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Microsoft CEO Satya Nadella on AI's Business Revolution: What Happens to SaaS, OpenAI, and Microsoft? | LIVE from Davos

January 21, 20260 comments♥ 0
00:00All right, everybody, we're thrilled to have the one the only.Satya and Nadella here, the third CEO of Microsoft for an impromptu fireside chat with David Sacks,our czar of AI and crypto.Satya, third CEO of Microsoft, born in India.What an incredible story.Came here right after college.And you had a little round trip to pick up your wife.in your book to bring her here. Tell everybody briefly how that occurred. Well, you know, so that's a
00:38great story of the lebrant that is the immigration policies of the United States, I think.My wife and I went to college together in India. I came here for grad school, we then gotmarried. I got my green card, and she couldn't come join because.because we got married.So the story goes, basically,I had to give up my green card.So the funny thing is I went to the American embassy in Delhi,and I said, where's the line to give up my green card?
01:11And they said, there is no such a line.That would be a crazy thing to do in the 90s.So it was a strange thing to give up your green card,get an H-1 so that she could join.But it all worked out.So, you know, it's a long-lost memory,but it was a way to work around it.I wanted to ask you having launched a co-pilot first with GitHub, then having a co-pilot on the desktop.
01:39You made a very bold move for Microsoft to put that in the Windows product, which I use every day, on the desktop.But you did that before.It really could recognize the file system and interact with applications.Got a little bit of a lukewarm reception, but now you've been doubling down, doubling down.And there seems to be, in my estimation, three modalities for the knowledge workers.Elon's building at XAI, what they're calling a human emulator, if you saw that leak this week, yeah?Where they're just building employees and just putting them into their chat rooms and email.Then you have, Claude came out with co-work this week.
02:16Incredibly powerful.People are kind of losing their minds over it.I've been playing with it for the last 40 hours.Truly impressive.what's your vision for Microsoft and how knowledge workers will actually put this to usebecause there seems to be a gap between, you know, playing around with chat TPT and gettingsome interesting results and getting business results.Yeah, so I think one of the most perhaps illustrative examples of trying to understand
02:44these various form factors is looking at coding, which is obviously a form of knowledge workor probably the best example of knowledge work.And if you think about the journey coding as being,it started with essentially the next edit suggests.That was the first time, in fact, my own beliefin this entire generation of tech really sort of got formulated.But I started seeing, I think there's a codex model backin the day, it was pre-GPT-35.
03:14That's when next edit suggestions started workingwith some real accuracy.Then we went to chat.Then we went to action.and now to full autonomous agents.And then the autonomous agents can be both foreground, background,in the cloud or local.So that's all the form factors that exist today
03:34when you're coding.And interestingly, if you look at it,you use all of them.It's not like there's only one form factor.So that's, I think, probably one of the other lessons.So for example, when I'm in a CLI,I can go a foreground agent, background agent,and then just literally go edit in VS code right there,
03:52all happening in parallel, right?So that sort of shows how these form factors even composed.So then you bring that to knowledge work, to your point.We started with chat.Chat with reasoning sort of goes beyond just request response,because you now have that chain of thought where you can see it work.Now there are actions, right, essentially either through computer use or through, you know,basically skills, an agent
04:22calls so you can do action. So that's kind of the state of the co-pilot today. Now there is a way tothink about, you know, the theory of the mind evolution, right? Because you need, like if you remember,jobs had the best line, I would say, for PCs or computers was to say if you, it's a bicyclefor the mind. Bill had a line which I liked as well, which was its information at your fingertips.we kind of need now a new concept metaphorfor how we use computers in the AI age.You have one?And the one I like actually came from the CEO of Notion,
04:57which I know that manager of...Incredible product.You haven't bought it yet.I've not bought that.But it's both management, you know, basically a manager of infinite minds.That's a nice way to think about it.When you sort of really look at all the agentsthat you are working with,
05:16You kind of need to understand what I, in fact, the other term I like is we macrodelegate and microsteer.In fact, you kind of need that.In coding, you kind of have it, right?So you do a macro delegation, and then I can in parallel give it instructions while it is doing work.So that's sort of the state even today of co-pilot or what have you.You bring up a little bit of one of the form factors I'm very excited about,and you'll see us even in the next week even, do things,is while I'm sitting in GitHub copilot,
05:50it's not as if software developers sit in isolation, right?It's not like the only thing I work on is my repo.I attend meetings.I write specs or others have written specs that I'm implementing.I need to have my repo be consistent with that.So that means using either a straightforward MCP server or a skill,I want to be able to call into my work IQ,which is the co-pilot,
06:14bring that in.That's the type of composition of knowledge work that will happen.Same thing with security.Say you're a security professional, you have lots of logs,how do you sort of really analyze them,you drop them into a file system,then write code on top of it,create a dashboard, what have you.
