In this episode of the HR Digitalization Podcast, Anna Carlsson and Emira Blomberg sit down with Nina Rapp to discuss how HR can take an active role in the AI revolution – and why HR is critical for ensuring that technology creates real value in organizations.
The conversation is grounded in Microsoft’s latest Work Trend Index 2025, which reveals, among other things, that Swedish companies are lagging behind in the adoption of generative AI. Nina Rapp shares insights into how AI is already transforming ways of working – from personal assistants to autonomous agents acting as digital colleagues. The discussion spans technology, culture, leadership, and learning, highlighting how AI is no longer a future vision but an ongoing transformation that HR needs to lead.
A recurring theme in the episode is the importance of practicing, not just planning. By testing tools, launching internal initiatives, and driving education, HR can pave the way for broader AI adoption across the business. At the same time, the need for reflection is emphasized – around concepts such as “productivity,” “digital colleagues,” and “human competence” – and why the way we talk about AI matters.
The episode offers both strategic perspectives and concrete examples of how HR can help ensure that AI becomes a positive force in working life. By stepping forward as change leaders – in collaboration with IT and executive management – HR can not only manage the transition but actively shape it.
So how can HR actually unlock AI’s potential in practice? Tune in to the episode and gain insights, experiences, and future outlooks from one of Sweden’s leading voices on AI and the future of work.
Note: This episode is in Swedish. A translated transcript is available below.
Transcript:
Anna Carlsson: In today’s episode, Emira and I are joined by Nina Rapp from Microsoft Sweden. Together, we take a deep dive into what actually happens when AI becomes part of everyday work – not just strategy. What does it take to turn the potential of technology into real change in the workplace?
We start from Microsoft’s brand-new Work Trend Index Report 2025, which, among other things, shows that Sweden is lagging behind in AI maturity – something many of you are probably already aware of. The conversation ranges from Copilot and practical applications to reskilling, leadership, and HR’s role in driving transformation. We talk about AI assistants, data culture, new ways of working – and why HR cannot wait for someone else to lead the way.
We recorded this episode just before the summer holidays, when Nina was still Business Area Manager for Modern Work. Since then, Microsoft has reorganized, and Modern Work is no longer a separate business area. These topics have now been integrated into a new division called AI Business Solutions, led by Helena Fuchs.
Anna Carlsson: Welcome to the HR Digitalization Podcast, Nina.
Nina Rapp: Thank you so much! Excited to be here.
Anna Carlsson: So great to have you here – and Emira is with us as well.
Emira Blomberg: I’m here.
Anna Carlsson: Perfect. Every time. Well, almost every time.
Emira Blomberg: Almost every time.
Anna Carlsson: Exactly. And I actually had your predecessor here, Nina, four years ago when you launched Viva. And before that, you really didn’t even hear Microsoft and HR in the same sentence. But a lot has happened since then. Before we dive into that, though, could you introduce yourself? Who are you, Nina?
Nina Rapp: Well, that could turn into a philosophical question we could discuss at length. But my name is Nina Rapp, and I’m Business Area Manager for what we call Modern Work at Microsoft. That includes all the technology closest to the workplace, and also the role of acting as a future of work lead for AI in the workplace. Much of what I talk about right now. Technology in its context is very much my focus – tech is not an end in itself. Even though I represent it commercially, I always want to emphasize that.
Anna Carlsson: I can relate to that. I used to be a commercial representative in this area before I started my own business – and at that point, I didn’t want to be in that role anymore. Because, of course, when you represent a company, you inevitably become its representative. But you have a fantastic portfolio to represent.
Nina Rapp: I couldn’t agree more. And the reason I’m working in this role today is that I used to be an IT generalist. What I saw with my customers was the power of these tools – how empowered employees become when they have the right tools, the right culture, and the right perspective. When you put technology, workplace, and people together as a whole to support employees – that’s what really fascinated me. I also felt it was highly relevant for a new audience, not just the classic IT audience. Over the years, I’ve worked my way into the role I have today.
Anna Carlsson: So, what’s your educational background?
Nina Rapp: I studied IT in high school, I did. But at university, I studied economics and marketing – to be able to talk about strategy and what we actually do with these tools. That’s really my profile in a nutshell. The technology is magical, but just talking about technology won’t let us reach its full capacity and potential. We need to be able to articulate and solve business challenges with it.
Anna Carlsson: That’s great. I actually have a somewhat similar background – except I skipped university. But I also started with IT, in high school. And what about you, Emira? Maybe you should share that here, since you and Nina haven’t met before. Sometimes we do a little pre-chat, but this time it might be good for Nina to know.
