game. All right. So in the past few minutes we went from so many different ideas planned them and also coded them using copilot coding agents in the cloud on github.com in VS code in background using CLI agents had that code reviewed with the copilot code review agent and also implemented the security fixes using copilot autofix agent all the while having a ability to look at all of my agent sessions, steer them in the single mission control view on GitHub or even in VS Code and that is agent HQ. Thank you. Back to you Satya.

Satya Nadella31:13

Thank you so much Karan. And so you know when you look at all of these tools that Karan showed, you know what does it do? It inspires you. So recently we had Thanksgiving in the United States. So we had some time off and so what does one do when you have time off? You build and so I built an app. And so this is by the way this is my regular laptop you are seeing. So this is my Azure subscription and this is in fact my app that's deployed right now I think in Canada Central. This is my repo. This is my GitHub repo. So this is my code. In fact the way my standard sort of way I work is I have a Windows 365 setup. So it travels with me everywhere. And then of course I use GitHub and then I use code spaces. So this is I think it'll show up with the code space here. So it's kind of like turtles all the way down, right? So I have my code space running on GitHub running on Windows 365. So that's kind of my virtual environment that I travel with. And of course like as Karan was showing every morning I get up and my favorite place to go is here right which is I go to my repo and I go to my copilot and start assigning it tasks like every day there's some multiple agents I kick off like this morning I said please upgrade this entire app to GPT 5.2 right so and it's actually done and when I'm done with my keynote and I'm on a flight back I'll kind of get there on my flight with Wi-Fi and be able to actually look at the PR and push it if you will. In fact, I'll test it once in my code spaces and then I'll commit. But that's in fact it shows you the power of how you can literally start really taking simple tasks to big updates and start powering through them. So what did I build? So what I built is essentially a new deep research tool. You know, one of my life's ambition is to figure out how to get a job in the copilot team. And so I'm preparing for it. I'm sort of desperately trying how to get competent enough to get hired. And so therefore, I said, okay, let me build a new more sophisticated deep research application. And so the thing that I did is you know, I said, there are all these models available. So why don't I create decision frameworks that work on top of the model and one of those decision frameworks is Andrej Karpathy who's a famous AI researcher came up with this LLM council he called it right so the idea is you'll have like a selection committee you'll have multiple members of the committee right so in this case I can have GPT 5.1 or 5.2 today Claude Gemini Llama Grok whatever right pick your favorite selection committee then you elect even a chairman like you can say who is the chairman is it Claude or Gemini or GPT or what have you pick your chair and then go ahead and issue a query and ask it to do stuff and then another one I did was DXO this is a pretty cool decision framework this comes out of healthcare in fact we first implemented it in fact we've implemented it in healthcare where you have just different roles. So for example, one role is a lead researcher who does let think of it as exhaustive breadth first research. There's a critical reviewer and by the way you can assign different models to these different roles. So I have a lead researcher that happens to be Claude, a critical reviewer that happens to be a GPT. And what does the critical reviewer do? They that particular role finds method problems, right? say recency bias or period bias whatever are the issues which are cognitive biases then you can have domain expert data analyst so different roles and in fact when we applied DXO in healthcare it turned out that having multiple roles work together in a multi-agent system outperformed any single model right it's intuitive right why not have all the smart people working with you on a particular decision versus one and so that was DXO then I implemented even another one called ensemble. And the idea with ensemble is you sort of fire off parallel queries anonymize the responses so there is no bias even in selection. And then synthesize it right in fact last night I said well let's even implement a regular old debate. So this is a new feature I added and thank god it's showed up here. And basically think of it as chain of debate. In fact, I think of all of these as instead of thinking of them as chain of thought, thinking of all of this as chain of debate. And I said, let's actually have a full-on debate. So, the bottom line here is you can have different formats of, you know, even debates. You can have pros and cons, SWOT, you can have risk versus impact, counterfactual versus devil's advocate, right? So, you can even pick your form framework. You can have critiques. So, each sort of each person makes an argument, everybody else critiques.

