My name is Erik and we will be three speakers here today. It will be me and then Kenzie Zimmer and Tobias Søndergaard. We all work with AI and in particular AI adoption and AI transformations. And then we will also have time for a Q&A. So all the questions that you have, put them in the chat and we will, after the panel conversation, take the questions that we in particular like. So I think we are just ready to jump in. The first point on our agenda is the AI adoption model, which Tobias and Kenzie will walk you through. So let's go ahead. All right. We've transitioned here in the studio and we are ready to talk a little bit about how it is we see the world of AI adoption. And yeah, super nice to be here. So just to get us started, I think I'll try just to put a few words on how we see organizations actually doing right now when it comes to AI adoption. What are we seeing? What's the stance? What's the role of communication? And then we'll kind of dive into how it is, how is it then that we actually work with this? How do we support our clients in this? So we are moving from AI rollout into real, you know, scalable organizational learnings. But we've been asked to kind of try and also, you know, do a little bit of a benchmarking exercise. What does this actually look like? And across the organizations that we work with and the organizations that we read about and interface with, we see a few patterns that repeat. Adoption comes in three waves. And I think also it's worth pointing out that these definitions of the waves are not necessarily defined by what the technology is, what state it is in, which tools you have chosen, etc. It's more about the organizational capabilities. So we like to say that the first wave of getting started with AI adoption is where it becomes an initiative. It's where a tool gets bought. There's a launch. Maybe there's even an all-company email. There's possibly a slide at a town hall. And then to be quite frank, what we see a lot is silence. Silence is never good, though, because it is not neutral and it kind of creates a vacuum in organizations. So when you've pushed that button, you've sent that email, you've gone on a town hall, AI is going to continue. People are not going to stop. But they're likely going to stop telling you about it and you will not be able to facilitate those conversations. So it means there's likely to be a little bit of shadow AI going on using unsanctioned tools. There's going to be some ad hoc training here and there. And there's, you know, at the end of it going to be some energy without a specific direction. And it sounds a little bit harsh, but I think this is a natural starting point. It's a place to mature from. I've put the 7 out of 10 dots on this slide trying to indicate that we actually do believe that around 70% of organizations are in this place. Wave number 2 is that AI becomes a program. It becomes structured. It becomes segmented. It becomes cadenced. There might even be learning journeys for different types of employees. There will be a communicative rhythm that Erik will get back to talking about later. We'll be tracking the usage and so on. The organization, you know, starts pushing, but it also kind of starts listening for the first time. So this is wave number 2. We like to say that based on our experiences and some of the studies that we are following, around 20% of organizations are here. And then finally, wave number 3, AI becomes a movement. Communication starts running two ways, back and forth, and it lives everywhere. That means the leaders are going to be narrating the direction. Managers are hosting local conversations. The teams are sharing what works without necessarily being asked. And at this level, AI adoption becomes self-sustaining. But it's also definitely very tricky. I think we like to say that 10% of organizations at best are here. And even if you look to some studies like the recent BCG AI radar, 1% of executives actually describe their role as really mature. So that's what we see. A final note from our side is, you know, also notice what's not on this slide. We talk about the organizational capability. So we might even meet companies that are running advanced agentic workflows in places, still being in wave number 1. It's something else having an organization orchestrated around that. So when we talk about waves here, we try to measure the organizational strength, in a sense. So the question then becomes, which we'll dive into, is what actually starts moving you, you know, your organizations from one wave to the next? It isn't necessarily budget. It isn't necessarily the model you licensed. But we like to say it's kind of about that, the change muscle, the AI adoption muscle that exists. So going into that, I will start out just really briefly. But the way that we work with this and the way we help organizations move through follows four dimensions and one, you could say, overarching principle. We work with communication to provide direction and meaning in order to mitigate uncertainty. We engage in capability building to build the ability, fostering the practice of good AI behaviors. We talk about enabling structures, so giving access, setting expectations, sustaining communities. That's the tissue that makes AI youth legitimate. And