Source: Microsoft
Headline: Podcast: Microsoft EVP Rajesh Jha on leading with courage in the AI era
MOLLY WOOD: That was Rajesh Jha, Microsoft’s Executive Vice President for Experiences and Devices. As a key figure at the helm of Microsoft’s product innovation, he leads a team of tens of thousands of people around the world who have worked to integrate AI into Windows and tools like Microsoft 365, Teams, and more. He’s also a key member of the company’s senior leadership team, which works directly for Microsoft Chairman and CEO Satya Nadella. In this episode, Jha shares his perspective on navigating the complexities of how AI is changing the way we work, and he offers actionable advice on how leaders have to adapt, compete, and bring their people along with them. And now my conversation with Rajesh. Rajesh, thank you so much for being on WorkLab today.
RAJESH JHA: Thank you, Molly, for hosting me. It’s a real pleasure to be here with you.
MOLLY WOOD: You have more than 30,000 employees, and you run a $100 billion business, which is more than most CEOs do. What are just some of the many lessons I’m sure you have learned from running such a huge organization?
RAJESH JHA: It’s been a real privilege to be at Microsoft through so many of the growth years. When I reflect back on my career, there are a few things that are enduring. The mission matters because through the ups and downs, if you have a sense of purpose, you have a North Star, that really does matter. And Microsoft has been really great to always be grounded in our customer successes, our success—this theme of empowerment, from Bill into Steve into Satya. So that was definitely number one. The second thing that I would say is, it seems very trite, but it has really worked for me specifically and my team, is, whenever we are looking at a hard strategic call, we start from, how would the customer react to the decision that we’re making, that has been incredibly grounding, so that’s been enduring. Of course, the team matters, the culture matters, because that’s where the work gets done. And then finally, managing a large business is about, literally, about figuring out how to make elephants dance, because you have a large-scale business, customers expect us to have a certain level of quality and continuity and predictability. At the same time, they take a bet on us to innovate. And so how do you stay nimble and innovate while also being predictable and trustworthy for customers? That is a hard thing to go do, but absolutely essential. It’s an and, it just can’t be an or.
MOLLY WOOD: Well, and Microsoft is an elephant that has danced, quite nimbly, for the last 50 years—
RAJESH JHA: Sometime clumsily, sometimes nimbly, yes. [laughter]
MOLLY WOOD: We’ll focus on the nimble—or not, right, based on your experience in bringing new technologies to market and helping to effectuate some pretty major technological innovations. What insights do you have for leaders who are now navigating this AI transformation?
RAJESH JHA: I mean, now is the time for leaders to really consider how their businesses, how their teams, how their skill set—how does that evolve in a world where we are looking at, you know, something at the peer of electricity coming into society, or the internet coming into society. And so it’s time to lean forward, and lean forward in a way that makes sense for their businesses or their business process. It is such a big change that it’s going to probably take a decade to play out, but there is no avoiding the sea change that’s underway now. So some bravery, but bravery on customers’ terms.
MOLLY WOOD: Yeah. I’m thinking of leaders who may be wary, who may need a dose of that courage. You’ve spoken about being asked by Steve Ballmer to bring Office to cloud, as one example of a transformation that maybe you were a little wary about. Can you walk us through that experience and how it might give a shot of courage for folks today.
RAJESH JHA: This was, you know, back maybe 15 years ago, Microsoft was incredibly profitable and the cloud was a question mark for many at Microsoft. A) would this technology be mature enough? B) is the business model, because the margins were going to be lower on the cloud than our old business model of being on premises. Number three, would we be able to transform fast enough? Because Microsoft had grown up being a server company, a client company, and would we be able to transcend that to be about cloud and mobile. And they were all very important questions. And there was a lot of, you know, let’s hold back. Let’s see if this trend is really real or not. And Steve showed incredible courage by going all in. What Steve did was he gave license to people to go and learn, even if we were not perfect on day one. And so the big lesson for me in how Steve started that journey was, leaders, if you have hesitation, whether it’s a business model hesitation or cultural hesitation, skill hesitation, it’s very hard for the teams to rally behind something where the leader themselves are half-hearted. So that was a very big moment for us, because he was unambiguous about, hey, this is the way that software is going to be delivered in the future. This is the way we can democratize the value we bring to customers. And there were a lot of benefits, and we are just going to go all in.