06:33Those are the types of knowledge work that we can enable.Then I think you bring up one more thing,which is can you create quote-unquote digital employees,digital co-workers, or what have you?And it's all about credentials, right?So today you could, like you can literally-Are you working on that as well?Yeah.
06:48So in fact, we introduced something called Agent 365 as a way to give identities.In fact, extending the identities we have for humans todayand the endpoint protection we have for their compute devices to agents.So you might clone me working in the HR departmentor working in the marketing department and have a virtual version of me inside of office.That's correct.So there are two sort of modalities there.One is you give every knowledge worker,
07:14Infinite minds.That's kind of one.And then you create even infinite minds independent of your identity.Because identity is one of the key things you've got to get right.Even for it to work, right?For permissions and decision making?Permissions, decision making.One of the key things is who did what to whom is sort of the most important query in an organization.
07:37At the end of the day, the organization needs to understand what work got doneand what's the provenance of that work,and how do you trace it back, right?So therefore, you kind of want either,if it's a human with a lot of agents,then it's really macro-delegation,microstering by the humanwhose identity was passed on.
07:58So it's delegation versus a separate identity.And that was done by a level of management,product management, that you've eliminated,that alphabets eliminated,meta has started to eliminate in their organizationfour years ago.You had the same number of employees you have at Microsoft now, but you put a $90 billiononto the top line of the revenue in that time, and you doubled your income during that time.
08:23So how did that happen?Is that automation of those jobs?Is that you were a little bit overstaffed?I think it's actually, you're pulling on a very interesting thread, which is at some level,what's the big structural change that needs to happen?In fact, I would say this is probably the biggest change.change in knowledge work since PCs. I mean, I always, you know, think about, like, how did workhappen pre-PCs, right? I mean, think about a multinational company like ours trying to do a forecast,
08:53right? Faxes went around, inter-office memos got sent, and then you kind of created a, you know,a forecast. Then suddenly, you know, PCs became standard issue. You put an Excel spreadsheet,put some numbers sent it in email, everybody entered numbers, and you had a forecast. So the work,the work artifact and the workflow all changed.That's what's happening.So, for example, I'll give you at LinkedIn,we used to have product managers,we had designers, we had front-end engineers,
09:24and then we had back-end engineers and so on.So what we did is we sort of took those first four rolesand combined them.In fact, increased scope and said,they're all full-stack builders.So I like that because that's a structural changethat allows for us to increase the change,both the work and the workflow,
09:44between these functions.And I would assume the velocitybecause you don't have four people communicatingand that throughput of ideas,which is one person in vibe coding.Exactly.And there's a new workflow.At the same time, as you can imagine,
09:56if to build an AI product today,there's a complete new workflow, right?It starts with e-val.So basically there's this e-valto science, to infrastructure.And so e-vales are,are done by these full stack builders and what have you,and product managers in the new form.