then we talk about leadership, you know, supporting the leaders that hold the AI adoption paradoxes that become surfaced and then still being able to make clear and sound choices. So that's the top level. Yeah. Yeah. And I think the line running underneath all of this is this concept of designing for agency. So the goal is never just compliance with a rollout. We see in AI even more than other sort of more traditional IT implementations that this is different. So we want people to be acting with this technology on their own initiative. We want the organization to be creating space and be enabling people to also be working both bottom up and top down. So let's dive right into a few of these elements. We're going to move on to communication, which is our first one that Eric's going to talk a lot more about today. And this is sort of both the when you have a tool rollout, but also the ongoing conversation in an organization that Tobias and Eric have mentioned that has to sustain what's happening in the organization after we just make something available to employees. So this is how we support the ongoing dialogue. And this can take a lot of different forms, but I will save that part for later. Then we have a capability building. So growing the practice. And this is something where we're seeing companies are really beginning to move from a one-off tool training. How do I use it? What do I click on? What are the features? And beginning to talk about what are AI capabilities? And these can even be tool agnostic. How do I ensure quality? What about critical thinking? So we want to have a shared language around AI and a collective capability to work with it in the right ways to support business objectives. We want to both have an AI for all. So empowering everyone. And then working with certain areas of the organization that are maybe going further. So this is really running the gamut. Enabling structure. So we need to give it some form. What does that mean? That means that there's sort of this connective tissue that enables the active use of AI. This could be what tools employees get access to and how we're setting them up in order to support more advanced workflows, in order to support ease of use. Maybe in a bespoke GPT you're focusing on user interfaces or UX. Maybe if you have an enterprise solution you're looking at how the business is working to enable features that make sense and can support employees in different areas. Maybe there are development expectations that leaders have with their employees and different organizational support mechanisms. What sort of communities are you building up around AI? So moving it from just the individual to how they're working in the organization. And that would all be included in this element. And finally, this interfaces a lot with, of course, communication, but leadership. Be the catalyst. So we know that leaders right now are in this position where they have to hold paradoxes. There's a lot going on in this space and they're supposed to set direction, but there's a lot of uncertainty. Employees are supposed to be experimenting, but the business is also supposed to be benefiting. And how do we bring clarity and ensure progress while also making space to navigate these dilemmas? So we're not going to know everything. And so a lot of that is supporting leaders at all levels. It could be the top level of the organization. It also could be the leaders working with teams and every day. And in addition, leaders leading themselves. So how do I lead myself in an uncertain transformation like this? Great. These are the elements of our approach to working holistically with organizations on AI adoption. And now we're going to dive into communication and how that drives healthy AI adoption. Thank you so much, Kent and Tobias. It is now time to zoom in on the communication dimension. Here the point I want to make is simple. Strategic communication is a key priority for achieving healthy AI adoption. And I'm going to walk you through how we see it. To us, communication is not just a transfer of information like the emails being sent out explaining the access to the tools. Or here's our SharePoint site with a prompt library that you can neatly use. Or like an intranet article explaining compliance rules. To us, communication is the continuous orchestration of these meaningful conversations around what AI means for our employees, for our leaders, and for our company as a whole. When applied right, communication replaces all the uncertainty that is around AI and builds trust and meaning. Let me explain what I mean. So AI moves super fast. We all know that. And because it moves fast and it has a lot of impact, it puts pressure on organizations. The way we see it, leaders are expected to offer clarity in an environment where the technological developments are just accelerating. A competitor seems to be moving faster than you. And AI is expected to be this golden nugget thing. But it's also a potential disruptor. It's a business killer. People are talking about it in very vivid terms. And finally, the rising cost of tokens and licenses makes this a serious investment. It adds pressure. Excuse me. See? Fear of losing jobs, the excitement about efficiency gains and just a general generosity or curiosity. And