In this week's episode of HR Digitalization Podcast, Anna Carlsson and Emira Blomberg, together with guest Thomas Eklöf from AI for HR, discuss how generative AI is shaping the workplace and what challenges and opportunities this technology brings to the HR industry. The conversation revolves around the rapid advancement of AI, the struggle to keep up with its pace, and how HR can and should adapt to the ongoing digital transformation.
The discussion touches on the rapid development of AI and its implications, where the guests reflect on the technology’s unique characteristics and the need for individual adaptation. The role of HR in AI adoption is crucial, and Thomas Eklöf emphasizes the importance of HR supporting the organization through the transition while also developing its own digital competence.
Challenges and resistance to AI are explored, particularly the fear of change, lack of time, and absence of strategic decisions. A key topic is how AI can transform HR work by streamlining processes such as recruitment, analysis, and communication. The episode concludes with concrete recommendations on how HR can take an active role in AI adoption, such as implementing scheduled "AI races" and fostering a culture of experimentation and knowledge sharing.
By engaging with AI development, HR can create more efficient and innovative work processes. So how can your organization take the next step? Tune in to the episode and get inspired by the future of HR!
Note: This episode is in Swedish. A translated transcript is available below.
Transcription:
Anna Carlsson: Welcome to the HR Digitalization Podcast! Thomas.
Thomas Eklöf: Thank you!
Anna Carlsson: There is so much happening in the AI field. It’s almost hard to grasp, I feel. Here we are now—it's February. I think this episode will be released in a few weeks after we record it. But it feels like I can’t really keep up with the pace. I don’t think anyone else can either. Or? And Emira is here. What do you say about that? Are you keeping up?
Emira Blomberg: No, but I don’t even know if I’m keeping up. That’s the challenge—how do you know when you are keeping up or not?
Thomas Eklöf: I can say that I am not keeping up. And I work almost full-time with this just to try to keep up. But it’s almost impossible. So much is happening all the time—not just in terms of new releases, but also a lot of discussion, expectations, and so many things at once. Filtering through all of that is difficult, even for me. It feels like almost no one is keeping up.
Emira Blomberg: Then I think we need a new definition of "keeping up." It’s not about staying updated with every single news release all the time—that's impossible, even for an AI expert like you. Instead, we probably need to define keeping up in a different way.
Thomas Eklöf: Yes, I was thinking about that earlier too. The connection to HR is that the most important thing for us isn’t the latest tools or the newest update of some large language model, but rather understanding what this actually is. Understanding how we should use it. Going back to basics instead of getting caught up in the constant hype. In a way, it's like a war.
Anna Carlsson: You mean a kind of balance of terror?
Thomas Eklöf: In some way, yes. Now that China is also involved, it’s an ongoing race to always be the best and at the forefront. So much has happened just this week that it's really hard to keep up.
Anna Carlsson: So now we take a snapshot in time—February 10, 2025—and gain some perspective. That’s what we plan to do today. But first, you should introduce yourself. Thomas, you’re our guest today.
Thomas Eklöf: Right. My name is Thomas, and I come from an HR background. I’ve worked in HR for 15 years, originally in recruitment, just like you, Emira. But in the last ten years, I’ve worked broadly within HR in all sorts of roles—everything from specialist roles to HR manager. Mostly as a consultant coming in from the outside to help organizations. I also wrote a book called Innovative Recruitment, which was published in 2018. That’s when my interest in AI started to take shape, because we were already writing about exciting tools back then, including one that was big at the time, called Maja, which was later acquired by one of the major players.
Anna Carlsson: Right.
Thomas Eklöf: That was long before ChatGPT. AI wasn’t hyped or big at that time. So my interest in AI has followed and developed over time.
Emira Blomberg: Does the book’s title still hold up today?
Thomas Eklöf: Innovative Recruitment? Considering the state of the recruitment market, I think it still holds up. If you look at how we work with our methods in Sweden as a whole, the book is still modern, at least in terms of approach. Nils Ahlén and I challenge the traditional way of doing things and promote a more adaptable recruitment process. So I think it still holds up—but maybe not as "innovative" anymore.
Anna Carlsson: That’s why I have a podcast instead of writing a book—so I can be more flexible along the way. But a book does give you a different kind of status.
