アイデア：望ましい仕事の未来へAIを導く

Behind every emerging technology is a great idea propelling it forward. In the Microsoft Research Podcast series Ideas, members of the research community at Microsoft discuss the beliefs that animate their research, the experiences and thinkers that inform it, and the positive human impact it targets.

Since 2020, researchers across Microsoft have conducted, surfaced, and analyzed key research into how people work as part of the New Future of Work research initiative. They’ve done this through a variety of lenses—from changes caused by the pandemic to the adoption of hybrid work practices to the arrival of increasingly capable AI models—with the goal of empowering people and organizations to redefine work in real time.

In this episode, Microsoft Chief Scientist and Technical Fellow Jaime Teevan talks with researchers Jenna Butler, Jake Hofman, and Rebecca Janssen about the latest efforts: the Microsoft New Future of Work Report 2025. The group explores what the report says about AI’s adoption and impact, the intentionality needed to create a future in which people flourish, and current perceptions around AI use. Plus, is AI a tool or a collaborator? And why the answer matters.

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The New Future of Work

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Microsoft New Future of Work Report 2025

Publication | December 2025

The New Future of Work: Research from Microsoft into the Pandemic’s Impact on Work Practices

Publication | January 2021

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Transcript

[MUSIC]

JAIME TEEVAN: Really what we’ve been living through, it’s not that, like, every year work is changing in a generational manner. It’s much more that we are in the middle of a really big shift in sort of how digital technology can support people getting things done.

JENNA BUTLER: It is not predetermined. The future of work is actively being built by us, by consumers. I love that.

JAKE HOFMAN: It’s easy for us to say, let’s get everyone to adopt and let’s boost efficiency. Let’s make everything really quick, right. But I don’t think that that’s actually the future, like, we want to live in.

REBECCA JANSSEN: We keep benchmarking against the past. So what can AI do, or can AI do what we already do? And I think this is, like, a mistake or maybe only the first step and the more important step comes next.

STANDARD INTRODUCTION: You’re listening to Ideas, a Microsoft Research Podcast that dives deep into the world of technology research and the profound questions behind the code.

[MUSIC FADES]

JAIME TEEVAN: Hi, I’m Jaime Teevan, chief scientist and technical fellow at Microsoft, and today, we’re going to talk about the new future of work.

So back in 2020, researchers from across Microsoft came together to try to make sense of this seismic shift in work practices that was happening as a result of the pandemic, and the next year, the group published the very first New Future of Work report. Microsoft has been publishing a new report every year since with no shortages of disruptions and major technological shifts in between.

Joining me today to explore the latest report are my colleagues, Jenna Butler, Jake Hofman, and Rebecca Janssen, who are a few of the many authors on the report.

Jenna, Jake, Rebecca, welcome to the podcast.

REBECCA JANSSEN: Thanks, Jaime.

JAKE HOFMAN: Thanks, Jaime.

JENNA BUTLER: Thank you.

TEEVAN: There are a lot of factors that shape the work people do and how they do it, from social factors to economic factors to technological factors. And, you know, as we’ve learned from the previous reports that we’ve written together, accounting for this complexity requires a lot of different backgrounds, knowledge bases, approaches, and research methodologies.

So before we get into the specifics of the report, I’d love it if each of you could share a little bit about the experience and expertise that you bring to the contributions you made to the report and why the work you do matters. Jenna, why don’t you get us started?

BUTLER: Sure, yeah, thank you, Jaime.

So I’ve been on the report since it started in 2020, and I’m really proud of the work that we do. I think it matters for a number of reasons, but most importantly, I think, especially right now, people feel like technology is sort of happening to them and these changes are happening to them. And actually, with any technology we introduce to society, that’s a sociotechnical shift. And so how people perceive it, use it, what they want to do with it, what they’re willing to pay for—all these things matter. And so the report, I think, gives some agency to people to let them know, like, what’s happening right now, what’s the latest research, and also how are your own behaviors and views shaping the technology.