this sense of overwhelm. To be frank, and I think you would agree, AI is currently the topic over lunch with a colleague on LinkedIn or just in a conversation with your grandma. It's everywhere, right? So combined with the fact that there is no single right way to use AI means that employees are left to find their own path. And that gap, that gap between what leaders are expected to do and what employees need, that is a communication problem. It's one we know quite well from other transformations, but what is new around AI is that this problem becomes supercharged. Higher stakes, less time, more people, and more uncertainty. So, leaders facing all this pressure do what most of us would do. They wait. Wait until they've spent like four months developing this clear strategy that they can communicate. Wait until someone in the company violates a guideline that is tucked away in a SharePoint site and then step in. Or wait for the technological developments to sort of just settle. But the truth is, this will never settle. Meanwhile, employees are waiting too. They are, but they are also waiting in silence. The lack of information and communication from leaders is not coming. So, what they do is that they start having conversations with colleagues. They are reading headlines. They are forming opinions. And they are looking up for this signal that's not really coming. This is the vacuum that we are talking about. But it doesn't stay empty for long. Because what happens and what we see with our clients is that employees fill this vacuum with noise, rumors, feelings, and whatever that sort of just happens to be in the organization at the current time. And the irony is that this silence is not a strategic communication choice. It's just fear of not saying the right thing or saying the wrong thing. But from the employee perspective, silence is a message, like Tobias talked about. And it can be a message interpreted in many ways. But what we see is that it's a message that this is not really important. Or maybe it's an invitation to do whatever we like with AI. So, in case that you were unsure, yes, this signals danger. And the thing is that it's not just a leader-employee problem. It's an organizational problem. So, without meaningful conversation, this vacuum will form across functions, teams, across management layers, creating interpretations of what AI is and how it should be used. And this adds risk, if you were unsure. And it stalls what we call healthy adoption. So, we need to prioritize communication. If we don't prioritize communication, what we see is that we see four key risks. We see that it creates an environment of fear and distrust, because people are simply left to themselves and they're fluctuating feelings. No communication also leads to data exposure and that being increased, that likelihood being increased, because people are just using tools without really knowing the risks of using them. Third, we see that adoption becomes uneven across the organization, because some teams move fast while other hosts hold back. And finally, if we don't prioritize communication, impact stays low, because people don't understand how to work with AI in ways that create value. So, a few examples that we have seen and that we come across quite often is that, in the first case, with this fear and distrust, this translates into skepticism and conversations about job, fear of job loss, simply. Some completely avoid using AI, and others use it for individual gains. In the second category, an example could be that little or no communication leads to a lot of employees using public tools without really being mindful of what they're sharing, and this creates a risk. In the third category, a result of poor communication also might lead to a silenced learning culture. Here, we have experienced that a lack of open sharing about what works and what doesn't slows down the collective learning. It becomes a me game, not an organizational game. And finally, if organizations don't communicate, those late bloomers might never really adopt AI, because of the expectation-reality gap that we see. Early experiments and working with this technology disappoints. I don't get what I wanted, so I'll never use it. This stalls the momentum and also slows down healthy adoption. So, the point is that employees don't have bad intentions, but it's the unclear communication that creates unclear behavior. And this is what we want to do something about with communication. So, what do we do? The problem is a vacuum, but the answer is not just information. In our perspective, the answer is communication that creates meaning, direction, and the confidence to act. And then, not doing it one-off, but doing it continuously, because this will never stop. So, leadership, managers, and AI leads must speak up, because AI adoption depends on it. To do that, we have four guiding principles. First, you need to take a stand and set a direction for your company or for your department and your use of AI. Not explaining everything, but explaining your ambitions and your directions. This helps build trust and confidence in both the technology and also senior leadership that you represent. Second, you need to balance excitement with that parameter of risk and compliance awareness. AI, as