Thomas Eklöf: Yes. Just to wrap that up—AI became a major topic, and when ChatGPT truly arrived and changed the playing field, I felt it was time to dive even deeper into a topic I already found exciting. Since then, I have been running AI for HR, offering training, courses, and lectures, mainly for HR. Over the last six months, I have expanded to reach more leaders and management teams.
Anna Carlsson: Really exciting to talk about this topic. Should we call it a global event? And we should also mention that you and I have worked together on a few things. We've done Friday Live, and you and Emira have done sessions when I wasn't there. So we’ve had Friday morning sessions live on LinkedIn. Right now, we’re not doing that—I can’t fit it into my schedule. LinkedIn also changed some of its rules. And we are co-teaching a course where you complement my training in HR digitalization, which also has a significant AI component. It's interesting to discuss today—what does it really take for AI to work in the future of HR? But I wonder, where should we start with this topic? Where are we right now? I was listening to Josh Bersin—he talks about Super Humans. I had several discussions when I was at the HR Directors' Summit last week. How should we leverage AI, and what will happen to us as individuals moving forward? And how fast will this happen? What are your thoughts?
Thomas Eklöf: I think about this a lot. I don’t think the biggest challenge is the technology itself. The real challenge is us—our ability to relearn. AI is a tool. But it’s a tool that is very different from previous innovations, meaning we have much greater opportunities to do things differently thanks to it. I still think we are standing still. I could list studies that show this. The most recent one, from January, was from BCG, which showed the same trend—that Sweden and the Nordic countries are falling behind, or rather, stagnating. Development isn’t happening as rapidly here as in the rest of Europe, the US, or other parts of the world. Their numbers show that AI usage doubled from 2023 to 2024 globally, while Sweden remained at roughly the same levels.
There are probably many reasons for this, but I think our main challenge is making sense of AI. Some people might think it’s good to take it slow, stay put, and wait to see what happens. It’s a balance—you can wait a week, and suddenly, a new model arrives that changes everything. But at the same time, you have to jump in at some point to start understanding and navigating this. I often compare it to laying railway tracks while riding on the train. We don’t know exactly where we’ll end up, but if we just stand on the platform, we definitely won’t see where it’s heading.
Anna Carlsson: You have to make time.
Thomas Eklöf: Yes, I was also a personnel manager and talked about this. One of my final tips is that we need to free up time to enable this shift, and I think we are stuck. As you said, Emira, we are stuck in the operational day-to-day tasks and don't have time to look up, and that's a strategic decision. It's a decision for us as an organization. What should we deprioritize if we want to invest in this?
Emira Blomberg: Ideally, we should do this: anyone who has worked in a sales organization knows about those mornings or afternoons when you block your calendar for a joint "call race." Everyone thinks it's boring, exhausting, and tough to cold call. But you need it to move forward.
Anna Carlsson: And for those who don't know what that is, it's when you call potential new customers.
Emira Blomberg: Exactly.
Anna Carlsson: Picking up the phone and calling an unknown person. You do it as a group.
Emira Blomberg: Because that way, you get some momentum. Maybe you even set goals, like the person who books the most meetings in those two hours wins a nice prize. You have live updates, and it turns into an event. If it's in the afternoon, maybe you finish with some bubbly or something fun. Why not do the same here? Every HR department out there should have an "AI race." Block two hours on a Friday morning, for example, and then reflect—what did you learn?
Anna Carlsson: What did I do? How did I use AI? And then take action. It could start with an inspiration session, or you could even ask ChatGPT for inspiration and then work together.
Emira Blomberg: Exactly.
Anna Carlsson: And encourage each other.
Thomas Eklöf: And I think that's a great approach. You have to start playing with it, having fun with it, to make it enjoyable. But also, you need to vary your approach and explore new ways of thinking. I often ask the question: "What do you see your role looking like in five years?" Imagine that up to 90% of tasks disappear—what happens to our roles then? Most people just see minor efficiency improvements, but it can completely change the playing field for many HR roles. I believe the transformation will be much bigger. But it also requires a shift in mindset. We have to rethink how we work, which is a significant challenge. We have to start with efficiency improvements now, but as we integrate generative AI more and more, we realize—wow, there's so much potential here. But if we never start and only dabble on the side, we won’t gain these new insights. That’s what I mean—you can’t stay on the platform waiting while stuck in the operational wheel. You need to make a strategic decision.