MOLLY WOOD: So leaders have to go all in. But I would imagine it’s not a—progress is not always a straight line.
RAJESH JHA: No, it wasn’t. And even with us in the cloud, it wasn’t. But the main thing is, leaders have to lead. And when you’re taking a look, the hard things are process, business model change, culture change, skill change. They’re all incredibly hard, and that’s why there has to be a commitment from the top that we are going to see this through. And then we were eyes wide open as what our deficiencies were. And so we didn’t have the right skill set. We trained people, we brought in new people, we embraced the red—all the things that we were not doing well in this new transformation. We were very open, very honest. It just takes leadership to set the tone here and to set the things in motion.
MOLLY WOOD: Right, and to your point, persistence and belief that it is the right direction so that you stay on that road even when it gets hard.
RAJESH JHA: That is correct, Molly, absolutely. And then one additional point I would make with persistence and belief is, it’s one thing to say it, it’s another thing to allocate resources to that belief. We have a quote, which is, if you really want to see the strategy of an organization, you’ve got to see where they’re allocating resources.
MOLLY WOOD: On the one hand, it sounds like you’re saying, get comfortable with chaos—
RAJESH JHA: Controlled chaos, Molly. Controlled chaos.
MOLLY WOOD: Then of course there’s the question of how not to break things. You know, security becomes a big concern with incorporating AI, doing it in a way that doesn’t introduce more problems. What is your advice for having proper guardrails in place as you transform in the AI age?
RAJESH JHA: So, I’m gonna answer that in two parts. Part one is, what do I mean by controlled chaos? So Satya invited Scott Guthrie, myself, Charlie [Bell] as the three big product leaders at Microsoft to go over to Bill’s house to see GPT-4, and Satya’s exact comment to me at that time was, I’ve gotta get you guys to be believers. And he had already seen it. And so he and Kevin Scott, they were already on board about the capabilities. So anyway, we go over to Bill’s house, it was in the kitchen area, where the OpenAI folks had put in a demo and they had a grader who grades AP biology there. The thing that really got me was it was not just the multiple choice questions that the model was doing a great job of, it was doing a great job on the written answers. There was some of the AP biology stuff, I’ve studied some biology, but they were far above my ability to understand. And so I look at all of that, I’m completely blown away. But then, for me, the big moment was when Bill asked the question, what would you say to the parent of a sick child, and the empathy or the humanity, almost, that it was able to convey in the answer was like, I would’ve felt proud to have written such a thoughtful note. And I was like, god, this is really, I mean, we are leaving behind the low-altitude handshake between computing and humanity. We are taking a look at something that can be almost at the pure level. And so now, fast-forward, it’s not that long, two years, and we are at the point where we are talking about agents and digital labor and people working together.
MOLLY WOOD: But that was it, that worked. You became believers.
RAJESH JHA: For me, that was it. I lead a large organization, and I see lots of cool stuff all the time, and part of my job is to make sure the trains keep running on time, but make sure I’m open-minded about big things. And when big things show up, I try to scope it and manage it. I have never in my 30 years ever gone to my team and said, drop all your plans. And for me, that was it. None of the existing plans matter anymore. I huddled all my senior leaders, and I said, Folks, I want you all to run a hundred miles an hour. It’s going to be very uncomfortable, because we’re going to unleash some amount of chaos, but let’s make sure we harden our processes that this chaos does not make its way to customers. So what I mean by controlled chaos is, if you’re unleashing a lot of activity all at once, you need to have the mitigating controls and the guardrails to make sure the chaos is controlled and managed. And so we huddled together to make sure our processes were hardened. So that’s one of the things with controlled chaos. But one of the guardrails that is not negotiable is security, as you correctly pointed out. So in our implementation of AI, we started very much from the mindset of, how does the AI inherit all the existing security and governance controls that an organization already has? It’s one thing to come and tell them, hey, rethink all your business process, rethink your scaling, rethink how work is done, and rethink your security and governance. It’s just not doable. And so we architected this from the ground up, that, for example, when you use Microsoft Copilot, it is using your permissions, so it only has access to what you have access to. It can never do any more than what you might do as a human. And then we also made sure that it was the mindset of a copilot, not an autopilot, and so the humans were always in control. So this way, whatever governance, data classification, permissions, you know, conditional access, retention policies—whatever a customer had, and how they managed human-to-human conversations, all of that accreted to human-to-AI conversation. That was a very hard guardrail we knew we just could not compromise.