10:13The infrastructure is built by the systems engineersat the back end because they support the sciencethat supports the product.So in some sense, there's a new loop.And you have to structurally change.And so a lot of what is happening inside a techis that change, which is, I think, going to be pretty massive.And at the same time, a company like ours,
10:33I have to do everything.It's not like I can just go live in the future.I have to make sure we're doing a fine.fantastic job of doing hot patching on Windows is done with quality, while at the same timebuilding the e-vals that are improving co-pilot quality, right? And so both of those have to be firstclass. I assume this is the most challenging moment of your career because Microsoft was so dominant,duopoly in some spaces, but you really weren't up against the competition level. You're upagainst now. I was talking to Elon, you know, and he was sort of saying, well, building cars was
11:07pretty easy because I was up against the legacy carmakers. And now I'm up against, just look at theset you're up against. Yeah, it's a pretty intense time. I mean, so the way I always think isit's always helpful when you have a complete new set of competitors every decade, because thatkeeps you fit. If I think about it, I joined Microsoft in 92 when I had Novell. I had Novellthe big existential competitor we had.And here we are in 2026.And you're absolutely right.It's a pretty intense time.
11:41I'm glad there's the competition.It's quite honestly, at the end of the day, when I look at it, right,as a percentage of GDP, five years from now, where will tech be?Right.It will be higher.So we are blessed to be in this industry.It's a lot of intense competition.But it's not so zero-sum as some people make it out.
12:01ties getting much bigger.The TAM and just the impact of this tech is going to be so massive.The question then, of course, is what is, like I always go back to what's the brand identityMicrosoft has, brand permission we have, what do customers expect from us?Sometimes we kind of overthink somehow that every customer wants the same thing from all of thecompetitors.And finding that out, right, it's kind of a different take on the Peter Thiel thing,which is you've got to avoid competition by really, really.
12:31understanding what customers really want from you versus thinking everybody's a competitor.David?Yeah, so there are a lot of heads of state here, obviously at Davos, as well as CEOs of Fortune500 companies.And I think you got asked a question last night at the dinner about how they should think aboutAI and how to be successful.And I recall they used the word diffusion.And I was wondering if you could expand on those remarks because that really resonated with
12:59some of the policy work I've been doing.No, absolutely. In fact, what you all have been doing to make sure in this context of the American tech stack is broadly used around the world and is trusted around the world.Because I think when I look back, David, to me, at the end of the day, you create the technology, but really the benefits come only by intense use.In fact, one of my favorite studies has always been this work that an economist, I thinkour Adatma did, his name is Diego Komen, where he studied basically what happened duringthe Industrial Revolution.How did countries get ahead?And the simple sort of takeaway from that was any country that brought the latest technology
13:51into their country and then did value-add technology on top of it, right?So it's like, don't reinvent the wheel.bring the latest and then build on top of it.That's to me what happens, you know, when you have diffusion.So especially with general purpose technology like AI,it needs to spread, like right in our own country in the United States.We now need, we have the tech.The question is, is it being used in healthcare?
14:16Is it being used in financial services?Is it being used in every sector of the economy by large businesses,small business, public sector?So to me, unless and until we see that diffused,and intense use, we're not going to have the success.And so that's the phase we are in.It's diffusing faster.And so some of the policy work you have done,
14:40and in general, the good news here is the technology is there.The rails around cloud and mobile that were laid outmake it possible for this thing to spread.It's not impossible to get the tokens.The question is, what are the use cases,and how do you manage the change in all?the change in all of that.You know, like one of the questions at least in Davos
15:02is it's one thing for the West and the developed nations.What about the Global South?I think Global South has a huge opportunity to, quite frankly,because to me, like let's say, you know,40%, 50% of the GDP of most Global South countriesis public sector.So just imagine this tech making a differencein how the governments really parlay
15:24the taxpayer money into services for citizens.And if there's efficiency gains, that's probably a couple of points with GDP growth right there.And so I'm very optimistic that there's going to be a poll and that we should as the United States,given the technology stack we have, in Europe, in Asia, in South America, in Africa,and everywhere else get it to be broadly deployed.One of the questions I get asked a lot about the AI race is how do you know if you're winningor how do you know if the United States is ahead of its global competitors?And the answer I give is market share.
