Good morning everybody, and welcome to Finance 4.0. news. I hope you're all well and excited to spend the next half an hour 45 minutes together diving into what does the future hold for finance. AI is here to stay, adoption is increasing and leaders are wondering how do we go about it and these are some of the themes we're going to look into today, Anders. Yes and today we go beyond the headlines. We speak with people on the front line, people who are in this on a daily basis just like all of you because we're on this journey together. People that understand what it takes to experiment and create a safe space to do that. People that understand how to go from experimentation to scaling AI and create enterprise impact. And people who've tried transformations over and over and over again and knows what works and also what doesn't. So it's a great lineup that we have for you today. Indeed. But let's start just by setting the scene, Anders. And what do we mean by finance 4.0? Is it really just about the new technology that we're seeing? Is it just about AI? Or is there something more about it? Is it about leadership? About ways of working? About actually people finding new and better ways of doing things? So let's set the scene. Yeah. And really it's about all of that. But if you search history and look at sources of finance 4.0, of course it draws on the analogy to industry 4.0. We're really connecting industry through automation and data and everything that we know. But the early sources of finance 4.0 was really all about technology, right? Just like industry 4.0. But when we published a perspective on this, welcome to finance function 4.0, back in 2021, we have a different perspective. It was even not before AI, but before the GPTs that we know today. So it was definitely with a different lens on technology. But we knew technology was there. We knew AI was going to come. But what was the difference maker? It was how we as people, as humans, interact with it. And so that was the different perspective. And that's why it's about more than just technology. It's about people. It's about the operating model. It's about process and technology as well. So it's about a lot more. And that's also why we said that finance 4.0 is driven by people and enabled by technology. Yeah. And oh boy, how things have changed since 2021. I don't think any of us expected so much disruption driven by technology. And the transformation that we're looking into now, AI driven is probably one of the most disruptives we've seen in recent history. And when we look at finance, AI has really the potential of putting finance on a whole new level and enabling finance functions to be even more close to the business and enabling finance leaders to truly be there in the front line and driving the future together with their CEOs. So AI is here, but are finance functions truly changing? Yeah, I think that's the real question, right? Because we speak with a lot of finance leaders every single day. And while all of them are on this journey, no one has found the answer, if of course the answer even exists. So there's a lot still to explore here, which takes us to our first story, the adoption gap between AI being available and actually being adopted in finance. Because many finance teams have access to AI today, whether it's your co-pilot or other GPT, whether it's some sort of assistance or agents that you have built either outside your systems or inside your systems or something else. We all have some sort of access to AI. But individual experimentation does not automatically redesign work or change everything in the short term. So the immediate challenge is uncertainty about what AI means for us and how we're going to use it in our daily work. And what does it take for us to really adopt it? So, Victoria, you sat down with someone who is in this on a daily basis and I believe maybe have found some answers at least. So, you know, can you give us a little bit of an introduction before we hear from the man himself? Yes. So I had the pleasure of sitting down with Christopher Møllenbach, CFO of Danica Pension and the former finance leader in Danske Bank. So a man with a wealth of experience when it comes to finance, finance leadership. And he is currently driving his own transformation driven by AI and the new technology. He is a huge fan of AI and he's a huge fan of technology, not only at work but also in his personal life. And when I sat down with him and I asked him, he said, he said, you know, what is making your finance transformation? AI driven succeed. And you won't imagine the first thing he said, right? Christopher being very finance in a very traditional industry. And yet the first thing he said to me said, Victoria, you need psychological safety. And from that moment, then our conversation took off. And here we can hear a snippet of it. So tell me what is it that you're doing? What are the levers that you think are working in your finance transformation? Well, I think first of all, the key thing in such a transformation is getting the buy-in from from your employees, getting them on board with the journey. And you know, with any transformation, you will have a group of employees who are naturally excited. And this is obviously true for AI. There's going to be a group of employees that are naturally excited and who want the transformation together with you. But then you're going to have many employees that are going to be ambivalent. And you're also going to have employees that are fairly uncertain about what does this mean for them, who are not really comfortable with the uncertainty that such a big transformation brings. So for me, this is going to