MOLLY WOOD: But I want to go back to the example that you just gave, this moment of having this experience and realizing how—
RAJESH JHA: Profound.
MOLLY WOOD: Profound—exactly—and sophisticated these models were, because those are the kind of moments that give you the faith to go all in.
Rajesh Jha: Just to go back to that moment, Molly, I mean, to think as an engineer, as somebody who’s been in the tech industry a long time, who’s been through so many of the transformations, the big takeaway for me was, you know, for the first time computing, so far, human and machine interaction has been very much—machines are very low level. You know, we interact with pixels, we click on things, we read stuff. When I come in to work, I don’t come in to work thinking, oh, I should do 16 minutes of email and then read four documents and then, you know, open that spreadsheet, take a look at that budget. I come in thinking, I’ve got to work on budget today. So I think at a high level of intent, but then my intent to decompose is, either on my device, on a bunch of icons I’m swiping through, flipping from application to application, or going really low level—reading emails and then clicking a link. And so high-level intent gets reduced to low-level clerical work, almost. So when I saw this demo, I was like, Wow, the interaction is going to change. It is not going to be intent and then reduced to low-level stuff. AI is going to have the capability to have a human-to-human-like conversation. So intent, high-level intent to high-level intent, and that was what was the big takeaway for me. This is the computing for the last 35 years. One thing that hadn’t changed was a fundamental interaction pattern between people and their devices, and that was going to change, because now you could express, hey, I want to write a document that has the following three ideas, take a look at the relevant stuff in my enterprise and on the web—and can you compose a report for me? That is the kind of thing that I would tell another human being if there was a new hire in my team and, you know, I was thinking about a project to give them. This is the kind of way I might express the project to them, and then they will go in and do the work, check in with me, and we go back and forth. Now that was going to be possible.
MOLLY WOOD: Let’s keep talking about that idea of leveling up. We now live in a world where I may get an email from your account and I may not know if it was written by you or an AI, and that may not matter.
RAJESH JHA: You know, in some ways, it’s not that different from what happens for some of us. Let’s say I was to send a large piece of email to my team. I would actually work with my staff and my leadership team to get the latest status on a few things, and then I would put it in my words, and I would send it out. Now, everybody has that ability, because what the copilot does, you know, if I’m responding to a customer today, I go to my engineer who’s working on the customer issues, and say, hey, what is the latest status on this? And I would take a look at some of the other past conversations. I would try and respond to the customer that way. Now the copilot is doing that for me. It’s taking a look at my past emails. It reaches out to the customer service database. It tells me the latest status on this. It creates me a draft that I then go write and I send it out. And in some ways, I get reminded of, my dad used to run a large steel plant in India, and I visited him about 20 years ago. I walked into his office and he was very proud, because they had just gotten email, and I was working at Microsoft, and he had just gotten email. His secretary walked in at that time, and she said, Mr. Jha, I’ve got your morning messages for you, and here’s a message that I’m just going to go reach out to your technical assistant or respond to this person. This one, I know what to do already. This one, what would you like me to tell the customer, this person’s asking for dinner tomorrow. You’re free. And they were done in 15 minutes, and she left. And I looked at my dad, and I said, god, you’re so old-fashioned. Somebody’s actually printing your email, reading and coming and talking to you about it, whereas, look at me, I’m carrying it on my phone. I can get to it anywhere. But now, you know, I understand he was a smart guy, and I’m a digital clerk. I do all the clerical work myself. You know, I’m sorting messages. I’m replying to staff. I don’t come in to work thinking I should be a digital clerk. I come in to work because I want to lead a team, build products and value. That is what AI is now going to do. It’s going to take the clerical part for all of us, and will automate a lot of clerical parts to let the human ingenuity and the creativity and really let us focus on the intent and the meaning of our work.