Emira Blomberg: Yes, exactly. My background overlaps a bit. I also have a degree in economics, but I’m also a linguist. I usually describe myself as both a linguist and an economist. For me, education was more about curiosity – I could have studied any interdisciplinary subject. But I find it fascinating that language is becoming so relevant again now, thanks to what we’re talking about today with LLMs and so on. For me, language has always been about logic – and economic systems are also logic. It’s about recognizing patterns in the world, whether economic patterns or linguistic ones. That helps me understand reality and where we’re headed.
Right now, I work at a product company, in business development – with one foot in the commercial side and one in product. Product is, of course, commercial. So we talk a lot about technology and how it enables things. But our platform isn’t particularly advanced – it’s actually quite simple and very user-friendly.
Nina Rapp: What kind of platform is it?
Emira Blomberg: We provide a tool for digital reference checking. It’s a very niche product. In the HR world, you have ATS systems, which are the most complex recruitment systems, since they handle the entire application flow. Then you have HR systems inside companies. So when we talk about agents, copilots, and facilitators – technical enablers – that’s very relevant in my area too. That’s why it’s so exciting to have you here.
Also, Anna and I were at the HR Tech conference recently. And everyone was talking a lot about the future – “this is going to happen, this is what we’ll see.” But very few could describe what’s happening now – in practice.
Anna Carlsson: Exactly. And that leads to the perfect question for you, Nina: How do you see where we are right now, in your area? What does the market look like? Where would you like to start?
Nina Rapp: That’s a very exciting question, because so much is happening. As I mentioned, I have all of Microsoft’s workplace solutions under my umbrella. And right now, 90% of the conversations are AI-related. We’ve been in the generative AI era for about two and a half years. What made generative AI so exciting – and why it became so big – is that it fundamentally changed ways of working.
AI has existed for a long time, but with generative AI it became understandable for the everyday person. It turned into something that actively supports us. Over the past year and a half, we’ve spent a lot of time on that.
A year ago, when we sat here, we were talking about how Sweden was falling behind – and that it was employees driving adoption at the workplace. Employees were bringing consumer tools to work, because sanctioned tools weren’t available. But we couldn’t manage without them. Stress levels were very high, and we saw that generative AI could relieve some of that burden and help us work smarter. So the focus was very much on personal productivity.
Anna Carlsson: And just to clarify for listeners, we’re recording this in May, even though the episode will be released after summer.
Nina Rapp: Good point, Anna – thank you! So, where we are today is that we’ve moved from focusing mainly on personal productivity to talking about agents and digital labor as extensions of our teams. In May, Microsoft released a new Work Trend Index report, where we share data points about the labor market pulse and the evolution of how we see this.
Step one: every employee has an assistant – that’s where we’ve spent a lot of time. Step two, where many organizations are now, is agents that work on our behalf. As employees, we set the direction: “This is what you should do, dear agent – go help me with this.” Basically, human-led agent execution.
Step three – where the frontrunners already are, but most organizations are not yet – is the next part of the agent spectrum. Agents will carry out more and more tasks without needing constant instructions. We’ll be more like conductors, setting the direction, but without having to issue commands for every single task. That’s where we need to rethink the role of agents in our teams – as digital colleagues bringing intelligence and power to support us.
Looking ahead, the investments we’ll see in the next 12–18 months are about keeping headcount stable, but increasing productivity and scaling up with more digital labor through agents. Those are some of the trends and insights from this year’s Work Trend Index report.
Anna Carlsson: Which makes me think – do you look at different categories within organizations, or across industries? Many of our listeners work in HR, or with providers, or as consultants. But they all share that HR or “people” perspective. Do you see any difference in how HR compares with other functions? Should HR still be the ones creating the right environment and tackling these questions?
Nina Rapp: Let me first explain how the report is structured. It’s based on telemetry data from Microsoft services, showing how they’re used globally. We also look at LinkedIn trends and use LinkedIn data. And then we conducted 31,000 qualitative surveys, with 1,000 respondents from Sweden, to get local insights.
We can see some differences across industries. But we haven’t broken the data down by role, so I can’t say that HR stands out one way or the other in this dataset. And generally, when we talk in Sweden – including in forums like this – we mostly focus on the Swedish numbers, even though we follow the global trends closely.
Anna Carlsson: But how are we doing in Sweden? I mean, we’re not really known for being… I’m thinking in general, we’re often considered digitally mature. But in HR, I know from other studies that we’re a bit behind. So how does Sweden compare globally when it comes to adopting this technology and moving through the different stages?