we know, creates a lot of opportunities, but it also has inherent risks that we need to explain. And we need to explain these clearly. Third, you need to communicate about upskilling and training and capability building in a meaningful and engaging way. So, people don't build capabilities and knowledge that they don't really have. So, finally, you need to stimulate a culture of sharing and learning. So, the organization can surface both the good and the bad examples. And this is done through communication and through continuous communication. So, figuring out how we communicate on an ongoing basis, whether you are a team lead or you are part of the senior leadership, is what we do for our clients. We help you figure out what should go in each of these boxes to create healthy adoption. All right. So, if we look at it from this perspective, if we use communication well, it allows the organization and the leaders to step into this vacuum that's otherwise there. And it replaces the uncertainty and it creates meaning. We are not doing this by pointing to a fixed destination where we want to go. No, we are sort of just building that shared meaning and that collective confidence over time. And it takes time. But being silent is not the right way to go. So, the goal is simple. Make employees feel that AI is happening with them, not to them, or not in the absence of them. To round off our perspective on communication, we have a few recommendations for you. The goal is not to control how AI shapes your company. It's really about taking control of that uncertainty. And to that, we have three recommendations. So, our first recommendation is what we call leadership sensemaking. We suggest a close sparring between senior leaders about what should be communicated. Not that they become the technological experts, but that they figure out what this technology means for them and their company. And this takes time. But it also builds a meaningful and trustful direction. Too often, we see that leaders are saying stuff like, yeah, but we need more use of AI without following up with why it's important for us. Or it will disrupt our business and it will kill our services and not explaining, so what should we do about it? Or finally, senior leaders saying that they are not really using AI themselves and it's a do or die scenario, which sort of leads the question as to why should the organization then engage in this technology? So, create sensemaking together with leadership. That's our first recommendation. For the second recommendation, it is give a clear mandate and share examples. Employees should be encouraged to work with AI while knowing what they're allowed to do, basically. So, it's super important that they have that feeling that their leadership is backing them and that they can see good examples of good use. If we don't see examples and if we don't clear about them, it's really hard to know what's good and what's bad. So, that's a second recommendation. Give that mandate and share those examples. The third recommendation is the local conversations through managers. Managers should not only be able to pass on information. They also need to create space for this conversation to take place in their teams. They need to figure out and have conversation about what AI means in our work and how it can help us and how to be careful about what this means. And now we have a phone ringing in the studio. So, I will just shortly, and there it goes. Hope someone's not sick. But, we are sort of at that place in time where we have given our perspective on communication. And what we think about it and what we believe are super important. I will now sort of move to a more comfortable setting and join my colleagues Tobias and Kenzie for a conversation. And good recommendations. So, I will take the first one. Okay. So, what is the communication mistake that you most often see organizations make in AI projects? And what does it cost them? To me, and the mistake that I see quite often is that they're communicating all the danger. Basically, just setting their own platform, their company on fire without sort of pointing to the lifeboat. So, it's really just big words, a lot of feelings, explaining the risks, but really not explaining what to do about them. So, leaving the organization sort of with a big question mark, I think, is a big mistake. Yeah. Yeah. Yeah. No, no, for sure. I like that response, Eric. I think also a lot of it actually comes down to, and I think you said before as well, is, you know, giving information. So, I think there's a lot of that going around. We just implemented a new AI tool. You know, go ahead, enjoy, explore without setting those. So, like the communication doesn't really become actionable. It stays on an information level. So, it doesn't really set a mandate. It doesn't really set expectations or similar. It really just conveys, we have a new tool, kind of on that level. So, I think it's kind of about probing, how do we get like one step deeper on the communications as well? I don't know if you agree, but I think a lot of it stays top-down, stays informational based. It doesn't become conversational. It doesn't become, you know, collaborative. It doesn't become a conversation. Yeah, and it's like I mentioned previously, it's