MOLLY WOOD: We need help, Rajesh. We need help. [laughter] Well, speaking of delivering that help to customers, it’s been about a year, year and a half, since Microsoft 365 Copilot launched. Do you have stories from the trenches? Are there fun examples you can share about how this has gone?
RAJESH JHA: Really well. Ever since I came to Microsoft, this is the fastest adoption we’ve seen. When a customer buys a license and gives it to an end user, because the copilot is integrated into your user flows in Office, or Teams in a meeting, or so on and so forth, we see very good uptake in usage and retention. Some things that surprised me a little bit—and in hindsight, perhaps not so surprising—is the amount of customizations that customers do want for AI. I have feedback from some customers saying, hey, your AI, I want it to engage more because, you know, we build safety into our AI so it will not engage on some topics. Some customers want it to engage more, some want it to engage less. So they want to customize that. One of the things that some customers ask for is, hey, I would like your AI to not reach out to the web. I only want it to work with the stuff that’s in my enterprise. And I say, yeah, we’ve got that configuration for you. But can I ask you why? If you allow your employees to be able to use the browser and search the web as a part of their job, why is it not okay for the copilot that’s acting on their behalf to reach out on the web and assist them? So I’m surprised with the amount of configuration that enterprises want, which is, of course, enterprises have different business rules and process, so we built many more customizations in M365 Copilot than I had anticipated coming in.
MOLLY WOOD: I read some research recently where one of the AI firms said that they had done some analysis and found themselves really surprised at how long the long tail of interactions with AI are.
RAJESH JHA: So true. This generation of AI is about information work. It changes how people write, learn, collaborate, read, and so there’s a long tail. Not all of us triage information the same way.
MOLLY WOOD: What are some best practices that are starting to emerge? Because certainly every enterprise is going to adopt differently, interact differently, and then have different use cases that may or may not make their experience work.
RAJESH JHA: That’s a great question. I would say the successful implementations that we see are the first stage, of course, is to enable people to get productivity boosts with the AI, where the AI is really assisting you. And then the next most important thing that customers end up doing that gives them a real return on investment is to rethink their high-value business process or high-cost business processes, and figure out how to reconfigure that with agents that can automate a bunch of those processes to be either more effective or more efficient. That, I think, is changing the way work happens. For example, if you’re a lawyer and you’re working with a bunch of documents, instead of having—somebody spent a lot of time going through the past relevant briefs and composing a new template. How do you change a new brief creation? How do you change an approval process? How do you change a customer support ticket handling? How do you change a marketing campaign? How do you change a developer workflow? I see customers actually taking a business process, and they are rewiring that for a world where people and AI can work together to automate that, to make it more effective, more efficient. So that is a good best practice, is not trying to solve a hundred business processes, but taking a few and going really deep and measuring the ROI and tweaking that, because then the payoff is right there.
MOLLY WOOD: Well, and to dig in a little further, it also sounds like what you’re saying is that companies and CIOs maybe need to commit. Like, if you don’t commit, if you don’t plug Copilot in, if you don’t enable the full Microsoft Graph, if you maybe don’t give access to the web, people are still going to find these tools and use some version of them that might not be as good as they could be if you really do go all in.