Nina Rapp: Sweden hasn’t exactly been quick to jump on the generative AI bandwagon. And that’s not just our reports – every report I’ve seen shows the same thing. Sweden has fallen behind in usage.
I think it comes back to something cultural: our own preference for innovation. We don’t just want to adopt what others have built – we want to invent it ourselves. And often, we’ve also treated this as an IT issue, leaving it to IT departments that didn’t always have the right conditions.
What’s needed is clear leadership, a focus on the human side of changing ways of working, and IT at the table as well.
One interesting shift in this year’s report is that previously, employees were the main driving force. But now, leaders have really leaned in – showing greater trust and understanding of working with generative AI and agents. In fact, in Sweden, managers are almost twice as advanced as employees in their understanding, especially when it comes to agents. And I think that’s fascinating.
Anna Carlsson: Yes, really. I mean, last year it was the opposite – it was widely discussed that leaders were lagging behind employees. But now they’ve clearly taken a step forward.
Nina Rapp: Leaders have indeed taken huge steps forward. But we can’t forget the rest of the organization. I’d say employees have come a long way in terms of personal productivity, but they haven’t yet understood agent-based AI.
And that’s where we need to go back and forth. It’s not about employees or leaders – everyone needs to be on board. And we need to make clear that this isn’t an IT issue. It’s about innovation, about what we want to do going forward, about how we rethink organizational structures.
In fact, we’re also seeing – building on insights from a Harvard professor – that organizations will change structurally. A new function will likely emerge between HR and IT, tasked with managing and orchestrating this new agent spectrum – our digital colleagues.
How do we capture business needs? How do we respond and create or source the right digital workforce, now that we can access intelligence almost on tap in a way we never could before? These capabilities sit right between HR and IT. That’s a very exciting change to watch. We’ve borrowed the idea from Harvard, but I think it’s going to become reality.
Emira Blomberg: I think we have a big challenge here when it comes to the whole language and terminology. Generative AI became quite popular and accessible very quickly thanks to ChatGPT. But I don’t think we’ve really embedded it into our organizations yet. One reason is that we still struggle with concepts like “productivity.” What does that really mean?
In some roles, productivity is very clear and measurable. In others, it’s far less clear and much more subjective. I think that’s a major challenge – defining what productivity means, and recognizing when we’ve actually achieved productivity gains.
And then there’s the whole concept of agents. You call them digital colleagues – but are they really colleagues? Isn’t that just a way of anthropomorphizing? Do we really need to humanize them? I find it interesting, because you also said we need to rethink the concept of agents – that they used to mean one thing and now they’re something else. So, does it really matter what we call them?
Nina Rapp: That’s a fascinating perspective. I haven’t actually heard it put that way before. But I think it’s worth reflecting on how we want to shape this. Personally, I like the concept of digital colleagues. I use a set of agents myself, and they make me feel so empowered. So to me, they really are digital colleagues that I value highly.
In my role, I’m expected to go into many different meetings – with customers, with partners – very well prepared. My Executive Briefing assistant is an agent that keeps track of everything I need to know. It helps me go into those meetings and shine. People often think I’ve spent hours preparing, when in fact, I’ve had the support of my agent.
Anna Carlsson: I can definitely relate to that.
Nina Rapp: I know exactly what format I want, and I get the information in a way that works for me and my role. To me, it feels like having a digital colleague in my team. I do understand if not everyone likes that terminology, but from my own experience, once you start working this way, it feels very natural.
And this will also change how we build organizational structures. Traditionally, they’ve been built around knowledge and information. But in the future, we might instead think in terms of tasks: bringing in a sales agent, an onboarding agent, or some other form of competence quickly when we need it.
Of course, human competence is still crucial. People are in the driver’s seat, and human skills will remain extremely important. That’s also what we see in the skills data – AI competence ranks as number one, but then come human capabilities like critical thinking, reflection, and so on. We need to lean into those.
Anna Carlsson: I think this ties very closely to HR’s role, since HR is always mindful of the language we use and what different terms signal. I actually had an episode years ago – I think this is episode number 101 if I’ve counted right – about digital colleagues. But back then, before generative AI, we were talking more about automation and robotics.
And I remember there was a huge backlash around the idea of calling them “digital colleagues.” People found it strange and even offensive. It really shows how much depends on perception. If you’re deeply people-oriented, the idea of “colleagues” being digital can feel uncomfortable.