I can have multiple rounds of it. So I was just kind of I had a lot of time I guess in my hotel room yesterday. But I went on and added features. I said okay let's have, oh by the way, I even added because I was spending so many tokens I said man I might as well actually add cost control to my thing. And so I said do I need fast lower cost or deep higher cost. I'm picking balanced here. I can pick the different research analyst, system architect, risk officer, three types of roles, then have multiple rounds. So you get the point. So of course you build all this. What does one good old South Asian do? Use it to select the best ever Indian test cricket team. I think we need one. And so if I go to my history, you'll see I've been at it. I've been working it. In fact, I have a fantastic MLB lineup as well. But since we are here in Mumbai, I'll show you some of the stuff. So I'll show you the council one. I'll show you what it came back with. In fact, let me increase the font here. So this is the chairman synthesis. It shows me, obviously Sunil opens with Sehwag, Rahul, Sachin, Virat. A man it picked. So this is the synthesis and it shows VVS at six and seven and then it goes on. Here's the interesting thing. The chairman's report says that there was unanimous consensus, Gavaskar, Sehwag, Dravid, Tendulkar, Kohli, Kapil, Ashwin, Bumrah. But the big debate of course was, do you need an additional batsman or not? And thank God they selected, at least being a Hyderabadi, I'm really proud that they made VVS Laxman in there. And here's the interesting thing. It waited 51 and Claude's inclusion. I mean, think about this. These two models bid for my man Laxman, because of his crisis management and made the point about why, and then the other debate was who is the captain. In fact, I think, oh by the way, the Kumble versus Zaheer was also a very good one. It sort of chose Anil versus Zaheer. Zaheer is going to be 12th man, you know, depends. I guess that's where I think there's more work to be done. I would pick Zaheer some days and sometimes depending on where you're playing. Captaincy debate, it picked Kohli. So the key thing is I see the annotations of every chain of debate and it gives me insight. In fact, if I go back to show you one other case, let me go back to my history again. Let me go to the DXO view. I think this is interesting because the DXO view is slightly different. It says here is what the lead researcher did. Then it says here's what the critical reviewer did. But here's the cool thing. Look at the way it found the biases, the error bias. So the critical reviewer's job was to say, okay, when I'm selecting something, are you mixing up your stats? I mean, I always say, you know, sometimes you could say wow the fitness levels of the modern teams are so great and wonderful, but man, watch Gavaskar go in to bat without a helmet or even a, I don't know, Hazare go on uncovered wicket in play in England. How do you really equate for that? So that's the error bias. And so to me, to be able to have all these models debate that issue is what this is all about. So anyway, you get the point. You can use these decision frameworks as the new form of metacognition. So if you have all this abundance of models, the ability to literally do what I did, which is just build your own multi-agent system, that's the new commodity. I mean, the reality is, all of us are going to be doing this work just like how we do spreadsheets or documents. And if we have that power, then the question is what are we going to do with it? And one of the things I think is exercise better judgment, better decision, and in high stake situations in healthcare, in financial services, in insurance, in supply chain. And that's the beauty of it, to be able to think about these as metacognition frameworks for us to apply better judgment in a world where we have all of this. One of the other things I should mention is I built all this. I even made it into a Copilot. So this is all in my Azure private tenant. And I then did a basically an open API to it. And so then I made it into a Copilot agent and then I said great, let me go deploy and guess what, I was caught. So in other words, the Microsoft DLP, data loss prevention, came in and said you can't deploy it because this has to be deployed inside the Microsoft tenant. You just can't point it to an external agent because that's a massive exfiltration problem. And that is thanks to this other part which I think is the runtime of agents we have built called Agent 365. And Agent 365 takes our identity management, our Defender, things like Purview and data loss prevention, all of that, and brings it to the agent world just like what we have done for end-user computing. We're now doing it for agents because if people are going to build powerful agents like the one I built, you want full compliance, you want full visibility, you want full governance of it. And that's what Agent 365 does. Because you can't just run around and say I have thousands and hundreds of thousands of agents without that security and governance and visibility. And that's really what Agent 365 delivers. The beauty of all this is there is significant momentum, significant ambition level to translate this ultimately into people doing unbelievable things. So this morning I had a chance to meet with for example the folks from Adani, who are really doing this invoice to payment and reduce something that took 20 plus days to 4 hours. I had a chance to meet the team from Aditya Birla where they took their mobile app that's doing complex products and said okay, here's a conversational interface that just makes it simpler for them to be able to interact. I had a chance to meet with the folks at LTI Mindtree. They're doing a complete wall-to-wall transformation using things from Copilot to Copilot Studio to Foundry to do every business process and re-look at it from an AI first perspective. Mankind. It's a beautiful use case of really putting that power of AI and the expertise in the hands of the people who are the medical reps who are visiting doctors in rural areas to be able to make sure that the medical rep is confident in answering the questions and then improving care outcomes. Yes Bank has done a fantastic job of really the invoice turnaround times. So they're also doing a wall-to-wall transformation with 40 plus use cases, but really seeing the ROI in each one of these examples. Now, one of the chances I had again was to meet with the team that built this new agentic system called the Maha Crime OS. So this was sponsored by the Chief Minister of Maharashtra who's here with us. And it was really great to meet both the SP as well as the people in the team, and in fact the investigative team, and the pride they had in being able to use this system to deliver justice to a citizen in Nagpur who was unfortunately a victim of a crime. But the ability for them to use this agentic system to speed up the time to justice was just fantastic to see. So let's go ahead and play the video.