And when it comes to expertise, I study software engineering productivity and right now very specifically how AI impacts or changes that. But my background is actually originally in bioinformatics studying cancer. And I’ve always loved multidisciplinary fields because I feel like with the type of problems we have in today’s world, the solutions often lie at the interface of multiple disciplines. And so this report with over, you know, 50 different authors from all over the world, I think, is a really fun example of just how much great stuff you can get when you bring different people like that together.

TEEVAN: Thanks, Jenna. How about you, Jake?

HOFMAN: Yeah, so I’ve been involved with the report since 2023, so less time than Jenna, but as an author originally on bits related to AI and cognition, which is a core research topic for our Microsoft Research New York City lab. And more recently, I’ve co-led a workstream across the whole company called Thinking and Learning with AI, or TALA for short, with Richard Banks, another researcher.

And so Jenna and Rebecca and company, who really drive and lead the report, were kind enough to invite me to be a section editor this year. And I gladly accepted because I know how widely read and impactful the report is. And I think it’s just a wonderful opportunity to showcase research not only from Microsoft but from all around, from a coherent viewpoint and voice.

TEEVAN: Thanks, Jake, and Rebecca?

JANSSEN: Yeah, and we were really glad to have you join us as section editor, Jake, just to say that.

Yes, so I joined Microsoft full time in October 2024, so, kind of, like the new joiner among the three of us. And already during my PhD, I was interested in, like, AI and its impacts on work and society, in particular from the economics perspective. So I was always really excited about that group’s work and was, yeah, just, like, really looking forward to leaning in not only on the economics perspective and those sections but also, like, more broadly with, like, editing the report overall.

And to the point of, like, why it matters, I think what is so exciting about the report is the variety of, like, different people, different backgrounds, and different topics. And there’s, like, so much you can talk about, speak about, but also realize, oh, AI is impacting work but also, like, so many different other parts of life.

TEEVAN: Rebecca, I love your story, too, about how you had been reading the report from outside of Microsoft and then got to come in to engage. I know there were a number of people involved this year who said that. It, kind of, was cool, like, to feel it become something of an institution.

JANSSEN: Yeah, yeah, exactly.

TEEVAN: Yeah, no, super cool. But for listeners who are new to the New Future of Work Report, can you share a little about what it is, who it’s for, what people can use it for?

BUTLER: Yeah, I can take that one. So obviously I’m biased—I think it’s for everyone. But perhaps it’s not. But the idea is to, sort of, showcase the research that’s been happening over the last year. So we release it annually, usually in December, on these big shifts that have been happening, and so the last couple of years, AI has been a big part of it. And the idea is to take research not just from Microsoft but from external places, as well, all around the world, and try and, sort of, sum it up in small statements that we can back up with research. And we are very careful to make sure we’re only doing this in areas where we have a researcher and we can make a pretty bold claim and where we feel confident in the data and that it backs up what we’re saying.

And so if you just want to read one, albeit somewhat long, report, you’ll get an idea of what’s happening in the world of AI and work fairly broadly. So from the economy to adoption, to thinking and learning, to specific industries and what leading experts outside the company are thinking and predicting, as well. So it should be broadly accessible to any sort of academic audience. You don’t need to be an AI expert to read it. And hopefully, it’ll help with all different areas.

TEEVAN: You know, one of the things that jumped out to me, Jenna, sort of reflecting on the past five years—this is our fifth report—so on the past … over the ones we’ve done is every time when we go to release it, it’s like, “Oh my gosh, work has changed. It will never be the same again.” [LAUGHTER] I was actually, like, reading the past introductions to the report.

In 2021, during, you know, thinking about the pandemic, I was like, “Work will never again be the same!” In 2022, as we were shifting to hybrid work, I said, “Work is changing faster than it has in a generation.” 2023—we’ve been living through not one but two generational shifts in how we work. And then, you know, more recently, obviously, we’ve been talking a lot about the transformative impact on AI and productivity.