But I also think this underlines the need for hands-on experience. If you haven’t tried working with a digital colleague – or an AI coach, or whatever you call it – you don’t really know what it means. It’s a learning process. You need to take a few steps before you get that “aha” moment and see what’s possible.
What do you think, Emira?
Emira Blomberg: Yes, and I think this connects back to productivity again. Maybe we do need to use terms like “digital colleagues” during this transition period, just to understand what we’re dealing with. But in the future, AI might become so integrated that we won’t even talk about it separately anymore.
It’s the same with productivity. In the past, we talked about specialists and generalists. Now, maybe we’ll divide roles into “generators” and “directors.” Some tasks can be easily replaced by generative AI, while others are harder to substitute. But it’s also philosophical – is there really anything AI can’t do?
Nina Rapp: That’s exactly where we need to take a step back and look at human skills – areas where AI doesn’t shine, but people do. In the survey, for example, conflict management comes up as something we need to work on. Human adaptability, process optimization, creative thinking – these are human strengths.
I also like your point about whether we should even talk about AI as something separate. I often say AI isn’t its own issue. It needs to be integrated into existing processes, into what we already do. Then our ways of working will evolve – some things we’ll stop doing ourselves, and others we’ll reinvent.
But yes, it’s a massive shift.
Anna Carlsson: A very big one.
Nina Rapp: Yes – and it’s happening quickly. But it’s also a natural evolution. We’re not throwing away what we do today – we’re accelerating it. For those who lean in with curiosity, this brings huge opportunities.
One of the biggest is democratization. In the past, digitalization created a divide: some people loved systems and became super-users, while others felt left behind and said, “This isn’t for me.” But with generative AI, the frame changes. It’s natural language. You just describe the outcome you want – “update the system,” “give me the vacation list” – without needing to know all the details.
That means everyone can be digitally empowered, as long as they’re curious and willing to try. And that’s also how we design our services – to make it simple.
Take Copilot, for example. We call it “the UI for AI.” It’s basically the user interface for generative AI. Through Copilot, you can connect everything – from existing business systems to new agents – and access all that power. You just tell Copilot what you need: “Update my CRM system, update payroll, pull the vacation schedules.” Instead of logging into each system, Copilot becomes the front-end.
Anna Carlsson: And I think “Copilot” is a brilliant name. It’s exactly like having someone sitting beside you in the cockpit – like you, Emira, here with me. You’re my co-pilot. So if “digital colleague” feels uncomfortable, this makes perfect sense – someone right there beside you, helping you, supporting you, making things easier.
Nina Rapp: I’m glad you like it! I can’t take credit for the name, but yes – that’s exactly the idea. We are the pilots, and these are our copilots.
Emira Blomberg: Maybe it’s just my dystopian side, but I actually prefer to keep it technical – AI as AI. I’m not a big fan of humanizing it. To me, there’s nothing human about AI. People want to give their agents names, call them this or that – but I think that’s just a fad.
Anna Carlsson: Maybe so. It’s probably part of the journey, and over time it’ll just become a natural part of everyday life. But it will take time for everyone to get there.
I actually said at HR Tech that everyone will have a digital component in their work. Some people reacted strongly to that, but I don’t see how it could be otherwise. Regardless of your job, you’ll need at least some digital literacy – not just to use tools, but also to question and challenge them. That’s part of the AI Act as well – that we all need enough understanding to ask the right questions.
So in four years, when we sit here again – where will we be then?
Nina Rapp: And that’s the thing – the acceleration is exponential. The internet took 16 years to reach 100 million users. Mobile phones took seven years. ChatGPT took two to three months, depending on the source. Things are moving faster and faster.
Think about how much has changed in just the last two and a half years. Classic AI was mostly in the hands of IT. Then generative AI suddenly entered living rooms, dinner conversations, everyday life. At the same time, the services themselves have improved dramatically. The models keep evolving, and now we have agents.
And yes, I know agents are hard to grasp. But think of them as natural product development. For example, in Teams, we now have a meeting facilitator agent. It sets the agenda, keeps time, takes notes, follows up, reminds us when we have only five minutes left.
That’s an agent – but you could also just call it product development, powered by AI. That’s why the term “agent” can be confusing.
Anna Carlsson: So what is an agent, really? In the beginning, people thought of them as stand-alone. But it’s not that. An agent is simply something that takes on a specific task for you. It might be built by you personally, tailored to your needs, or developed by a provider. Either way, it just becomes part of your seamless experience.
Emira Blomberg: Exactly. And I think as long as it’s still opt-in – where you give commands for each action – people will continue to think of it as an agent. But as you said, it’s only a matter of time before you don’t even need to ask it for everything.