RAJESH JHA: Yeah, Molly, it’s exactly right. I mean, it goes back to the point we made, which is, leaders, have, you know, leaders have to lead. And the reason why they have to lead here in this transformation is, if a support organization, a marketing organization, engineering organization is wired to work the old way, they are not automatically going to rewire themselves for a world where AI can do a bunch of tasks and people’s tasks change. That’s not going to happen, bottom-up. It’s going to have to happen from the leaders leaning in and saying, okay, you know, am I sure that I have the right compliance and governance and security? Because those are non-negotiable. But once I have that, how do I lead the way where I empower and I get to a world where AI assisting, to agents and people working together? One of the concepts we’ve talked about, and it’s come out in the new Work Trend Index is, corporations, for the longest time, have had static org charts, and every once in a while you do a reorganization and you reconfigure teams for your new evolving business priorities. But those things are not very frequent, nor should they be very frequent, because there’s a huge lag to those things. The way work happens is people, it’s, teams are less static and they’re more outcome-driven. Some of this started to happen post-COVID also, where the fluidity of the team composition was not represented in the org chart. That thing is going to accelerate far more in a world where digital labor and people, agents and people, are going to work together as business processes get rewired. None of this is going to be possible without leaders committing to that. And the way you can commit to it is by taking a few processes that are incredibly important for your business’ top line or your profitability because it’s a high-cost thing, and trying to figure out how to reconfigure those things for people and agents working together in one team.
MOLLY WOOD: What do you wish business leaders understood about AI agents to help them make that commitment?
RAJESH JHA: The first thing I would just say is, like, it’s not some distant future, it’s happening now. My product management team, they ran a research today of a bunch of different organizations, and this time, you know, usually we talk to 30,000 people across different organizations, 30 different countries. This time, they also reached out to AI-native companies that have started to emerge, so-called frontier companies. And if you take a look at the frontier companies, it is very obvious that the way the distribution of human work and digital labor, how that gets constituted, there’s very interesting patterns that are starting to emerge. The first thing I would just tell leaders is—of established companies such as myself, my peers, and the rest of large organizations—it’s possible today to take full advantage of agents. The security model exists, the identity model exists, the user interface exists. The hard work here is to actually go pick the processes that give you the most bang for the buck and then be rigorous about measuring that. And this is why we invested in something called the Copilot Impact Dashboard, so customers can take their core KPIs and they can measure how the copilot is moving those KPIs. So be rigorous, but be forward-looking. It’s not, hey, let’s just take a leap of faith and let’s get agents everywhere. Be rigorous with security. Be rigorous with governance. Measure the ROI, but pick the processes that you’re going to go add agents to.
MOLLY WOOD: It seems like the other tension, in addition to going all in, right, in addition to commitment, is pace, the pace of introducing that change, going fast to keep up to, you know, be pushed properly by Frontier Firms, but not compromising security and guardrails.
RAJESH JHA: And so on the pace, it’s a super good tension that you pick up on, and we deal with the tension all the time ourselves at Microsoft. What is hard is to have pace at scale. But what’s not hard is to have pace at smaller scale. I’m not advocating for a large organization to go and say, go rewire all your business process, fast, into the frontier methodology. I’m saying, pick a few that are really important to you and go with base on those, learn from that. Meanwhile, invest in skilling. Meanwhile, invest in assistance for everybody else. And that’s what we do, too, in my team. We want to move very quickly, but we move very quickly in a scoped garden with a few processes, a few customers, and then once we are sure it is mature and it’s ready, do we then scale it out. So, moving fast doesn’t mean move fast all over, all at once, if you’re a large organization. It means you’re moving fast by having picked and assessed. And, you know, which way do you want to go fast and where do you want to go more cautiously, and then take the lessons from moving fast and more broadly.
MOLLY WOOD: Right. It’s so valuable to put a fine point on that, because any problem is manageable in component parts.
RAJESH JHA: Hundred percent. Hundred percent. And picking is the important thing. But if you pick something unimportant that you’re moving fast on, you’re not really learning a lot either.
MOLLY WOOD: Right. Then the other tension, the technology itself is moving really fast, so you might have incorporated something, you’re doing a great job measuring it, and now there’s a whole new tool. How do you advise business leaders to keep up?
RAJESH JHA: The playbook is still the same. You have to figure out how to move fast and stay predictable at the same time. And the way you do that is by managing where you move fast and by having rigorous measures of whether the ROI is working out or not. Because you’re a hundred percent right. I mean, the compression of innovation that I’m seeing in the AI wave is like nothing that we’ve seen before in the last 30 years.