Narrator45:03

Today policing is all about cyber crime. It is all about financial frauds and it is global. We receive about 30 cyber crime reports every single day. So you can imagine the kind of influx of cyber crime reporting that is taking place.

Crime OS serves as an investigation co-pilot. You're able to have an agent that is able to detect the patterns, able to make sense of it and have it speak to the direction of the investigation itself.

The Maharashtra government through Marvel has collaborated with both Microsoft as well as Cyber Eye in terms of adapting Crime OS for the needs of Maharashtra. Ethical and responsible AI for public good is our motto and Microsoft has provided us a very safe and advanced platform.

Maha Crime OS is built using multiple technologies. Underlying this is Azure and AI services through Microsoft Foundry. We're also using Defender for Cloud and Microsoft Fabric. With Maha Crime OS, the turnaround times of investigations are decreased by 80%. Almost 100% of investigations are getting digitally registered and investigators are acting upon them.

That makes me really proud that we're able to adapt emerging technology to fulfill the needs of several millions of people across the state and make government function much more effectively and transparently for them.

If AI is properly used in governance, we can make the lives of people easier.

Satya Nadella47:59

It's a great example, quite frankly, of using the power of all this technology to help citizens of this country. And more importantly, it also is a great example of how quickly this technology is diffusing. I mean, if you thought about any previous era of tech and the rate at which it would come to impact in a context like this versus where we are, and that I think is the opportunity in front of us. So it's fantastic to see. So the last piece I want to talk about is powering all of this, of course, ultimately is the infrastructure. You got to run essentially a token factory. And when it comes to token factory, one of the most important things is this one simple equation yet very important, which is performance per tokens. It's all about tokens per dollar or per rupee per watt. You have to optimize. And this by the way is going to be the most important thing. Whether any country, any community, any state that is able to really have the infrastructure that delivers this efficient frontier of the token factory is just going to have more abundance of tokens that can then be deployed to drive the productivity, which directly is going to be correlated to the GDP growth in the economy. And so to that end, we are all in. We are building out Azure as the world's computer. We are investing in building out Azure in India. We now have multiple regions. In fact, in Maharashtra we have a central India region in Pune, we have west India in Mumbai, we have south India in Chennai, we have a DC in partnership with Jio. We're also very excited about our new south central region that is going to come out in Hyderabad next year, which is going to be the next big data center region, and we keep expanding. And to that end, I'm really, by the way, the region in Hyderabad is going to be 100% renewable, so that's the other cool thing, we're really focusing on sustainability as well. And to us, we are also building all of this with ensuring that there's real sovereignty, because after all, at the end of the day, this is not just about bringing the capabilities, but it's also ensuring that there is real sovereignty controls. And so for that, we have a full set of options. You can use public cloud, you can use public cloud with sovereign controls, that means you have the key management locally. You can use confidential computing in concert with it so that when the data is being processed, even in use, at rest, in flight, it's encrypted and the keys are with you. We also have the private cloud option. We also obviously have a region that's operated by local partners like Jio or NIC and others. And so we have a full set of options. So think of it as a portfolio that you can then use for the different workloads you have and have the assurance of your own sovereignty and control over it. We're also doing in fact sovereign data control. So Copilot and all of the things we talked about are all being locally processed. So none of that data is going outside of the data boundary of India. And so we're very excited about all of these options being available. Now one other point I would also make, since we talked about Crime OS and what have you, is one of the biggest challenges for any online infrastructure is cyber and cyber risk and cyber security. And it's an intelligence game. Ultimately, whoever has the best intelligence is going to be able to defend you the best. And so Microsoft sees trillions of signals every day. We see every nation state and every cyber criminal everywhere in the world. And we are able to harness that to protect. In fact, in the demo, the current show was pretty cool. He basically was able to take your production instance, have Defender check in real time what are all the vulnerabilities, and then have you even go back and fix those vulnerabilities. And that's not a static list. That is a dynamic list that is being monitoring essentially what is the cyber activity and the cyber attack graph. And so to me, really thinking about sovereignty and cyber resilience are two sides of risk. So when you think about managing your risk, you want to think about it because if you get disconnected, you have a sovereign everything except it doesn't have the best intelligence, you're going to be very vulnerable. And so therefore it's a much more nuanced discussion that needs real thought. And at the end of the day, it's not a one time decision. It's a continuous monitoring of that portfolio of risk and opportunity. So to that end, we are very committed to this country. And therefore one of the things that I was excited to have a chance to meet the Prime Minister earlier this week and even announce the biggest announcement. It's our biggest investment in Asia, 17.5 billion, which builds on top of the three billion we announced earlier in the year. And so we are obviously very excited to bring all of this infrastructure to empower ultimately all the citizens of this country, all the developers of this country. And so that's where I want to close out with, which is to us, all this is about empowering every person and every organization in India to achieve more. To us, whether it is things like Gigatime which allow us to think about making personalized care or even precision oncology possible in every tier 2 city in this country because an entrepreneur here will take an advance like that and parlay it into health outcomes that matter, or the Maha Crime OS that's going to deliver justice to someone who was a victim of some crime in Nagpur. To us, ultimately that's why we do what we do. All of us working together to realize the opportunity ahead of us in this age of AI is an exciting time. I hope you all have high ambition for what you can do. We sure do for you all. Thank you all very much.