And here I am again, falling into the trap of calling it “it” like it’s some kind of being – which it’s not. It’s us and the technology. But as HR, you can imagine getting your vacation lists without even asking It will become an opt-out behavior instead. Everything will keep running the way I want it to—unless I say otherwise. That’s probably how it will be. Right now, I think it’s more an active action from the human to tell the AI what they want, and we’ll end up in a situation where it’s the opposite.
Nina Rapp: Our view is that we will still set the direction, even in the world of autonomous agents. And an autonomous agent already exists today. It’s the kind that can act without you always giving it the task. For example, every time an email comes in from a customer saying RFP—request for proposal—then instead of it being taken in and processed through all the different steps, that email is automatically sent in. Generative AI and this agent look at the context: what’s being requested, what’s the format, what knowledge and information sits within our organization to respond to this—and then it drafts the reply, and finally sends it to the team: “Hey, we’ve got the request. I’ve made a draft. Go through it and see if there’s anything you want to adjust.”
So it’s already triggered automatically because you have set the direction: when an RFP comes in, follow this process, use this knowledge, and send it to these tagged participants. That already exists today. This isn’t the future. We just need to keep pointing the direction: what do you want it to do here? That’s our role. There will only be more and more of these things. I would say all the boring stuff—that’s what we hand off, and we keep the fun parts. Because that’s where we should be.
Anna Carlsson: That’s how we usually put it.
Emira Blomberg: Exactly like that. Before we started recording, I mentioned a LinkedIn post that describes how AI takes your job. And this is exactly how it starts. You ask for help—or rather, the AI suggests: “Instead of you writing an out-of-office message now that you’re going on vacation, I can reply to some of your emails while you’re away, so you don’t come back to a full inbox.” And then the user gives directions about which emails should be answered and how.
Because people hate coming back to that mountain of emails, it works great that Copilot has handled it, and you get a nice little summary of the emails you received. And then it suggests, “I can keep doing this if you want.” And it eats its way into reality, and the post ends with the person no longer having a job because it’s crept further and further in, and has also learned how to act—thanks to the person’s natural behavior in the beginning. What we helped it with ultimately became our downfall. I don’t know if you followed that.
Anna Carlsson: Yes, I followed.
Emira Blomberg: And it’s very on point—though quite dystopian.
Nina Rapp: And many people are worried about what happens when AI can do so much. What’s our role? We shouldn’t gloss over that. Transformation means people feel anxious. But this comes back to us as humans. There’s a new number from this year’s report: 77% of Swedish white-collar workers say they don’t have the time or energy to manage the work they were hired to do. Two years ago, that figure was 57%. This number keeps going up.
Personally, I’ve spent at least five or six years trying to make myself redundant—saying, “Wow, how fantastic if I’m not needed; if the organization delivers in such a way that I just keep it together. How great if everything works without me.” If I’m not needed, then I’ve done a good job. That hasn’t happened. I do other things with the time I’ve made more efficient.
And here we really have to say: let’s let go of certain things and also reflect more on purpose. Early on, when we started taking active roles in meetings and said, “I won’t attend this meeting; I’ll send Copilot instead to summarize,” we got the question: “If everyone sends Copilot and their AI assistants, then what is a meeting?” Maybe a meeting is a forum where we exchange something. I send Copilot to all meetings where I don’t have an active role—if it’s an informational meeting where I don’t need to give input live. Then I send Copilot and catch up later. But if it’s a meeting where we have an exchange, then I can’t send Copilot in my place.
And those emails you mentioned—do I want an exchange there, or is it just information that needs a reply to questions? It might be perfectly fine for AI to take that part, so we can focus on the qualitative, more value-creating, new tasks.
Emira Blomberg: Now it really becomes—everything comes to a head when you say that, because you’re raising philosophical questions: What is a meeting? What does an email contain? And my area of expertise is recruitment. We’ve seen AI-generated applications from candidates explode, and at the same pace, recruiters get lots of smart tools. So we’re in a situation where AI is screening AI. Who gets the job then? How do we ensure it was a good process and that the right candidate got the job?
Nina Rapp: That’s why I think it’s so important that we lean in so we can shape it. We can ask the right questions, we can design it, and we can qualify it. Because this train is moving. The tools exist; they’ll be used—they should be used. But we, as their users, help shape what works and what doesn’t. How do we want to draw the boundaries? That’s why I worry when I see all the reports saying Sweden is behind. It means that others are the ones redrawing those boundaries.