this pointing to a SharePoint. You know, here's our guidelines. Here are the compliance rules. Here's our way to work with AI. But it's just information. And employers don't really know what to do with them. Right. Another example that we often see is that leaders will say, experiment with it. We want you to try it out. And then nothing happens after that. So, it's like, okay, you know, will you set it on the agenda at your team meeting every week and ask someone to present something they tried? Or you have to follow it up with like creating that space. We talk about that a lot with designing for agency so that you're not just setting a message, but then you're giving them a vision of, I'm not just telling you, but this is how we do it in our actions every day. So, experimentation lives and it's not just a saying. And I think the point of experimentation is particularly good because you do see it quite a lot. And it becomes, I think the questions that follow is, great, am I supposed to do that on my own time? Like get my work done faster so I can find time to experiment? Right. Or would that be provided to me? Yeah. Good point. Yeah. I think maybe a final point I'll make is we're seeing quite a few companies communicating externally before communicating meaningfully internally. So, as an employee, you're kind of finding out where your organization is on AI by reading an external source and then kind of wondering, okay, well, what about me? That's a strategy. Yeah. Cool. Okay. Let's take the next question. Question number two. Leaders are expected to set a direction and create safety around AI, but many generally do not know what to say. What does good AI communication from leadership look like in practice? Tobias touched on this a little bit before, but difference between information and meaning. And here I think we also talk about leaders getting themselves involved. So not only what this means for us, what this means for you, but what this means for me. I think a lot of leaders are also going through their own AI journey. They might not be particularly used to working with AI. They might be on their own journey. But I know that in some scenarios where I've worked, leadership has been quite open about where they are. I'm also trying this out. I tried it out the other day. This is the result I got. This is what I think. So kind of inviting employees in to that sort of transparent conversation and not having it always just be so corporate in a way. Yeah. Yeah. Yeah. And I mean, I was just with a leadership team basically yesterday. We had a lot of great conversations around it. And I think to your point, Kenzie, it's totally fair to be on that stage in your journey. I don't think, I think the vacuum that you've kind of established for us, the communication vacuum, Eric, is it's not something you're supposed to fill out with technical expertise. I mean, if you're a leader, you're not supposed to be the expert explaining all the bits and pieces of, I don't know, selecting models or choosing tools or whatever. That's not what it's about. But I do think at least one thing which we also sometimes see is that actually then that won't necessarily stop leaders from going on, say, a town hall or a video on internal communication piece and saying, this is really important. But the problem becomes if you haven't really had those experiences, if you haven't really worked with it, tested it, again, not on the expert level, but just on a, okay, people have told me it's important. Let me get my hands dirty and my sleeves up and actually assess it. You probably need to do that before you start telling your organization it's important. I.e., you need to figure out what the change is and why it's important before you go say that to your organization. Because if not, I think people will spot it like that, basically. It's about trust. It's about trust, for sure. To me, I think it's really about leaders establishing some sort of pulse about what's important. around around AI and what it means for them. Figure out how do I bring this in, which is also part of the structural elements. How do we bring these conversations in to whatever we have? If it's a weekly meeting, if it's a weekly touchdown, if it's an email that you are sharing with an opinion that you have or whatever it is. And I think because understanding the technology won't happen overnight. It takes time. It's an investment in time, but it's also you need to help yourself creating that meaning through some sort of pulse with your team and with your organization. So establishing pulse is my recommendation. Yeah. What does that kind of look like in practice? You know, if you were to say, okay, you need to set up a pulse. Yeah. What do you do? Yeah. What do you do after this webinar? Yeah. But so what we recommend is that that senior leadership have an active voice and shares their direction that they want to take the company in ongoingly. So it's not just one town hall. It's tapping into existing meetings that's already there and putting AI on the agenda and bringing meaningful things to that meeting or to that communication. So it's really about finding existing meetings or establishing structures around communication to have that pulse. I think if you also talk about manager in