Anna Carlsson: And this isn't just about AI. I'm passionate about structuring other areas and using different tools for different tasks. Nowadays, it's not enough to say, "We have one system that takes care of that." You constantly need to look ahead. We've discussed this in previous episodes—the importance of dedicating time to innovation. We need to invest in the future now because it’s only becoming more critical. If you don’t take the time to do things differently, whether it's generative AI or something else, you’ll miss out. It enhances personal efficiency and benefits other areas as well. We have to look up and allocate time for this, and it has to be acceptable to do so. This isn’t just about HR.
Thomas Eklöf: No, I think it applies to all functions. We need to make decisions and look into the future to be prepared. I believe many don’t do this. If you don’t figure out how to adapt, external forces will dictate the changes. Someone will find a way to revolutionize recruitment processes or other functions, and suddenly, you’ll be caught off guard, realizing, "Oh no, we have to do this too." And then, you might have to lay people off because you weren’t prepared for the transition. You didn’t start reskilling or upskilling in time, and suddenly, you’re left behind. We need to stay one step ahead.
Anna Carlsson: Who typically attends your training sessions?
Thomas Eklöf: That’s an interesting question. You mentioned earlier that people often say they lack examples. One of the biggest challenges in training is finding the right level. It doesn’t matter if I’m hosting a webinar or a specialized session for an HR team—there are always vast differences in knowledge levels. Some have barely tried ChatGPT, while others are daily power users or "AI natives," as some call them. Finding the right balance is difficult. More and more people are using AI, but very few are true AI natives—those who use it daily and see how it enhances their abilities, just like you do. AI doesn’t just make you faster—it makes you better.
Anna Carlsson: It makes me better.
Thomas Eklöf: And that’s the key. Many still see AI purely as automation. They think of RPA (Robotic Process Automation)—digitally automating tasks. They focus on small efficiency improvements, removing manual work. But that’s just one part. The real transformation happens when AI enhances our capabilities and changes how we think and work. That takes time to grasp and integrate into workflows.
Anna Carlsson: Changing the way we work—how many times do you need to do something differently before it sticks?
Thomas Eklöf: Good question.
Emira Blomberg: I think about how leadership philosophies have evolved. We moved from a directive approach to a more coaching leadership style. But how many managers are still stuck in the old way? How many specialists get promoted to managerial roles when they shouldn’t? That slows down cultural transformation in organizations. Another key takeaway is that new leaders must have a perspective on AI and their development in relation to it. At the very least, they must be open to it. These skills need to be integrated now. Some organizations will lag for so long, which will have devastating consequences. There’s a saying: "The future is already here—it’s just not evenly distributed." Some are far ahead, while others are still way behind.
Thomas Eklöf: Absolutely. If you look at societal change over time, there are always multiple speeds of transformation. I read a Wall Street Journal article about "AI-native companies"—businesses born in the AI era that use AI-first strategies versus traditional companies trying to adapt. The difference is massive. AI-native companies are more agile and ready for new ways of working, while legacy organizations struggle with old infrastructures, both system-wise and culturally. Some cling to "this is how we’ve always done it" and lack a beginner’s mindset. Many try AI once, decide it doesn’t work, and give up. They don’t realize that the real efficiency gains come after sustained effort and learning. Change leadership will be crucial—it’s a cultural shift that requires behavioral adaptation over time.
Anna Carlsson: What role should HR play in this transformation? It might hit HR harder since digitalization isn’t naturally embedded in the role. That makes it tougher to transition to something so different from traditional HR tasks. Should HR take the lead, or is that too stressful?
Thomas Eklöf: You’re right. A study (about a year old) showed that only 9% of HR professionals felt digitally prepared for this future. That means just one in ten is ready. Helena Tronny, CEO of one of this year’s top companies, said there’s "AI or digital shame"—a reluctance to admit incompetence in digital tools. That prevents people from opening up and being vulnerable. HR needs to step up, even if they aren’t AI experts. They understand culture, change management, and human challenges. That’s where HR’s core competency lies. However, the mistake many organizations make is waiting for IT to lead. IT should handle security and tool selection, but HR must drive the transformation.
Anna Carlsson: There’s a lot on HR’s plate right now. I got a reflection from a previous episode about pay transparency—we don’t discuss certain topics, like political beliefs, religion… and now, digital incompetence.
Emira Blomberg: Exactly.
Anna Carlsson: But we need to.