Anna Carlsson: Not us—with our ethics and morals and our way of seeing openness and other issues. If we’re not there to guide and decide, then yes—someone else will. We’ve perhaps leaned on the “free world,” the US, for a long time, and we can’t do that in the same way anymore. We have to be there ourselves, steering and setting direction. And everyone needs to take an active position in this.
Back to meetings—(and we’ll get to recruitment too). Meetings: how long have I and many colleagues asked, “Why do we have this meeting?” If it’s just information, there are easier ways. Maybe a leader somewhere has used meetings as their go-to technique and hasn’t learned other ways of sharing—recording short videos, writing texts, sharing in other ways.
So when this starts happening, of course there’s pushback—like, “My employees are sending their agents; I’ll just call everyone back to the office.” That can be a reaction. But we’ll also address things that weren’t necessary; where we spent lots of time we could have used to resolve a sensitive situation, help a new leader figure out how to act, or take a meeting with candidates.
But yes, that’s a huge problem—the one you mentioned—AI-generated CVs and cover letters meeting an AI screener. If you haven’t found a good model for how to work with these tools—again, lean in, make the effort, use them in the best way, not just the easiest, quickest, first idea.
Nina Rapp: Another thing—bit of a side note, but I’m hearing it more and more: “Is it cheating to work with AI?”
Anna Carlsson: Yes, exactly—that came up just yesterday, actually.
Nina Rapp: I absolutely don’t think so. But maybe we should be transparent about when AI is used and when it isn’t, and discuss these aspects. It’s the same as asking, “Is it cheating to use a computer instead of writing by hand, or a calculator instead of doing math in your head?” These are natural tools—so let’s use them, while being transparent. “I wrote this text together with AI.” Does it matter in some contexts whether it was written with or without AI? Yes, in some contexts. In others, no. But let’s work smarter and move past the “cheating with AI” idea.
There’s that old quote—can’t remember who said it—“Hire only lazy people, because lazy people will find smarter ways to get the outcomes.”
Anna Carlsson: Yes.
Nina Rapp: And I think it’s true. It doesn’t matter how many hours you spend—it’s the outcome that counts. So why not reward working smarter—doing faster work or better work in less time?
Emira Blomberg: I think again it’s because we haven’t really grounded the concept of productivity. In recruitment, you’re supposed to select the candidate best suited for the job—the one who will demonstrate the highest productivity once in the role. So what is productivity, and how should it be achieved once on the job? That’s unclear. That’s why people start talking about cheating—because it isn’t defined.
And we only realized this when we got these smart tools, because then we saw the system was broken—and it was already broken. Cover letters have never been good, except possibly in roles where writing and self-presentation are central; then they’re a good predictor. In all other contexts, the cover letter is a terrible predictor of performance. So the system was already broken. The tools just made that even more obvious.
Anna Carlsson: And now I’d like to move into some areas I prepared—much of it around AI, which is the big topic now. You have a lot of insight from what you’re seeing, since you provide so many tools to organizations through Copilot and the entire Microsoft environment—the largest environment across companies and organizations.
I remember you came and met a group in a network I run with people responsible for HR Tech, and we talked about all the services you miss if you don’t stay up to date. From the Copilot side—what functions do you think organizations should look at and make use of, the ones people often already have access to? Any thoughts there?
Nina Rapp: If we start back on the Copilot track, I want to highlight something called Copilot Chat. If you have the Office suite today—Microsoft 365, formerly Office 365—you get a free Copilot that’s enterprise-ready. It doesn’t cost anything extra, but it has the security levels needed for business use. It interacts with information on the internet and with the agents you build and publish.
So you can actually get started with secure AI for all employees—even if you haven’t bought Copilot licenses that let it talk to your emails, chats, and document systems. There are different levels, and the cost of getting started has often been a blocker. But the Copilot Chat—your entry point to the UI for AI—is available at no extra cost.
Anna Carlsson: That’s new—quite new now, right? Or maybe you don’t remember—time flies.
Nina Rapp: It’s actually been around longer—reasonably long. I’d say at least a year and a half with an enterprise-adapted version that could talk to web data. But what happened in January 2025 was that it was turned into the Copilot chat, with more capabilities to talk to agents—depending on how long you want to converse and on the timeline. Secure AI has existed—but we’ve probably been a bit too quiet about what you already get included.
Anna Carlsson: That could be the case.
Nina Rapp: So I want to put in a plug for that—alongside everything around Copilot agents. And we can mention a few other things that are being discussed a lot. One is the Viva platform you mentioned—something you talked about three and a half or four years ago.