the team level, managers are a lot there for the everyday work and they're really, you know, the ones that are, you know, employees are seeing on a more frequent basis. And so it's also about like, this is how we're going to own this. So this is our, you know, area or business area department goal. And this is how AI fits into that. So it's not necessarily only about the technology, but it's also about the business problems we're trying to solve. And, and, and conveying that and kind of saying, hey, team, you know, this, this is what this means for us. So maybe there's some norms we need to have maybe in our area, compliance is super important or quality. And this is how we're going to discuss how we work on it together. So also I think good communication from like middle leadership is kind of about moving from the individual to the team and kind of setting that, that the framework. Yeah. Yeah. Are we ready for the last question? Last question. Last question. Before we go to the online questions. It's a tough one, but it's also, I think an interesting one. Curious to see what you guys say. Yeah. So the question is, what is the one piece of advice you would give to a program owner and leaders who are part of AI adoption projects today? Mm-hm. If I, if I should start, I think that because the technology is moving so fast and we don't really know where we're going, but we just know that we're moving fast. The one piece of advice I would give is that you should talk while you are walking. Because if you are staying silent, it becomes a problem. And if you're just doing stuff, it becomes a problem. So, we don't want to open a situation where people in organizations think that or have a feeling that I think AI is happening somewhere in the basement, but I don't really know. Or we have, we are being exposed to all these information on LinkedIn or wherever, and I'm just getting the anxiety. What does this mean for me? So it's walking while you're talking. I would say my, my recommendation would be. Yeah. Yeah. For me, it's taking trust seriously. And I see trust is happening at a lot of different levels in the organization. An easy one that we talk about, I think a lot more when it comes to training is an individual and the tool. So how do I trust the tool? And this is a lot about, you know, the data and knowing how to use it and things like that. But then you could have trust between employees. So what happens when my fellow employee is suddenly a subject matter expert in my field overnight, because they're using AI and how does that affect the way that we work? Or can I trust that the way my colleague used AI is the same standards that I think it should be used? Employees to organization. We've also talked about, so where is this going? Will I have a job? And then leaders to their own employees. So can I trust that my employees are following the guidelines we've set? And to avoid it being only at this umbrella level, I think often in change initiatives we say, like start really small and keep even the smallest promises. So if people have questions at a training, address them. Answer the questions. Get back to them. If people reach out, it's these small things that begin to build trust so that people feel like they're not sending everything into a vacuum. So taking that seriously, I think, is super important. Almost like several vectors of trust. But then also, I don't know if I can put you on the spot, but what's the most important vector then? I think that's hard. I think, I don't know if I could pick one. I think one that's maybe under looked at is team trust. We're seeing it's been a lot of individual use, and now we need to begin moving it to how our team's going to be working. And, you know, going from individual gains to organizational gains. And that can be a big blocker if everyone's sort of running around and not really knowing the expectations of working and trusting each other for that collective work. Yeah, sure. Sure. What do you think? Yeah, I think for me, just kind of the last perspective probably is, I think it's also about the structures. Like, I think in many cases, it becomes one-offs, right? Okay, we need to get started. So we need to communicate. Okay, one email going out to all of the company, you know, done. Check. Next step, we do one training for everyone. Check. And then we kind of assume it'll just go by itself. So I think, you know, we talked about enabling structures before. That's part of it, setting structure and like putting some rigidity behind your AI adoption efforts. But I think the same is true for working with your leadership, for doing communication. I think all of that is important. So it's really about finding a rhythm for doing that. Because unfortunately, it's not just a one-off. Especially, you said, it's a really, it's a volatile, it's a complex world. We had a new model two days ago. It changes all the time, which is super fun. But I think for many employees, it also becomes really, you know, oof, a new model two days ago. Shit, do I need to change the way I do my work now or not? So I think having structure around that is going to be important. It's not just a one-off. Perfect. I think we'll take some questions from the audience. Nice. Let's see here. There's a lot of them. Thanks for