16:02You know, if we look around the world in five yearsand we see that American companies, American technology has, say, 80% market share,it means we did a good job.If we look around the world in five years and see that it's, say, Chinese chipsand Chinese models that are being used all over the world,well, it means we probably lost.So, you know, ultimately usage is the proof of the puddingis in the eating of it.
16:25I mean, in this case, the way that you know that you're succeeding is through market shares, through usage.And I would agree with that.But, David, since you even worked at Microsoft for a few years, one of the things that I'm very grounded on is always that Bill Gates line of a platform, right?So one of the things that I always think about is it's market share, but it's also ecosystem effects, right?See, what the United States always has done is not just about our market share.or even the revenues to U.S. companies.In fact, one of the things I learned at Microsoftis whenever I did a country visit,
17:03the data I would first study is, let's say,in the UK or in Switzerland or what have you,what is the total employment created in Switzerlandin our channel?That used to be like the number one thing in our country reports, right?And the total number of...Would that be like the number of IT workers,the number of office workers?
17:24So channel partners, we're ISVs, so the number of ISVs who were there.So we used to have a complete marker of how did the ecosystem around the platform get built one country at a time.And that is what the United States has always done.In fact, the U.S. tech stack, including in China, got built because others built around our tech stack.The same thing is going to happen.So that's why I think the work you're doing around diffusion is about really, really,increasing the size of the pie, the trust in the platform,so that there is true economic opportunity, quite frankly.
18:02Well, you're right, and I remember, actually,you brought back some memories from this is about a decade agowhen my company Yamra was acquired by Microsoft.We were part of the SharePoint Group,and I remember that the product managers there were very proud of the factthat the revenue from the SharePoint ecosystem,meaning non-Microsoft, the consulting community, the implementers who would go into companiesto implement SharePoint, I think their revenue is something like seven times greater than Microsoft's
18:32own software revenue.In aggregate.In aggregate.And I think Bill had a line about you're not an ecosystem or a platform until the revenueon top of your platform is some factor of your own revenue.And I think what's really important about this is when we talk about this, is when we talkabout diffusion and obviously we want the United States to have this leading position,it doesn't mean as bad for the rest of the world because they're able to build on top of those
19:00platforms and create even more value.100%.In fact, that's sort of the most important point, right?So this is not about American tech and revenues to the United States.It's actually creating opportunity using a new platform everywhere.And in fact, you know, like I remember I worked on our database products.in the 90s, you know, with SAP.In fact, the combination of SQL server and R3 were successful on both sides.
19:29There's a lot talked about Intel and Microsoft,but one of the other things that I grew up in,which has sort of been foundational in how I look at the world,is what we did with an European software companythat is still, you know, a giant.And so, you know, who knows what the next big AI app will beand what will happen.But I sort of go in with the attitude
19:50that there will be tech companies,maybe even top five tech companiesthat could emerge everywherewith even the American tech stack.You have done some amazing acquisitionsthat you're quite a dealmakeron top of being a technologist.It's probably the least reported aspect
20:07of your spectacular tenureand the massive growth you've had.But you did a deal with OpenAIand probably one of the most savvyslash controversial dealmakers of all timesSam Altman. That deal was looked at as you're set up to get a windfall in cash which you don'tneed as Microsoft. Always nice, I'm guessing if they IPO. But did you create potentially, and thiswas the criticism of it, an ultimate competitor to Microsoft? And how do you think about that?
20:41And how can Microsoft, which missed Steve Bomber's biggest regret, missing the mobile revolution,How can you not have a Gemini, an XAI, a Claude that is your own?Or in your mind, do you have that because you have the source code of open AI?Yeah, I think that's right.So when people say, where is your foundation model?I mean, at the end of the day, we do have the IP.But that said, I think you bring up a couple of different things, right?One is, to ask the most important thing, when I look at what is Microsoft's strategy today,
21:13one is we want to build token factories, right?So our biggest business today is Azure business, and the Azure business, the TAM, given what's going to happen, is so huge that we now need to be fantastic at building these token factories.And that means a heterogeneous fleet of infrastructure and that every hyperscaler is always done, which is use software to make maximum use of it and for TCO and utilization.So that's one side of it.Then there's the app server business, right, which is everybody, you talked about like if everyone's going to be building agents, have infinite minds.have these RL gyms, have evals, what have you.There's an entire, just like every platform has had an app server.This one has an app server.