be one of the most interesting things to do is get the whole organization engaged. And and then also the most important lever in delivering an AI driven transformation. What is your role in this transformation? I think my role is obviously to be a role model. I'm personally very excited about AI. I love tech, I love IT and I love the possibilities it brings, but then also delivering a vision, which I think is much harder in this transformation, the previous transformations, because normally when you have a transformation, you have a clear goal of where you want to go. This time, you know, things are going to change, but it's difficult to articulate what exactly the future is like. And then finally, and I think this is maybe the hardest thing is going back to the getting people on board, is also getting people comfortable with taking risks, changing the way they do things and and feeling safe, experimenting when working in new ways. Because I think a lot of the AI transformation is working in a different way than we used to work. And that takes courage. And as a leader, providing the space for you for your team to have that courage, I think, is one of the most important things. What are you doing practically to create this safety, this psychological safety in your organization? Yeah, I think one of the one of the most successful things we've had in in Danica is a concept of AI sprints, where we've taken departments in in groups of six to eight to 10 people at a time, together with AI coaches for half or full day offsites where they they they come together and they experiment together in solving problems, finding new ways of doing things using AI tooling, using relatively standard AI tooling. So it's not the most advanced things we do, but it is using co-pilot Danske GPT in new ways and and just experiment together, sharing and then carrying that into the day to day world where we've created forums for sharing and experimenting together. So getting that familiarity up through these types of sprints, I think, has been the most effective thing we've done so far. I think that Anna's, Christophan and I, we ended up talking for over 40 minutes, so we only sharing small snippets of it. We're going to share the full interview in the link at the end, at the end of this session. But there was a lot of wisdom and a lot of real tangible experiences that that Christophan was was sharing with us. So it was really, really interesting speaking with him. And again, to reiterate two things that I took away, first of all, for him, this AI driven transformation is somewhat different from other transformations that we've seen in the past, simply because the end game is somewhat unknown. We don't really see what this is taking us. So his role as a leader is to show small glimpse of the future, while making sure that his organization feels comfortable and safe in taking on this journey together with him. And this psychological safety is about also creating the softer foundation with skills and upskilling and experimentation. It's also about the hard foundation in organization around the processes, data and governance. And he speaks into this also later on in the interview. And I think it was just amazing to see a finance leader sitting there so comfortable, so calm, talking about one of the biggest transformations and changes that we will see, not just in finance, but in society in general. And just, you know, he's in it, he feels it, and he's moving his team forward. And I think that's, you know, he talked about being a role model. And I think he's not just a role model for his team, he's a role model for all of us. If we can draw on that calmness that Christopher has, I think we will be in a better place of driving this transformation for going towards finance 4.0. But, you know, the first barrier is then not just access to technology. It's actually creating the foundation for people to feel safe, to use it, to experiment, and to get going, really. Yes. But, you know, we also have to be honest, even if like hundreds of people, even thousands of people in your organization start to experiment with AI, it's probably not going to create that enterprise transformation, create that enterprise impact that we're really looking for. So, you know, how do we prevent this from just becoming hundreds of disconnected experiments? I think that's really taking us into our next story. Absolutely. So, we really need to move from experimentation to impact at an enterprise level. And so, yes, there is this broad range of tools that we can go off and play with, and we need to feel comfortable enough to do so, no doubt. And yet, we need to be able to make choices. How do we bring all this technology and different tools together in a way that is coherent with our strategy? How do we make sure that there is impact? So, it is bottom-up experimentation, but there needs to be that top-down leadership that really pulls all this AI fever together aligned in one direction. And we actually spoke with a gentleman who has one of the coolest and newest titles in the C-suite. And he told us what he is doing from an enterprise point of view in order to drive AI that actually creates impact. Yeah. So, we spoke with Markus Kede, Chief AI Officer at Lundbeck. And he's had roles in both finance and the business. So, he has great perspectives on, you know, how to drive a transformation, how to create impact. And he spoke exactly about this that you mentioned, Victoria, that how the bottom-up experimentation that we heard from Christopher meets the top-down direction setting to create this enterprise impact. So, let's hear what Markus had to say. Many companies right now are