And one thing that was fun about doing this report was sort of looking at these what felt like different shifts over time and, like, being able to see the through threads and the connections. Because really what we’ve been living through, it’s not that, like, every year work is changing in a generational manner. It’s much more that we are in the middle of a really big shift in sort of how digital technology can support people getting things done.

And I’d be curious about what changes in attitudes and understanding of AI and work you all have witnessed in these past five years across industry and academia and even, like, on an individual level, like how it’s changed for you personally.

HOFMAN: I can kick us off with that maybe. I think it’s pretty amazing, like, in the last three years, to think about just how much in the research world has changed on generative AI and work.

You know, like, I remember, like, January 2023, you know, people were just off to the races. Everyone was doing everything they could to just evaluate a model in isolation because that’s what people had access to. But there was very little in terms of, like, humans in the loop and people evaluating what happens when it’s not just a model taking a standardized test or a benchmark. And so that was something that we immediately focused on because it really hit our expertise in the lab here. And, you know, there were others, but it was still, kind of, limited in terms of who had access to the models and who had the capability to, like, design and run experiments that involved, you know, real people, right. And even then, it was, kind of, limited to laboratory experiments, right.

And now, you know, fast-forward three years, and we have pretty much everyone has access to any model they want to. They have amazing tools to build and design experiments, and they can run them in the field, right. And I think there’s also been a shift from, OK, how much does this tool speed us up to what are the bigger, broader effects— which is all the exciting stuff, I think, for thinking and learning in particular—that these tools have beyond just efficiency.

So I think it’s just amazing. In no other time have you seen this leap from, you know, a three-year period from like a few people doing small lab studies to like lots of people doing field experiments with, you know, wide-reaching implications.

TEEVAN: Yeah. Rebecca or Jenna, have you observed in your own work practices, sort of, Jake’s talking about how his research is changing. Have you been observing things like that, as well?

JANSSEN: Yeah, definitely. I would say it’s just so interesting to see how these tools can help you. I mean, when I started or, like, I finished my PhD kind of like throughout this wave of, like, AI really picking up and just, like, even in this short time seeing, “Oh, where does it help me? Where does it not help me that much?” But also the stress of it: “Oh, where do I want to stay involved?” And I think that’s still, like, an ongoing progress or process, at least for me, to figure this out. And I think that’s also what I hear from other people, that they’re, like, experimenting a lot, playing around with this and figuring out, OK, where does it actually change things and change workflows on the broader level.

BUTLER: Yeah, I think, Rebecca, to that point of, like, where does it help me or where does it not, something that has struck me over the last five years of the report is how nuanced it is and how we anticipated certain things and it wasn’t necessarily like that.

Like when we all went remote, we thought, oh, people will be lonely. And there were studies looking at this, and it was like, wait, some people are really thriving. What’s that about? And then hybrid work, like, we don’t all need to go back or we need to go back sometimes.

And then with AI: “This incredible tool—everyone’s going to benefit.” And then we saw, oh, there’s so many factors as to who benefits and how they benefit, and whether they believe it’s going to be useful even impacts it and what kind of tasks they’re doing and what their problem-solving style is. So I think the uniqueness of all of this and how each worker is different and there was no single answer has been really fun to see and watch, as well—and tricky but keeps us employed.

TEEVAN: Yeah, yeah, yeah. No, so I like this thinking about the different ways that people … like, even just listening to the three of you and seeing the variation in the ways that you’re thinking about your work practices changing, adoption clearly matters a lot, and I know that’s something that we center in [on in] the report.

Jake, you talked about how everybody has access to models. But not everybody is actually using the models and we’re certainly not using them in the same way.

I was wondering if you could tell us a little bit about what the report says about today’s level of adoption and like who’s using it and how.