shooting questions out. Yeah. I'm having to. Good. So we're going to focus on the communication questions. Well, I can say it's finding one. I think that at least the feeling or what I'm seeing is that this feeling of FOMO is really, it's really real. Yeah. It's really, really real. Yeah. And wherever we go, we talk with people and clients that explain that they don't want or that they are feeling that they're missing out. Yes. Really. They are not at the party. But they're standing outside the party, looking at LinkedIn, looking at or talking with other colleagues during evening events or whatnot, and they're not in the party. And that's the feeling that we have to deal with when we do these adoption projects. Yeah. All right. Here's one question. You have communication as the first part of your framework. What is your view on the actual starting point? You make a point that follow-up communication is important, but do you start with FOMO and leaders? We always, at least what I say is that we always use the hierarchy. We always need to respect the hierarchy in an organization. We don't want to just shoot out that email. We need to onboard and explain what this means at a leadership perspective first. So communication, yes, that is the first thing, but working the way down the organization is key, really. Yeah. As I see it. I think, and I'm also probably, I'm tuned towards the technical stuff as well to some sense, but I think it's about, number one is like, you probably need a good tool that can be set up in a good, structured and compliant manner. You need that to start. Then you're going to want to take those, I think, baby steps in a sense. And I think like you put it before, Kenzie, maybe starting with smaller commitments, living up to those, and then kind of bridging as you go across. Now, the three ways we talked about before, you know, the role of communication, et cetera, that changed from being, you know, really limited, really top down into being more, know, in the sense of it, more segmented, more focused. That means it starts moving towards the teams until at some point we've reached the Nirvana point where it's self-sustaining, you know. Employees go around and they start making connections. What did you do with, you know, your AI tool yesterday? So, I think it's about really trying to come up with a plan for how you actually can evolve from those levels. But it probably starts top down, but you don't want to start that without having structures in place for how you will take them to the next steps, if that makes sense. Yeah. And it also depends on where your organization is, where in that three-way thing that you talked about in the beginning is your organization, your company, because it will depend on what initiatives that you should do. Yeah. Eric, how do you balance between communication training needs as a foundation before it appears as an AI adoption need? So, can you say that again? Yeah. So, what do I think? If I understand the question correctly, we are using or we are communicating in order to get people into the classrooms quite often. And we know that just setting up this training event doesn't mean that people will participate. So, we are strategically communicating in order to get people engaged and participate in training. And that's part of, you know, upskilling really. And how do you get people into training? Do you just send them a mail? Here's the training sign up. No. It goes through the leaders, obviously. It's a cascading exercise. And it's getting these leaders to push for the mandate and push for the invitation to go into the training. And the all email does not work. Yeah. Okay. Interesting. So, we have one last question maybe and then… Yeah. I think we have about 30 seconds. Will the slides be shared after the webinar? Yes, they will be. Yes, they will. How does communication play a role in the uneven gap due to personal interests and priorities of AI adoption? So, how do we reach individuals through communication and uneven adoption? That's a good question. If I can piggyback on also the waves I talked about, you know, from at the second level, it starts becoming a little bit more segmented in a sense. And I think it's at that point you start focusing on and you probably start becoming mature enough to really also segment that communication. Because there will be people in the organizations that will have a harder time getting started. They need some sort of support, some sort of training, some sort of communicative efforts, some sort of support from leaders. And they will be the ones that will just do it by themselves. They will use, you know, ChatGPT to learn how to cook a lasagna or fix their bike. And they can bring those experiences to work. So, I think that's also where AI is a bit weird because people didn't do that with their SAP systems, you know, before. So, yes, so I think it's working to segment. I think that's important. Yeah. Thank you. I think that's it for today. All the time we had. We had. Thank you for joining. And if you are curious to learn more, you are happy to reach out to us and share what's happening in your organization. But thank you for tuning in and have a good day. Thank you. Well, it's normal. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you.