allowing access to AI tools in different ways. And I would argue this is more distribution and not so much really driving transformation. So, that next step, you know, beyond talking about governance, beyond talking about performance systems, but really transforming the company to understand what it is we sit with now. Understand how this might impact on a functional, on an enterprise level and start working with it. What things are you doing in order to really mitigate that and making sure that you're not just distributing, but you're actually transforming your company? Yeah. I think it goes two ways, both from a bottom-up, which I think is what you're describing in distributing the tools and the opportunities for all our employees to understand what AI is and how to work with it. It's important. At the same time, as you have a top-down where you focus your AI strategy in terms of understanding what is your company strategy and how can AI be an enabler for you achieving the focus you have in your company strategy and allocating, prioritizing, focusing on what are the most important areas and opportunities for you as a company and then merging the two. Because if you only do the bottom-up, you have tons of mushrooming and tons of people doing great stuff, but very fragmented. If you only do the top-down, you're spending your time in the most important areas and you might be transforming the company, but you don't have employees that understand how to operate in that new future. And that's why I think it's so important to have both a top-down that has the right priorities for the company and a bottom-up where you have curiosity and experimentation in your company across all of your employees that understands how to operate in that new future. I think it's really important to have the framing of understanding your company strategy and how your AI strategy is an enabler of your company strategy. AI strategy is not a standalone thing we try to achieve. It's really, as I view it and as we view it in Lundbeck, an accelerator of our, in our case, our focused innovator strategy. And making that connection to say, what is most important? Where do we believe AI has the highest opportunity to accelerate our strategy? And we've done it in terms of defining six business questions where we believe AI has the highest opportunity to drive value. And then anchoring that in the business, identifying, okay, how can we then initiate strategic bets and projects initiatives that delivers on those business questions? And that's where the hard part comes in. And I think setting a strategy is hard and making sure that you have people around the organization being involved in it. So you have accountability in the organization, but then coming to the actual work and how you're then looking at reimagining, redefining the way you operate in order to deliver on those business questions are really hard and difficult. And as we talked about that differentiation between an activity and an impact is so crucial. If you embed an AI tool in a workflow and you have the same outcome, then you've done an activity. If you can explain how we're able to, through this workflow, deliver more assets or service more patients or have a substantial different outcome, then you have an impact. You've made an activity that drove an impact. And that mindset, I think, is crucial. I really like what Margaret said about AI strategy not being something on its own, right? It has to be something that fits into what we're trying to achieve as a company. I think we, in the past, with digital transformation strategies, maybe, you know, made it a thing of its own and didn't embed it really into the business strategy. And that's why we maybe struggle to really harness the impact of the latest, let's say, technology inflow into finance. So I really like this point. But I think some of the things that Marco says was that, you know, the distribution of AI tools that, you know, that gives access to people to use it. The adoption maybe changes individual work, right? So one worker is suddenly more productive than another. But to really, you know, do the enterprise impact, we need a transformation that changes workflows and business outcomes. I mean, that's really, you know, one key point. And then he talked about this bottom-up versus the top-down, where the bottom-up creates a lot of mushrooming activities, which, of course, you know, seemingly creates some sort of traction, but it doesn't really create that enterprise impact on its own. And then that top-down direction setting, if you only have that, it risks leaving your people alone, not really knowing what to do. And then you don't create the traction either. Of course, he also talked about AI initiatives needs to pass through some sort of investment scrutiny and, you know, make the hard choices, which, you know, let's remember that it's not just a free-for-all to spend, because AI can quickly become expensive. I think we have seen examples of that. And then finally, the old mantra of simplifying before you automate, I think, becomes even more important with AI. And Marcus also underscored that. So, you know, let's make sure we do it right this time. Yes. And it's interesting, because it's not the first time that finance organizations go through transformations. And when we talk about simplifying before transforming, when we talk about the changing workflows, processes, having clear accountabilities. And it's not the first time that we say these things. We've seen it as we went through the whole era of the new ERP systems coming in, of implementation of ERP systems, implementation of new tools. We've talked a lot about this