Anna Carlsson: Four years ago.
Nina Rapp: Four years ago—with my predecessor. The Viva platform came out after the pandemic, as an answer to how we can strengthen and support people and transformation with learning, communication, and measurability. Many have leaned in and gotten started with Viva. And now, whether we’re talking AI transformation, hybrid work, or any transformation, we see it’s incredibly valuable: learning to work in new ways, the learning components, communicating the change—what we’re doing, why, and how—and then, of course, measuring it.
So, the Viva platform—and one last thing. Now I’m throwing out all my…
Anna Carlsson: Yes.
Nina Rapp: favorites here. I get to work with all the fun stuff—and that’s Places. Many organizations still struggle with hybrid work: should we force people in? We want to meet—we feel good together, we want strong bonds. On the other side, employees come in and don’t find the people they want to meet.
The Places platform, built into Teams and Outlook, lets you see when others are in, when you should go in, and mark which meetings you’ll attend in person or digitally. Quite a lot of this is available without buying an extra license—though I should be transparent that many of the goodies do require a license.
Anna Carlsson: Well, it costs to develop, too, so it’s understandable that you want to be paid for the things you build—even if it can be tough for some to invest before they’ve tried it. But there is a chance to explore a bit.
Nina Rapp: There are lots of different things, but you shouldn’t start with the technology. You should start with the need. If you have challenges with hybrid work, Places is fantastic. If you want to work with people, communication, change management—Viva is fantastic. If you want to drive new ways of working together with AI, then Copilot is the entry point—or the UI for AI—and agents for business processes.
Anna Carlsson: But do you think we should spend more time on training—teaching the organization? Because at the start we talked about that role between IT and HR, and I often see that not much has been invested in rollouts when launching new tools. People expect them to be self-explanatory. What do you see there? Have we missed something?
Nina Rapp: Training. Training. Training. It’s needed. It’s interesting—I’ve seen some put training on the HR department, some on the IT department, and some spread it across the organization with ambassadors everywhere. I don’t think there’s a single “right” way. But we need leaders who invest in this and really make sure we explain: how do we use the tools, how do we do it the right, responsible way, and what can we do? That’s also a big reason Sweden may have fallen behind—there have been “yes” camps and “no” camps. Not everyone has been invited in, and many don’t know what they can do or how. Investment in training is actually a top-priority investment—we also see that in our latest Work Trend Index report.
Anna Carlsson: Interesting. And then you have—what is it called now—you just announced something called People Skills.
Nina Rapp: Yes.
Anna Carlsson: Something like that.
Nina Rapp: An agent to map the skills and competencies you have within your organization. It enables the agent to look at Microsoft 365—what you’re working on, which tools, which skills you demonstrate through your work—and map that. You can also add competencies and build an internal library. Leaders and managers can go in and get a summary: where is my team’s competence? We also know what role descriptions exist. What are we missing, or what do we need to build toward for current and future roles? So it’s basically that—a skills agent that helps map what we have, where we’re going, and how we get there.
Anna Carlsson: That’s been discussed before. How about privacy? Everything becomes so visible. Maybe it already is, but you’re not aware until it’s aggregated. It’s like now you can find out how much time you spend on different things. Do you already know what this will look like in the skills agent? Will it go to the employee themselves with the information, or… how is it distributed? From a people focus, you usually have different levels of what’s public and what isn’t. What do you think there? Have you had time to discuss it?
Nina Rapp: I’d say fundamental personal privacy is always core to how we build our solutions. We don’t pull out sensitive information or put individuals in the spotlight and share broadly. But you and I aren’t experts on every detail of the skills agent and the exact specifics—I have a bit better handle on Viva and so on. But you will be able to curate these cards yourself, too. It absolutely uses and aggregates. In larger teams you can see certain things; some things you can see yourself and curate as well.
Anna Carlsson: So that will exist—because it’s always that “big brother is watching you” feeling. Where do you draw the line? Is the data aggregated or not? That’s super important. I find this really interesting given our challenges and major trends around new skill needs and restructuring roles. But still, there’s that balance.
Nina Rapp: The purpose is very much to see where we can strengthen people—and it’s also support for managers to support their team members. That’s what we expect from leaders: to be there to help employees be their best. It’s about visualizing data that already exists, but enabling a good discussion. And then, when we talk at a broader organizational level, it’s more anonymized. So there’s one thing for the individual, one thing for the manager-and-employee based on what they already have access to, and anonymized views for larger teams.