Narrator55:04

India has more than 400 million unorganized workers. They're earning on the day-to-day wages and not getting any benefits. We need to shift the people from the informal to the formal sector that would help us to develop our economy. Through the initiative of e-Shram, the national unorganized workers database was developed and we are able to provide those workers with social security benefits, also giving them access to the National Career Service portal.

NCS is a one-stop solution for job seekers, employers, training providers and counselors.

We have AI based matching between the job seekers skills and the employers. So any informal worker can go to the NCS portal and match with the right employer. NCS has an AI resume builder and if a person is lacking certain skills, the AI tool helps them to develop those skills by giving them recommendations. We were expecting millions of unorganized workers to register in this system. So we wanted to have scalability, reliability and security. Microsoft Azure met all these qualifications. In addition to that, Azure OpenAI has become a game changer for unorganized workers.

Around 150 million workers are now on the NCS portal. We are also now trying to bring in more and more schemes to benefit these workers. AI is supporting us to provide opportunities for the individuals and youth of the country.

Please welcome President of Microsoft India, Puneet Chandok.

Puneet Chandok56:56

Good afternoon. Don't leave the hall yet folks. The energy is just building up. So if you could come back and I promise you we'll raise the energy up once again. So how's the crowd feeling guys? How's the energy? Let's pump it up. Let's take it up a notch, guys. Let's take it up a notch. And a big thank you to Satya for pumping us up. Love the way he framed the India opportunity. And I think the commitments that we're making to India are not just capital folks. That's our vote of confidence for India. That's our commitment to making India truly AI first. And India is at such an extraordinary moment now folks. We proved to the world what India can achieve, what a nation can achieve with digital public infrastructure. And now India is standing at the beginning of something even bigger, something much bigger. India's AI moment. India's moment to become truly frontier AI. And this is going to be India's AI century. And we as Microsoft are so proud to stand with India and make that a reality. I will start where Satya left us. Our mission, we succeed when the world around us succeeds. Folks, we succeed when India succeeds. For us at Microsoft, it's never just about technology. It's about what technology can do for every Indian, for each one of you. That's what we come to work for every day. And India's advantage will not just come from innovation. We'll obviously innovate like nobody else does, but also rapid diffusion of AI from classrooms to boardrooms. And we as Microsoft are so excited. We want to be co-pilots to India's AI transformation. And we will make that happen. So before I get to how we'll make this mission a reality, I thought I'll show you a little bit of how the world feels right now. The world seems unfamiliar. The world feels different. And if you remember, I went to Copilot, I said, 'Give me a sense of the last 20 years, how the movies played out in the world.' But do this from the lens of books and authors. And this is what Copilot pulled up. If you remember, Thomas Friedman wrote The World is Flat. 5th April 2005 is when that book came out. The world is flat and we generally felt the world is truly flat and code was moving across borders, factories are humming, the world seemed very different to today when Yuval Harari is saying that never before has the world looked so clueless. Fareed Zakaria is saying democracies looked different. The world is recalibrating folks. The world is rearranging itself. There are two forces at play. There's of course geopolitics that we're all trying to get our heads around but also AI. We have the largest infrastructure buildout in the history of humankind happening today across the world and even in India as Microsoft we're building our largest hyperscale presence but the largest AI infrastructure buildout of the century is happening and deep learning with these models that Satya spoke about is a gift that keeps giving. So these models are getting smarter and better every day. The challenge now is not to fight this world which refuses to play by the rules that we are used to but to understand it, to navigate it. And when you are in uncharted territory, when you're in unfamiliar territory, what do you do? You bet where the ball's going, not where the ball is. You bet where the river is flowing, not where the river is today. You predict where the world's going to go. So with that, I'm going to go out on a limb today and I'll give you my predictions on what's going to happen with AI and what's going to happen with the world. And I'll give you my five predictions. I might be wrong, but I will provoke you