21:54That's what we're doing with foundry and what have you, right?So there's an app server business.In that app server, one of the things that structurally now is pretty clearis anyone building any application or any companyis going to use not one model, but all the models.Why would I not?Right, which is, in fact, I will orchestrate for any given task,even multiple models, right?
22:16There's this one nice thing that we came out in our healthcare practice called the decision orchestrator.What it proves is that by assigning roles, right, so investigator, data analysts, domain expert,just giving even prompted roles to models, and then orchestrating them, gets better results than any one single frontier model.Am I right to read into that then that you're bullish on the open source models and think large language models will largely be commoditized?and that's not where the value will accrue?In fact, the way I think about it is that...Tim Cook and Apple thinks that, too, by the way...By the way, the way...
22:53You think about what happened in the database market, right?You know, I used to be like,everything is just a SQL database until it was not, right?There was...Think about it there.Doc databases, there is no SQL databases,the proliferation of databases, right?Who would have thought that the database market
23:09would have such a richness to it?Or that it could ever be open-source?That was mind-blowing.I mean, talk about Postgres.or what has happened even with Mongo, which is open,but there are even companies that have backed it.So to me, that's what's going to happen.To me, a model is like the database market.
23:25It's going to differences,but I sort of somehow think that there are definitely going to be frontier modelsthat are close source.You know, they're going to be open-source modelsthat are going to be frontier class.In fact, if anything, I think in this next year,what will be probably a big part of the discussion is,What's the future of a firm?
23:47A firm should be able to take the tacit knowledge it hasand embed it inside a weights in a model that they control.So when somebody asks me how many models should be there,I'll say as many models as firms in the world.That's sort of an extreme way.Because to me, that's how I think this knowledge economybecomes an AI economy.Are you secret?
24:14and you can say it here since we're on all-in,working on an LLM to exist on the Windows desktopbecause that you are.You have it.Like today there's a Phi-Silica modelwhich is completely residentusing NPUs and of course using GPUs.In fact, the largest installation of high power.
24:34In fact, it's one of the fascinating.The workstation is back.I'm one of the most, if you went to CES.Which is great for Microsoft because you have a nice desktop business.Absolutely.And so we, in fact, we think that that form factor, especially, I mean, I always say this, which is, you know, I started my career on a command line.Who knows, I may just end it in a command line.But you started that Sun, which was the original $5, $10,000 workstation.
24:59Do you see a time where you'll be meeting with your customers here and advocating a $10,000 desktop machine that has an LLM and the hardware?I mean, you can, you can put a DGX card and you can have, like, just a fantastic machine.And by the way, we are one architecture tweak away from even having some kind of a distributedmodel architecture, right, even an MOE architecture that knows how to really distribute itself,right? That's the type of breakthrough that can completely change what hybrid AI may look like.But we're absolutely committed and focused on making the PC a great place for local modelsand local models that then do even a lot of the prompt processing and call into the cloud, right?So there's a whole lot of work that can happen, and that's sort of definitely something that's in the way.
25:48Yeah, I think that the clog co-work has kind of shown the power of tapping into the local file drive and be able to use that.That brings up another point.You got me thinking about Yammer, and for people who don't know, you know, Yammer's claim to fame this is about 15 years ago,was that it pioneered a lot of, well, it used a lot of consumer growth tactics to attack enterprise software.I'm wondering, as you think about enterprise adoption of AI,how do you think it's going to spread over the next year?It feels like we're at sort of a critical point.Do you think it's going to be top-down?
26:20Is it going to come from the CEO directing a team,giving them a strategic transformation project,and they're going to do an RFP,or do you think it's going to spread bottom-up in the enterprisethrough AI-native employees who are adaptable,who are using the tools in their own lives,and they start to bring these things to workand sort of accomplishing amazing things.