Emira Blomberg: There’s also another trend now—that we want to become more AI ourselves, so to speak, and not put our fate in the hands of big giants like Microsoft, for example. Is that something you hear internally? Is it a real threat—where your data is, local servers, the cloud, and so on?
Nina Rapp: For many years we’ve been investing in Europe and in Sweden with local data centers—both physical locations, technical regulations, transparency, and compliance. So this isn’t something that just happened now—it’s been a long-standing commitment, and it’s given us a good position for where we are today.
Emira Blomberg: That must be a very present question—not least with everything going on. We’re sitting here in May; lots more will have happened by the time this airs. It feels like a very current debate.
Nina Rapp: Yes—and what you can take with you is that Microsoft runs on trust. That’s our mantra. That’s how we build—with transparency, with security, with physical aspects, with who we are as a company, and so on. If we don’t have trust, we have no customers. It’s our core value.
Anna Carlsson: It’ll be exciting to follow developments and see what happens in all these areas, actually. One more thought—you’re in the thick of it, with access to all the tools and, hopefully, learning all of it. What are your favorites—favorite… what should we call it—new ways of working? Do you have something you haven’t mentioned yet?
Nina Rapp: Something I haven’t mentioned—well, a lot of my life right now is collaboration with Copilot in different ways to plan, structure, start the day, and prepare for my meetings. I’m in a fairly meeting-heavy organization and role. Also planning and catching up on everything I miss while I’m in all those meetings.
But every physical day I have that isn’t from the home office, I start the day in Places so I can ensure I have a good physical day planned. Do I have conference rooms booked for all meetings—whether I booked them or others did? Is there a good structure in place for the hybrid setup? I know it’s a bit hard to describe, but I just open the Places app right in Teams on my phone: “Here is your day, Nina. Here are all the flags on meetings that aren’t prepped for where you plan to be today. Would you like us to fix that?” And with a few taps, the whole day is sorted.
Anna Carlsson: That sounds smooth.
Nina Rapp: This goes back to Places being built for the hybrid reality. If I’m at my home office, I don’t need to check conference rooms—I have my own room. But when I’m running between customers and partners, or I’m at our office, it adapts—and it’s like an AI built into Teams that fits hybrid work. We don’t call it an agent; we call it Places. But you could definitely say there’s a lot of AI built into it.
Anna Carlsson: I’m thinking this: we’re getting close to the end, and I always finish by asking for a bit of advice—the guest gets to give some advice. So, for our listeners—mainly HR—what advice would you like to send them about what to do now?
Nina Rapp: I’d really like to encourage everyone to get in the driver’s seat. And now I’m talking about the AI transformation here. Get in the driver’s seat. It’s a human transformation—about people and our ways of working. The best way to take the driver’s seat is to test, get started, tinker, and play. And don’t forget to also play with your digital colleagues—to get to know them so you can start making a plan: how will this affect things, how can you help lead the rest of the organization?
Get in the driver’s seat and think about what the ratio will be going forward between digital colleagues and human colleagues. We see that we’ll address those pressures—77% of Swedish white-collar workers say they can’t keep up—by bringing in digital labor. How many will that be? How should we train and talk about this transformation? Also figure out: should each person have three agents, thirty, or three hundred? There aren’t clear answers, but I think we need to discuss it from a human perspective right now.
And try to sign up for a prompt-athon. A prompt-athon is like an innovation hackathon in the generative AI era. Come, look over business challenges, and see where we can apply generative AI. At Microsoft, we have some prompt-athons you can sign up for; our partners have them too. You can also run one in-house—there’s open material you can download and do this with your organization: what challenges do we have, how do we work? Not as a side issue—let’s apply it to our unique needs.
Anna Carlsson: Those are super tips. Doing it in-house is exactly what I think—though you might need someone to take the first steps externally to guide the rest.
Nina Rapp: Exactly.
Anna Carlsson: So that sounds great. That’s the kind of thing I usually recommend too—that you sit down together. I don’t call it a prompt-athon, but that’s exactly what you need: to learn and understand how to work with your new digital colleagues—or whatever we’re going to call them.
Emira Blomberg: Yes, exactly—I’m sitting here squirming.
Anna Carlsson: Me too, a little—but we’ll have to book another session with you in a few years. Or maybe sooner.
Nina Rapp: Time moves faster now.
Anna Carlsson: It does—so we can’t wait four years until next time to discuss where we are. Thank you so much for coming and sharing.
Emira Blomberg: Truly.
Nina Rapp: Thank you for having me!
Emira Blomberg: Yes—many thanks! Super exciting.
Nina Rapp: And thanks to everyone listening.