and I will make you think differently. Number one, unmetered intelligence. Sam Harris, one of my favorite authors, had this quote that I always go back to. He said, 'Intelligence is a beautiful property given only to humans.' Unfortunately, he was wrong. For the first time in the history of mankind, we have potentially the ability to manufacture intelligence with AI. We're entering a new reality, folks, where compute or log of compute will become cognition. Imagine a world where intelligence moves from something which is scarce and expensive to something that's abundant and it's available almost on tap. This is a new reality. You don't put intelligence to work by hiring people, getting a team, getting a project manager and waiting for 6 months. You buy intelligence like there's a socket on the wall. You plug in and you get intelligence. That's the world we're moving into. So that's my first prediction which is the world will soon have access to intelligence on tap or unmetered intelligence. And this will change everything about how we run businesses because every business is a bundle of intelligence, bundle of expertise. Number two, we will not be alone in the workforce. We're used to physical colleagues. We're all physical colleagues to each other. But this next generation of agents that we're building which are autonomous, they can go through unstructured and structured data, goal seek on your behalf, and come back and say, 'Hey boss, I've got something useful for you.' Those are the agents we're building. That's how we're making these models useful for you. And these agents have three things. They have perception. They see everything you see. They have cognition. They have some intelligence and they have agency. They act on your behalf with your permission but not your involvement. So that's how we're bringing them together. And again I can promise you now in the next few years or quarters each of us will be agent bosses. Each of us will delegate work to agents. We will not just admire other people's AI stories. We will have agents working for us. So digital colleagues will join the workforce and amplify us. Number three, and this is what I call the inefficiency economy today. If you look at what's happening in the world, your lawyer makes more money if the case drags on for longer. Your doctor makes more money if you're sick for longer. Your IT services provider makes more money if your project runs longer. I could go on. There are trillion dollar industries today built on this inefficiency economy where people make more money if things go on for longer. AI is going to end this shraddha folks. We will move to an outcome economy. The longer they take, the more money they make is the shraddha that will break because AI doesn't bill hours. AI gives you outcomes. If AI can draft your legal document in 30 seconds, your lawyer will not be able to bill you by the hour. And we'll move to this world of microtransactions. And this is where the next generation of SaaS businesses are being built. The India flywheel and Satya spoke about this. India has got the largest infrastructure buildout happening. Tracks before trains. We're laying the AI infrastructure in the country and we're diffusing AI across classrooms to boardrooms. 92% of knowledge workers in India are using AI. 60% of our schools are using AI. But from farms to finance, from classrooms to boardrooms, India is diffusing AI. And that's where I think this flywheel of building infrastructure and diffusing AI is starting to spin. And that's why we're so optimistic on where this is headed. The last thing, and this is the question I get the most, what's going to happen to jobs? I'm sure you're all thinking about this. Will AI steal jobs? I don't think AI will steal jobs. It will dissect jobs. It will unbundle jobs. Your job is a bundle of tasks. My job is a bundle of tasks. AI will unbundle it. And when AI unbundles your role and my role, we'll have to bundle ourselves much better. But we're still living with this industrial age era template of learn once and live forever and make money. My grandfather did it. My father did it. I'm almost doing it. That industrial age era template is breaking. Folks, you and I are the last generation to have stable long-term careers. My kids for sure will have a portfolio of things that they'll do. And the next generation for all of you will do the same. The real pink slip in this new AI era is not automation. That's what we all worried about. The real pink slip is refusal to learn. And if you're refusing to learn today on AI, and that's why I said this is the only oxygen mask for all of us folks. And I come from Delhi. I know the value of oxygen masks. But on a serious note folks, this is guerrilla warfare against irrelevance every day. Learning AI is guerrilla warfare. So if you're not learning, if there's one thing I can leave you today, start learning. And that's why Satya spoke about our commitment to train 20 million people in India on AI by 2030. You better make sure you're scaling up and