MOLLY WOOD: So as we talk about committing, you know, it’s one thing to say, maybe give your model access to the web, but there’s this Microsoft Graph that it seems like really unlocks that power.
RAJESH JHA: The Microsoft Graph is really not Microsoft’s graph. It is a graph for the customer. It’s owned by the customer. And what it captures is how people inside of their organization work together—the meetings that are important, the documents that have been created, the chats and the projects that people are working on—the business processes that run in their organization, that is all a part of the Microsoft Graph. So you take the power of a reasoning model that now has access to the graph—remember again, the reasoning model has access to the same things that you would as an individual. So when I ask a reasoning model or an agent to work on my behalf on Microsoft Graph, it is working with my permissions. But now it has the ability to read far more, process far more than I would be able to. You take the unique intellectual property of the customer in the graph with all the right permissions overlaid, and then you let AI work on that, along with what’s available in the web, on the world knowledge, your enterprise knowledge—that is the real enabler. So what is great about the researcher in Microsoft 365 Copilot is that it works with your enterprise permissions and your enterprise data, everything that is in the graph. And that is what I think is a real breakthrough. Now you’ve got the makings of a digital employee, somebody who was able to come in, join an organization, and take advantage of all the intellectual property with all the permissioning honored, and take that and be a part of producing output for the company.
MOLLY WOOD: Right. I mean, it’s institutional knowledge, like, think about what a great employee I could be if I knew all the context and all the history that a company had gone through.
RAJESH JHA: Exactly. And all the relevant, you know, escalations, projects, all of that stuff.
MOLLY WOOD: Switching gears a little. You work very closely with Microsoft CEO Satya Nadella. Are there questions that he regularly asks you that you think all leaders should be asking their employees?
RAJESH JHA: I think fundamentally my boss, you know, Satya, I mean, he’s pushing me on exactly the set of questions you were asking, on my own organization. The way he describes the priorities that I have and my peer groups have, three priorities—quality, security, and AI transformation, are you moving fast? Fully understanding that quality and security and then moving fast, sometimes are intentions, but that’s what he’s saying. Are you doing your job to do all of these at the same time? A lot of the thrust of his conversations, questions are, are you evolving your own team to be frontier, and what’s getting in your way? Because whatever we learn then applies to our customers. So are we applying the same methodology to make your enterprise-grade securities non-negotiable. And then at the same time, are you moving fast to take full advantage? Are you really rethinking your production functions? So I would say all of his questions and interactions distill into these three things, and are we doing a good job balancing these three things.
MOLLY WOOD: This company has reinvented itself many times. What are the key lessons that we and all business leaders should take from those reinventions?
RAJESH JHA: I would say again, mission matters. Through those 50 years, our mission is a theme around empowerment, so number one. Number two, I would say is, team culture matters, of course, because the how and where the work—there’s no substitute for that. But then I would say you gotta do the and, it’s never an or. How do you stay scaled and perform while waiting and disrupting at the same time? That comes down to strong leadership, it comes down to good processes. Then, what you touched on that I want to reiterate is, you know, just resiliency. We didn’t get everything right in the last 50 years. We made mistakes, but being resilient, learning from the mistakes, embracing the red so we can do a better job the next time. I think those are all components that I would just say we benefited from having incredible CEOs from Bill and Steve and Satya, so that has been an amazing, you know, learning experience for me and many others to work with those three amazing individuals.
MOLLY WOOD: If our listeners could take away one actionable AI-related insight from you, what would it be?
RAJESH JHA: I would say, go embrace agents. Pick out your most important processes, reimagine them how agents and digital labor can rewire that.
MOLLY WOOD: We love to ask our WorkLab guests how they are using AI themselves, either at work or in your personal life. Are there use cases that have been really helpful for you that you’re willing to talk about?