Emira Blomberg: Maybe now is the time to separate compliance HR from transformational HR. Let compliance HR handle legal and regulatory tasks, while another HR function leads behavioral and organizational transformation.
Thomas Eklöf: Absolutely. Also, the new EU AI Act now requires companies to ensure employees using AI tools have basic AI literacy. That’s a compliance requirement. Who takes responsibility for that? Probably HR.
Emira Blomberg: There are—I'll use my former employer as an example again. I worked a bit with change management during that time, and there are four key factors for successful change management. The first is that there must be a strong "Why." You have to paint a vision of why we need to do this. The second is that you need to create a sense of urgency. COVID is a perfect example of that. Talk about a sense of urgency—suddenly, from one day to the next, no one could go out, no one could meet, and so on. I think we need to create that. We have to force it.
Then, it has to be easy to do the right thing. And finally, it has to be cast in stone—it has to stick. That means it should be easy to do the right thing. You have to enable people to make the right choices easily, but also, there should be consequences when they don’t follow through. Those four things are key.
Thomas Eklöf: And this—sorry.
Anna Carlsson: I was thinking about the first point, the "Why." It has to be a positive "Why," for me. So that I understand the reason. Not that it's about avoiding risks, but rather about opportunities—what you will be able to do. That’s also an important psychological aspect of change management, of transformation work. And I think this is something we often get caught up in—we jump straight to step two, the sense of urgency. But we must—
Thomas Eklöf: That’s why, when rolling things out, you have to find use cases for the specific function or department. The general ones aren’t interesting for most people because they just seem abstract. Instead, you have to get to the core of what people do in their daily work.
I think I was listening to a company called Tilda, which is an AI-first company running a learning platform and a platform for workshops and behavioral change. There, Jocke Jardeberg, who works with AI at Volvo, talked about how they worked with the Executive Assistant team—assistants for senior positions at Volvo. They found tasks that were very manual, slow processes that had been done the same way for 15–20 years. And suddenly, in just one workshop, they managed to break this pattern—they could just copy-paste from ChatGPT and transform an entire process. They had been doing the same boring copy-pasting between documents, and suddenly, they didn’t have to anymore.
For them, it was a revelation: "Wow, it’s such a relief to get rid of these tedious tasks." But it was specific to their situation. That’s where you have to start. That’s when you really get that "Wow, look how much we can do differently. Look how many boring tasks we might no longer have to do."
Anna Carlsson: But if we go back to the issue of regulations, I know that one of the things we discuss in HR is the importance of doing things the right way. But could that also lead to being overly cautious? I mean, AI literacy—the level of competence in using AI—is one aspect. But there are also other concerns, like being afraid of using the wrong tools. It can become an obstacle. This isn’t something HR can handle in a silo; as an organization, we need clear guidelines. "These are the tools you can use." But why isn’t that happening?
Thomas Eklöf: I think it’s mostly a lack of knowledge—that people don’t take the time to learn. When I talk about a playbook, I think it needs to be tailored for each department. Of course, there are general models like ChatGPT, which you can choose regardless of whether it's OpenAI, Google, or another provider.
In marketing, there are tons of different tools for generating images and videos. In HR, there are many tools—big players integrating various services, from recruitment companies to learning platforms. Each function has an array of tools to choose from. So, you need an overarching framework: "These are our main tools." But you can’t create a one-size-fits-all solution—it has to be tailored to each department’s needs. And then it becomes a financial and integration question that needs to be figured out as well.
Emira Blomberg: Exactly. I also think that people haven’t tapped into their curiosity.
Last weekend, I was at Yoga Games, and a yoga teacher there said, "You need to be driven by purpose, not by pressure." That really stuck with me—it applies to everything we do. Having a purpose and a goal in what you do instead of just operating under pressure makes things more meaningful.
It’s like going to the gym. You know you need to start exercising because you're over 40 and your muscles are deteriorating. So, you go there, and there are all these machines, and you have no idea how to use them. You feel like you’ll look ridiculous the first time you try.
You have a few options: You can read up beforehand—there’s a lot of information available, and you can prepare both mentally and practically. Or you can ask the people already there: "How does this machine work? What weight should I use? Oh, okay, I should sit straighter." And then, of course, every machine has instructions.
You can also just go there and start. The important thing is deciding to go and finding a personal reason—"No, I don’t have to train, but I want to stay healthy. I want to be an energetic grandmother for my grandchildren." That’s where motivation comes from.