you're learning AI. So those are my five predictions. A little bit about being frontier. And Satya spoke about frontier models. I'm going to talk to you about Frontier Company. These are frontier businesses. What are your frontier businesses? They're like frontier models. Always improving, always getting better, human-led, agent operated, buying intelligence on tap like I spoke and then compounding it. They put AI at the center of everything. And based on the thousands of companies that we have the privilege of working with who are building AI at scale in India and globally, we have some pattern recognition on where AI is being built. And these are the four areas where we're seeing the most impact folks. First, really thinking about employee experiences end to end. Hire the best talent. Give them the right skill sets. Give them the right tool sets. Measure their performance. Second, customer experience. Truly reinventing it. The N equals one for customers is now possible. And these people are ruthlessly focusing on customer engagement. I'll give you some stories in this. Reshaping business processes. You can't take your old process and put AI on it and expect magic. You have to replumb it left to right. And then finally, truly bending the curve on innovation. Let me give you some examples. Apollo Hospitals building a clinician co-pilot to make sure young doctors, young clinicians have as much expertise and judgment like experienced doctors. Air India reinventing the entire customer experience journey. AI.g their bot will do your tickets and your bookings and your check-in and upgrades. ICICI Lombard moving from a digital first to an AI-first company. Asian Paints transforming how you think about color, design, home experiences. I could go on folks but there are many businesses in India and we're publishing a book called Frontier Firms with 60 hero stories and I'd love for you guys to read the digital copy so we'll make sure you get one. And across all of these cases, all of these stories, one thing is common which is they're putting human ambition at the center of everything they do. They're truly democratizing intelligence, going back to my point around we're manufacturing intelligence now for the first time, but they're putting that at the center of it. And we as Microsoft are bringing our solutions across the board to make it happen. So let me bring this to a close, folks. And I'll leave you with three ideas, three actions as you go back to work after this today or tomorrow. The intelligence revolution is in motion, folks. It's in full motion now. It's in full flight. It'll impact every business, every function, every role, yours and mine. Think about how you're going to rewire your business. Think about digital colleagues. Think about becoming an agent boss. Think about getting AI to work for you. And these frontier firms are like time machines. They're telling you the future. And if they're doing this, this is where we're headed. Microsoft is truly becoming the home for India to build AI. And we are so privileged and humble about this. And this is something that we get back to work for every day. From private companies to businesses to government to education across the board, we're building AI. Partner with us. We'd love to find a way. And then finally, the last thing folks, AI skilling is the new literacy for all of us. This is the only oxygen mask. Learn with AI, build with AI, get AI to work for you. And by the way, learning AI is not like doing a PhD. It's about taking the sphere out. It's about working at it every day. It's like you can't get fit by watching others go to the gym. You can't learn AI by watching others play around with this. You have to go to the gym yourself every day. Believe me, I've tried sitting outside the gym doesn't help. It's full contact sport, guys. It's guerrilla warfare every day against irrelevance. So please get on this and learn every day. So I'll end where I started, folks. We're living through a moment of reset. The world is rearranging itself. It's rebooting itself. It looks unfamiliar. A new map is being formed across the world, folks. And this map doesn't care about where goods are produced or where value is produced. It only cares about where intelligence is produced and where intelligence is diffused through AI. And in this rearrangement of this world lies the biggest opportunity for all of us. For all of you, for me, for each one of you, for India, our digital destiny is being rewritten. Our destinies are being rewritten. And this is where the real opportunity for us is. Folks, the future is already here. There's never been a better time to build with AI. You've got a PhD level researcher, PhD level consultant, a PhD level lawyer, doctor sitting in your pocket. And once AI moves from a tool on your phone to being a teammate to a digital colleague, that's where the unlock will happen. Okay? So there's never been a better time to build. Don't wait. Get started now. You are the frontier. You are the future. Let's build. Thank you.