when the whole offshoring wave started some years back, when the whole concept of business partnering was introduced 10 years ago. So for finance leaders, this is not the first time that we sit in the face of having to lead a transformation. So what will make us succeed in this one? Yeah. You know, it could be like old wine and new bottles, right? You know, we cannot repeat the mistakes of the past. So the question is no longer, you know, what AI can do for us. I mean, I won't say that we have invented everything that can be invented. Of course not. But it's no longer about imagining the art of the possible. Because a lot of things are possible. It's a lot more about how do we actually make it happen in our organizations on a practical level, creating that impact that we're looking for. Because it's more about what finance leaders can actually get this done. I think it's a lot more about a leadership challenge than it's a technology challenge. And I think, you know, in finance transformations, leadership is really, really key. So this is really where we need to look now, not so much to the technology. But, Victoria, you also sat down with another veteran in this space who has gone through transformation after transformation after transformation. Has definitely made a lot of mistakes, but certainly also had a lot of learnings and successful outcomes as well. So, you know, can you give us a little bit of intro before we hear some of his war stories and lessons? Yes, he indeed shared a lot of war stories with me. And I'm talking about Martin Smith, who has over three decades of experience in finance and finance transformations. Most recently with AstraZeneca and AP-Møller Mærsk. And that's where Martin and I met. So Martin has tried all kinds of things throughout the transformations and finance transformations. He was leading transformations as a local CFO in a broad and global organization. He was also leading transformations as head of finance transformation in a global organization like Maersk. And throughout these decades of experiences and war stories, he really boiled down the essence of it in the interview that we had with him. So let's hear it from Martin. Martin, you have over three decades of war experience in driving finance transformations. What have you learned? I guess if I look back over the 30 or so years, I guess I've been involved in what I would call little transformations and big transformations. What do I mean by that? Whenever I was appointed to be whatever role, I immediately embarked on my own minor transformation in my kind of area. Didn't bother paying much attention to lots of other people. Went kind of my own way. And there were lots of other little transformations going on as well. The role you're probably referring to is what I would call a big transformation, which was an overall finance transformation across the whole organization. Let's call that big, big, big, big T. So I've been involved in all of those for 30 years for my sins. And I guess if I look back on the kind of the main headlines, I would probably say that looking back, the CFO is actually the finance transformation lead. Whatever the job title is or whatever the role is, the CFO is the person in the seat. And the senior finance leadership team is accountable for delivering, not the finance transformation lead. And I think that I probably got that wrong a few times. My CFO certainly got that wrong a few times because I was given the responsibility. And I think if I look back, if the CFO and the finance leadership team had those accountabilities in their, I don't know, objectives or compensation, I think we would have probably been able to move a little bit quicker. So CFO is in the seat would be my first lesson. And there were other lessons that Martin shared, but we decided to focus on this one. And this might seem an obvious statement, but it's not. So dear CFOs out there, you are heading the transformation in your organization. And dear finance leaders, you are not only holding the budgets for such a transformation, but you are also accountable of it. Transformation, yes, needs to have the mushroom, the experimentation across the organization, but it needs clear vision, clear foresight, clear energy from the top. What also Martin went on to share was about being able to measure impact. And this is something that when we embark on a transformation, we are relentlessly focused on having a baseline, understanding how we can tangibly measure the impact of the transformation that we're driving. And then finally, Martin said, you know, Victoria, you need to celebrate successes all the time because people get tired. People lose sight on why we're doing what we're doing. So communicate, celebrate successes, and the journey will be much easier for the whole organization. Yeah, so I think, you know, one of the core conclusions from all these interviews that we've heard, Victoria, is that, you know, finance 4.0 will not succeed as an AI program. Just like, you know, back when the ERP systems came out that you talked about didn't succeed as an ERP program either. It really has to be a business or at least a functional transformation, and it should be led by your most senior leaders. I've even said recently that if you are serious about finance transformation as a CFO, you need to spend up to 50% of your time on this. And I doubt many CFOs are spending that much today, but this is really what it takes to succeed because it is a leadership challenge. It's not a technology challenge. So we need to, like you said, create the impact. We need to change outcomes, and we cannot do that if we are doing it half-hearted. So I think that's one