JANSSEN: So what we see in the research—and this is mainly based on, like, surveys being conducted in different countries and then, of course, also some more, like, field experiment studies—what we see is that AI adoption is definitely increasing overall, but it’s really heterogeneous and more nuanced in depth, like who is using it and also, like, for which purposes.

So a German survey found that about, like, 38% of the respondents were using AI for work (opens in new tab). But this is just, like, the average. And we do see, like, lots of differences across, like, industries.

So there were other surveys where the results showed that IT and procurement were example industries or, like, sectors which were more open to use AI than maybe marketing or operations (opens in new tab).

There also has been some evidence on men being more open to using it than women (opens in new tab). I don’t know how the gap looks, like, right now. I hope this is, like, converging even more. But this is maybe, like, on the high level, like, about AI adoption levels.

And for the question of, like, what people use this for, there are now more studies also, like, using chat conversations to see, “Oh, what are actually, like, the user intents and goals.” And we have a group also within Microsoft who has done something similar, and they found that information retrieving but also communicating has been or have been among the top user intents. There’s definitely a lot of, like, writing related or there are a lot of writing-related tasks that are conducted with chat tools, and I think that’s, like, the big picture we see.

But maybe even there, I think, it also depends a lot on which AI tool people are using. So maybe Anthropic’s work sometimes shows more, a heavier weight on, like, coding and developer use cases. So there’s definitely, like, some variety.

TEEVAN: And, Jake, I know you’ve done a lot of studying in the education context, as well. Can you share a little about that?

HOFMAN: Yeah, I mean, the report, I think, gives really definitive numbers in this regard in that recent surveys show that, like, 80% of students, sorry, 80% of [K-12] teachers and 90% of [K-12] students report having used, you know, generative AI for schoolwork (opens in new tab), you know, with use growing year over year, right.

What’s interesting is that, you know, there are, like, myriad educational, like, tools and specific versions of generative AI products and all these startups, and yet almost all of the reporting shows that people are using the generic off-the-shelf Copilot, ChatGPT, Claude, Gemini, and so on (opens in new tab) not necessarily even in like a learn mode, right, and so I think this speaks to, like, the bigger sort of policy and training gap that’s out there in terms of the fact that everyone is using these tools, but there’s not amazing guidance for how to use them constructively.

The good news there, I think, is that we’ve seen, like, big efforts this year. So with the American Federation of Teachers in partnership with Microsoft and OpenAI and Anthropic, there’s actually a big program to try to re-skill teachers and give them the training to use this technology appropriately (opens in new tab). So I think there’s a lot of hope there, but I think it’s also really something we should keep our eye on in terms of making sure that we’re using these tools in the right way.

TEEVAN: Yeah, and one of the challenges is that the tools are changing so fast. Like, it’s very hard to provide any guidance …

HOFMAN: For sure, yeah.

TEEVAN: … when it’s going to be different tomorrow. Yeah, I find that, too.

Like, people are always asking me, they’re like, “Ooh, what surprises you most about how people are using AI?” And it’s funny because almost as soon as something surprises me, like a week later, everybody’s like, “That’s obvious” because things are changing so fast.

But I’m going to turn that question on to all three of you, and I would like you each to answer this. I’m curious what you have found particularly surprising about how people and organizations are leveraging AI right now. Maybe, Jenna, you want to kick us off?

BUTLER: Sure, yeah. I do a lot of studies looking at how organizational behavior is changing with AI, and something that is somewhat surprising but I think might really surprise others is just how much influence individual people have on the adoption of these technologies.

So lots of studies have shown that how individuals talk about it with their colleagues will change whether they’re willing to use it or what tasks they use it for (opens in new tab) and how leadership demonstrates and discusses these tools will impact whether their people feel like they can use them (opens in new tab).

And so while we did just give everyone like, “Hey, here’s access to these absolutely incredible tools,” as you said, Jaime, we