26:41Yeah, no, I think, like all things, David,I think it's both the top-down, bottom-up, right?The reason I say that top-down is,if I look at the ROI of applying AI in customer serviceor in supply chain or in HR self-service,those are the easy projects where IT and CXOs can make calls,and that's where you're seeing the first drop of,real AI adoption. But the bottom up is what ultimately will happen, right? I mean, even with the
27:13PCs, in fact, if you think back at it, the lawyers brought word in, and then finance boughtExcel in, and then email came, and then it became standard issue. That's what's happeningright now. So, for example, these agents, when I sort of talk about everybody's building agents,they're figuring out a way to go create these things that are changing workflow and removingdrudgery in their work, right? That's sort of the beginning of what is a bottom-up transformation.In fact, the thing that I'm most excited about is this bottom-up change. Even at Microsoft,for example, we manage something like 500-odd fiber operators around the world in Azure today.And by the way, I had not myself realized it. A lot of it, you know, it's called DevOps, but it's a physical
28:00asset. Things get cut. And when you sort of say DevOps, that means you literally are emailingpeople and saying, hey, what happened to that fiber cut?How do we repair it? So there's a lot ofback and forth. So thisnetwork, the person who runs ourglobal network basically has builtto your point about these persons. They're justdigital employees, essentially,
28:20that are doing all of thatDevOps. And sothat's, and those are completely bottomsup where you see the tools.It's kind of like, hey, I have the new wayto build agents. It's there. I'm goingto use it to create levels ofautomation that remove
28:36drudgery, improve efficiency, improve quality.And that ultimately is a skilling thing, which is sort of the big issue, which is, and skillingis not mystical.It's just by doing, right?So it's not like I go to a class per se.It's like the diffusion of the tools and using the tools.And that, I think, is what really going to be happening.And we're in a very interesting moment.
28:58Empowering an existing employee with these tools is so much easier than hiring and mentoring andbringing up the next generation. So it feels like we're in a little bit of an indigestion moment.At Microsoft, do you think, who's going to have my job in 30 or 40 years if the companystays the same size? Because given your technology-first approach, there's really no reasonto ever add another Microsoft employee at the pace this is going. And you haven't for four years.So how, you may have swapped some in and out and changed the texture of it. So how do you thinkabout maybe this next generation, what advice would you have for these college graduates whomaybe don't have an offer for Microsoft right now? And you used to spend a lot of time on that,
29:44building that group. But maybe you don't have that luxury now? Do you think about it ever?It's a great question. There's a little bit of a debate what happens to early in Koreaand how is college recruiting. I still am a big believer in college recruiting because at the endof the day, this is going to change the curve by which anyone can pick up proficiency in a codebase. It takes sort of just regular CS hiring. What has changed is perhaps for someone who comesin new into a team and to be able to ramp up thanks to all of the markdowns, the skills,the fact that I can go ask the agent.I mean, think about it, right?
30:29It's like having an unbelievable mentorwho is getting you onboarded onto a code-based faster.So in some sense, the productivity curveof a college hire is going to be much steeperthan it ever before.So I think there might be a difference.In fact, one of the things we're experimenting withis a different type of apprenticeship, right,
30:48which is you take somebody who's an IC senior dev,have like a cohort of college hiresworking with them.Because it's a new way of working.It's like I remember everybody who joined Microsoftwould say go, how did, you know, whatever,Cutler implement Malik or what have you.He would go try to read his code
31:10to understand what great craftsmanship looks like.Nowadays, I think that great craftsmanshipcomes by looking at even how the 10x, 100x engineersuse AI.to build great quality products.And that is what these new college gads will learn and learn faster.And so that's a beneficial thing for a company like us.Because at the end of the day, until we saw longevity or something,
31:36we need people to come into the workforce, be successful at Microsoft.So we are very committed.But we are also making sure that the scopes of the jobs make sensefor what the aspirations of people are going to be,both who are currently in the workforce and people who are entering the workforce.Okay, on that note, Sata Indella.Thank you so much.