RAJESH JHA: Yeah, the one thing we didn’t talk about that I feel is just mind-blowing, is this reasoning models. You know, today, Molly, you and I going back and forth, then you ask me a hard question, I’ll give you an answer off the cuff. But if you tell me, Rajesh, go think about it and come back to me. And, you know, I have a set of tools available to me and I come back to you, I’m going to give you a much better answer. And so with the reasoning model, that’s what’s happening. We are now letting the AI actually go reason over stuff, give it more time, more compute, and more tools. And so for me, the real breakthrough was every quarter I sit down with my leadership team to take a look at our plans for the next six months. So I ran the researcher model. The researcher model is a deep reasoning model in M365 Copilot that works with the graph and the web, and I asked it, hey, I’m about to have an off-site with my leadership team to take a look at the plans for the next six months, take a look at the competitive landscape, take a look at customer feedback, take a look at all the ideas that have been accumulating in the team, and try and give me a draft of what might be a good starting point for our off-site for the next six-month planning. It was incredible. It was able to get through my email and documents that I hadn’t fully read but my team was iterating on, it looked at the last year’s plans to take a look at the competitive landscape, gave me a great five-page, actually it was eight-page, document that I can now go and tweak and make it my own, and overlay my perspective and use as a starting point. The other one is, like, often I talk to customers, and before I get on the call, I ask my agent—it’s called a KYC agent that my team built, which is, know your customer—and so before I get on to a call with a customer, I go into that agent experience in M365 Copilot and say, can you bring me up to speed on this customer? And it’s able to get to the support tickets, their adoption, their past communications with me, all of that stuff. And I often end up showing the customer the output, and we walk through it, and their question is like, how did you generate that? And in personal life, you want to make a big purchase, you want to do a seven-day trip planning, you want to buy a new car. You know, instead of clicking on 40 links, they can do a lot of research for you and show you that. So I use it for a lot of that too.
MOLLY WOOD: Fast-forward for us, three to five years, if possible. What do you think could be the most profound change in the way we work?
RAJESH JHA: You know, I think it goes back to the reconstitution of the workforce between humans and digital labor. I think the way we think about org charts, the way we think about groups coming together, the way we think about production function. I mean, it is a big deal to have intelligence be abundant and for it to be affordable. At the same time, I feel very encouraged about what people can uniquely do when you take a lot of the grind and predictability and, you know, have a colleague that is intelligent. I mean, I feel very bullish about how the economy is going to evolve. It won’t be a straight line. There will be scale backs in some of the roles that we think about investing in today, but there will be new roles we’ll be creating. So it’s very hard to predict exactly how it’s going to play out or whether that’s a three-year horizon, five-year horizon, but I do think that is a very clear trend of where we are headed.
MOLLY WOOD: Rajesh Jha is Microsoft’s Executive Vice President of Experiences and Devices. Thank you so much for the time today. I couldn’t appreciate it more.
RAJESH JHA: Thank you, Molly. I really do appreciate the time as well.
MOLLY WOOD: That was Rajesh Jha, Microsoft’s Executive Vice President of Experiences and Devices. Thank you all so much for joining us on this final episode of this season of WorkLab. We’ll be back next season with more insights on how to stay ahead of the curve while the way we work is transforming so quickly. If you’ve got a question or a comment, please drop us an email at worklab@microsoft.com, and check out Microsoft’s Work Trend Indexes and the WorkLab digital publication, where you’ll find all our episodes along with thoughtful stories that explore how business leaders are thriving in today’s new world of work. You can find all of it at microsoft.com/worklab. As for this podcast, please, if you don’t mind, rate us, review us, and follow us wherever you listen. It helps us out a ton. The WorkLab podcast is a place for experts to share their insights and opinions. As students of the future of work, Microsoft values inputs from a diverse set of voices. That said, the opinions and findings of our guests are their own and they may not necessarily reflect Microsoft’s own research or positions. WorkLab is produced by Microsoft with Godfrey Dadich Partners and Reasonable Volume. I’m your host, Molly Wood. Sharon Kallander and Matthew Duncan produced this podcast. Jessica Voelker is the WorkLab editor.