Thomas Eklöf: I think—I read something from Garry Kasparov, the chess grandmaster who was one of the first to be defeated by AI. That was in, I believe, 1997.
Anna Carlsson: Kasparov.
Thomas Eklöf: Kasparov, exactly. I need to practice the Russian pronunciation.
Emira Blomberg: You need to use the right hand gestures, too.
Thomas Eklöf: Yes, exactly. Well, he was defeated when he lost to an AI machine. And it was IBM, the company you worked for, that had its Watson which defeated him. It was a huge global news story when this broke, that now AI was smarter than a chess champion, and it was a really big deal. Since then, the chess world has changed, where AI has become like an enhancer, where AI and humans work together. His insights later became a book. There's a really good TED Talk that I highly recommend if you search for Kasparov. And his insight was somewhere around that he made a reference to a competition where there were two average players, and they had access to AI tools against the masters with the best AI engines. But these average players managed to defeat the best ones because they used the AI tools in the way they were meant to. They optimized the AI services to get a better result. The takeaway from this is that there will be so many AI tools, like Excel. There's so much we can do, but if we don't understand how to harness the power of Excel, or if we don’t know how to unlock the power of ChatGPT, it will still fall flat. So, we need to start learning these nuances of what’s out there and start understanding which tools to use for which situations. It's a long journey to learn this and understand it. So, we shouldn’t push a "one size fits all" approach. Now we roll out ChatGPT for all our employees. Or now we’re rolling out Co-pilot, and I’m sure most companies will do that without training, just expecting to see all the efficiency gains Microsoft promises in their studies. Well, that’s not going to happen. We need to give the keys and the knowledge and understanding of when to use it. So, it’s about education. Competence is more important than which tool we choose.
Emira Blomberg: But I also think it’s up to you two, the ones holding the training. You have to find this balanced approach that helps people understand what to focus on and how to divide their work. Because, as we started saying, no one is keeping up. I think it’s this big monster you see ahead of you, or the big mountain to climb, when in fact, it’s more like an iPhone. We’ve heard that example before. Do you use all the functionality on your iPhone? No, you don’t. And also, do you know how every cell in your body works or how digestion works in detail? No, you don’t. But you know you need to eat vegetables because it’s good for you. And I think these simple truths are what we need to find and present to people so it becomes manageable. And that’s where we need to go, don’t you think?
Thomas Eklöf: I think it’s both. I think we need to have general knowledge of what it is that we’re doing and what its function is. Then I think about my neighbor. He’s a director, and he’s started working more and more with AI in film production. He describes that he uses 5 to 10 different tools because one is not good at doing everything, so he has to jump between different tools to get the best end result. So, I think we’ll see even more specialized roles in the future, and even in HR, we’ll rely more and more on different services and tools. Because they’ll do the job faster and better for us, but we’ll be like conductors putting everything together. That’s true for some specialized roles. Then, if you’re more of a generalist, like an HR manager or something else, you need to have that general understanding, that we need these balanced approaches to make it all come together.
Emira Blomberg: Yes, because a few experts don’t really help anyone. And as suppliers of a product that helps recruiters, we sometimes—though not often—get criticized for our product not being perfect, and then it’s like this: we’ve always had a choice. Either we can develop the perfect product that’s highly predictive, or we can make it easy to do the right thing. And the thing is, if we lower the bar a bit and move away from perfectionism, we get it out to the broader public, and then it becomes possible for the change to happen. And I think that’s where, I believe it was you, Anna, who said this: that making mistakes, we’re going to make mistakes. We have to make mistakes, and also, as you said, Thomas, I think a few specialists will emerge, but most people will need to be able to handle these tools, otherwise, change will never happen.