of the core conclusions of these talks here from the guests. Yes, and again, these were just small snippets we've showed. We are going to include in a link the full interviews so you can enjoy them at your own pace. They're super authentic and real and concrete. So, yes, I would encourage you to just listen to them. We also hosted an event a couple of weeks ago here in Sandvind where we hosted over 50 CFOs from Denmark and Europe going through some of these key themes, and we are going to also write an article about it. So we're also going to share that, capturing the essence of what was discussed. Yeah. So we spoke to finance leaders all over the world, you know, both here in Denmark. I went to the U.S. to speak to finance leaders there as well, and it's all the same. We are all on this journey together, and we know the technology is there. We know what it can do for us, and as leaders, it's time for us to try and solve it. So, you know, what are some of the key learnings that we've had here today speaking to these guests and the events and everything else that we do when it comes to finance 4.0? I think there are five points. The first is to mobilize the organization. Create a safe, practical environment where teams can experiment with real work. That's psychological safety that Christopher talked about. It is really, really key because we are going to make a lot, some mistakes when we experiment with AI, and if people feel like they are not encouraged to try and that they are not, let's say, protected when failing, it's not going to happen. So I think that that's really lesson number one. Number two is to make the strategic choices like Markus talked about. You know, connect AI investments directly with your strategic bets in your organization because it's almost like we saw with the internet. It wasn't a standalone thing. It changed the business model. In AI, it won't change all business models, but it will at least change a lot. And so if you don't connect those two things, you will not see the enterprise impact that you're looking for. Number three is to fix the foundation. It might sound a little boring and old by now because we have been talking about this for 20 years. I remember I was out at a tech company giving a talk to one of their clients some years back, and it was about AI as well. And we hadn't talked for five minutes before they'd started to talk about master data. So haven't we heard this one before? But we really need to document and simplify our processes, fix our data foundation, and establish some proper governance around this. I think, you know, with AI, the burning platform for fixing this foundation has never been on more fire than it is right now. So I really hope that you will pick up this one and start to do it. The fourth point is to reimagine before you automate. Start with required outcomes rather than just, you know, let's improve a little thing here and there, and then you will start to see the impact. Don't place AI just on top of your current workflows. If they are not working, AI will not magically make them work. You know, you need to fix them first. And then finally, number five, put the CFO in the driver's seat, just like Martin talked about. If finance leadership team is not behind this, not spending a significant amount of their time on this, it's just not going to happen. And they also need to take accountability for it. And I think accountability is something that we talk about it, we say it, but then three months into the transformation, everyone has forgotten about who actually owns what and who's accountable. Let's not make that same mistake here. Fantastic. Five points. I will add the last one. Humans. Humans in the loop. We need trust. We need judgment. We need humans in the loop now more than ever. So let's enable our organizations to join this journey. Let's make sure they get a proper upskilling. And let's make sure they also have the right foundation to work together. Clear processes, access to the right data, clear roles and responsibilities, governance and strong leadership. But humans need to be at the center of this journey. Good. I think this brings us to the end of the session. And I think it has been fantastic hearing from the guests that we've interviewed. And, you know, there's one question that we actually asked throughout these interviews is how optimistic they are when it comes to the future. Get off to a big start. Build some momentum. Deliver early. Publicize the deliveries that you have made. Get going. Get active. The only way that we are part of that change is to actively engage with it. I'm super optimistic. I've never been more optimistic. I think it's a super exciting future for us. So we know a lot more about AI today than just a few years ago. It is time to embark on the transformation together with your teams, together with your function, together with your company and together with, you know, your peers around you and other companies and industries as well. This is the leadership challenge that we need to solve together. Today, we and our guests especially shared a lot of tips and approaches that you can use to run this transformation successfully and maybe better than the previous ones. It's not a technology challenge anymore. Yes, AI is skyrocketing and keep improving all the time. We can expect that. But it's a leadership challenge. How do we embed this and make it successful in our companies? That is really the knot we have to crack together. Fantastic. These were the words. Thank you so much for joining us and for tuning in with us. Thank you, Andrers. This was a pleasure. Thank you, Victoria. We do it again. Yes, we will. Thank you.