Thomas Eklöf: I think it’s a couple of things, like intelligent failure. Emundsson, who wrote a book on it. I think we need to see that and be ready for failure and do it often, a little like Facebook. What do they say? Fail fast or something like that. I think there’s a point to that, because we have to test often and break early to realize when we’re on the wrong track and start over or test a new angle. We can’t get too focused on a big investment, like a huge rollout, like the IT system in the Västra Götaland region that didn’t go so well. We can’t get too locked into something big; we need to be more flexible. I think we have to be willing to test and fail more often, but we also need to have a plan in place. Back to what we talked about before, purpose. I think this is a challenge we’ve seen because studies show that AI projects have moved from wanting to get started with AI to many rolling it out fully. And now, many have started with pilot studies in AI, and here we’ve seen that 80% of them fail, according to a study. Imagine that, eight out of ten or four out of five fail in these projects. Some organizations might feel like, “No, this is too expensive,” and then they give up. It doesn’t work. But I think what happened is they’ve focused on the technology first, not on the needs. They’ve gotten excited about the cool technology and thought, "We have to be part of the AI wave." I think that’s better than doing nothing, but they’ve maybe skipped the needs assessment, which is so crucial, especially in design thinking processes, where you really get stuck on what the problems are. Then AI can be a way to solve the problem, but it doesn’t have to be the best way.
Anna Carlsson: Isn’t it easy now to think that AI is going to solve all problems?
Thomas Eklöf: Exactly, it’s like people think AI is an oracle that can solve everything. And I think especially for leaders, they get this image when they see lots of numbers and efficiency gains, and they think, "Now, here it is, the holy grail, AI will solve all our problems." But no, there are many issues within it that need solving, and it’s not certain that AI is the solution. And especially, I think a lot of people don’t understand the differences within AI. AI has so many different techniques, and the only one people are talking about is generative AI, generating new input. But if you talk about predictive analysis or predictive validity, I think we should mainly use services to work predictively. Using historical data to predict future outcomes. That’s not generative AI, it’s more traditional machine learning. Many of the processes and automations are about doing such things, not just thinking that ChatGPT is the answer to everything.
Emira Blomberg: That brings us back to your section with him, whose name I always forget, the one who talks about People Analytics and the different levels of analysis. Yes, exactly.
Anna Carlsson: I think we’re nearing the end of our time. One thing I’d like to send out from my perspective is: We haven’t really talked about solutions now, vendor solutions, but more about how we approach this vast area. And it’s the same with all other fields. Now we’re talking about the fact that there are different kinds of AI. There’s a vendor for everything right now. It’s about our own mindset, for what we’re capable of understanding is possible with digital technology. The data, the way we can analyze it, and how we’ve seen that we can apply different AI techniques to our world. It’s all there. Whatever you want, it’s available.
Thomas Eklöf: Yes, I think so. What I see as trends for HR and management is that I’ve also seen a lot of demos from different companies. And it feels like more and more are trying to become a one-stop solution, both for small and medium-sized businesses, as well as the big ones. They’ve always had the big ones, but I think what you need to find is that balance. You need to have that comprehensive solution, but at the same time have the freedom to start testing. One of the advantages of AI tools is that they’re relatively cheap to test even on a smaller scale. For example, Tilde, which I mentioned earlier. You can test it at a very low cost and start exploring. Can this complement our process? Can it help us in any way? But then I think we also need to start using generative AI so we don’t forget that most AI tools coming now are successors to those big language models. Most people use OpenAI or another model to train their own solution. If I can learn enough to use it for my purposes, then I don’t need to buy any of these tools. So, if I can use the core model really advanced, I can get so much more at no extra cost. But it does require that you really take the time to learn it.
Anna Carlsson: So, do you have any concrete advice to give to the listeners at this time we’re in?
Thomas Eklöf: Concrete advice: free up time. And if you feel you can’t make the decision strategically, then I think you should start leading by example. Start small, test things out, and talk to your closest colleagues in HR teams. Ask, “What are you doing? Should we sit down for our weekly meeting and talk a bit about what we’re doing?” Find an hour to start experimenting. Start small and get help if needed. There’s so much information out there, and free courses within HR, as you mentioned, Emira, from people like Sourcing Alliance. That’s one of my best tips: start now, with no shame. Then, talk about what works. Share knowledge and experience. Maybe AI or digitalization won't solve everything, but it will definitely change everything. And that’s enough. It will change everything.
Anna Carlsson: That’s what we’re coming back to.
Thomas Eklöf: Yes, I think so.
Anna Carlsson: Saying yes and saying no.
Thomas Eklöf: Yes, exactly. Also choosing to opt out. Absolutely.
Anna Carlsson: Thank you so much for coming here and discussing this topic, which I’m sure we can revisit many times in the future.
Emira Blomberg: Fun, fun conversation.
Anna Carlsson: Thank you for today.
Thomas Eklöf: Thank you.
Thomas Eklöf: Thank you.
