Glossary, Dr. Welcome everyone to this webinar about generative AI adoption. Thank you to all of you that have dialed in this morning. My colleague Kål and myself are your hosts today. And with us we have Morten Rue Christensen, CIO in Semler Group, to present their generative AI adoption journey. Thank you so much, Morten, for taking the time to share your journey with us. Thank you. So we'll be spending the next 30 minutes together. And the purpose of this webinar is to inspire you on how to approach generative AI adoption in your organizations. The agenda for today is quite simple. We have three points. We'll start by taking you through the characteristics of generative AI adoption and herein the typical barriers of adoption. Then we'll give you a short presentation to implement best practice framework for driving generative AI adoption initiatives. And lastly, and most importantly, and what we're all here for, Morten will present a concrete case from Semler Group on how they go about driving generative AI adoption in Semler. We will not have time for a Q&A in this session because it is a short webinar this morning, but feel free to write your questions in the chat throughout the webinar, and we will come back to you after the webinar with our answers. Thank you. Thank you. All right. in front of us with this genitive AI adoption. And we can already say now, it is significantly different from any other IT projects we have seen before due to several factors. And let's just examine these for a second. So first of all, when it comes to genitive AI, this is heavily quality dependent on your competencies. This means that your skills dependent on the quality you will have. So in other systems, there's a wrong and right answer. You cannot necessarily mess it so much up. But here it depends on your skills. The second one is that this AI system evolves dynamically. That requires for ongoing updates and improvements. So it's not a one-off and say, now we have developed this solution, we're good. You will be outdated within three to six months quickly. And then the next, there's individual use cases here. So use cases are heavily relying on who you are. So it's really hard to standardize our processes and approach to this. And fourth, the boundaries are a little bit blurry that present challenges in how defining where we can use it, how not, and what are the scope as they are expanding all the time. And lastly, this comes of course with ethical and legal risk that we must carefully manage to be sure that people are using it responsibly. So this is just different than anything else we've seen before. And when we ask people and survey them in organizations saying like, what are the barriers for you to adopt this technology? Actually, we can see most people are not actively resistant towards Genitive AI, but there are still barriers for them to overcome. One of them, give itself, is lack of access. If your tool do not have the functionalities or simply do not have access to a tool, then there is of course a barrier there. But the biggest barrier by far we are seeing people are saying that is, I do not understand the full capabilities of what this can do. And it's hard to say, how can this create value in my day-to-day work? Most of us can see that ChatGPT can write an email, translate something, but what more than that? The next is poor quality outcome. And that's because our limited prompting knowledge or understanding of what it actually should do and the model behind. And that will cause some people to doubt the effective and maybe of the value of this technology. The fourth is the lack of time. And I think it's a little bit of a dilemma here that we can see that so huge efficiency, quality and creativity gain to be gained from this. But people are saying, I cannot find the time to invest this upfront. The next barrier here, that is when it comes to lack of trust. People simply do not believe what it come out with necessarily as the right thing. Maybe it's incorrect or biased results. And the sixth, that is like the expectations of how I should use this is unclear. What am I allowed to do? Can I be open about it? Where can I use it or where can I not use it? And there's some confusion and lack of direction here. So all of these coming together with this unique thing about Genitive AI and these barriers just call for our, we need to have a different approach. We cannot necessarily use the same tools as we've done with other kind of IT implementations. And thereby we have collected all our experience and knowledge from projects now and put that into what we call a holistic AI adoption model. So here is our framework for looking at AI adoption. And addressing these challenges is quite important that we do this systematically. And it's so much more than technology. I can already say that. So each of these elements here are supporting the end users in make sure they are adopting it to their needs and in that workflow. And when I will, I will present these elements one by one for you in a second. And Morten will here in a similar case present how he have unfolded that in his organization. So central to this framework is to say clear ambition and goals for where the organization should use it. And this is a top down approach to say, where are we going to play with this? And most large organization. And most large organization are somewhere mature on this. But if we look beyond that, there is also a need for having use cases. The use cases for the end users need to be cleared, identified and create value. So where is it that we are going to use this? So that is like some of the basic hygiene thing that we need to have in place. But the next thing we need to look at is the leadership. And it's quite important and critical that the leadership dare to set clear expectations. So that we can inspire adoption and inspire adoption and show themselves how they are using it and also really support the experimentation that is needed for us to succeed with this. So next thing comes probably without saying that we need to invest in training. So training, we need to have good training for everyone. But this is also quite new because it's continuously education. You cannot say you have been on a training one year ago and you know everything about genitive AI because it's probably outdated. So there is something about staying up to date and understanding what is needed there and also go closer to the end users because broad organization training is not the medicine for everyone. So next one coming up is communication. It's quite essential to keep stakeholders engaged, to keep them updated and reasons to change. It's pretty important. It's not too technical and not too high level. So you need to find the right balance between when you're communicating this technology here. All right. And the fourth one we come up with here that is culture and ways of working. Making AI accessible and promoting peer learning cultivate an inclusive environment. This is where we make sure that people use it openly and learn from each other. And this is a key because we see people are sometimes working with this in the shadows and do not dare to be open about how they are using it. All right. And if we look at the fifth one that is performance management. So performance managing is a background monitoring what actually are the thing that move the needle. Monitoring the KPIs, KPIs and having insight into how are your AI adoption actually progressing and dare to measure that and actually also steer when you're not seeing the result you dare to have. So this playbook will not be the same for everyone but you need to experiment and evaluate the impact for your initiative here. And so sixth that is coming into user experience and functionality. We need to understand that the technology we have here to need to be easy. We need to have the functionalities that we actually need. And this is quite important that this is also close to the end user. So they have a saying in what they need to have in. So bringing this together, this is actually our holistic model of looking at AI adoption. Now here in second, Morten will unfold how he has been working with most of these in their organization. So Morten, will you dare to show us how you've been doing it? Thank you, Carl. And good morning out there to everyone. As Carl said, my name is Morten Rue Christensen. I'm CIO from Semler Group. Those of you who doesn't know Semler Group, we are the largest player within automotive. In Denmark, we also have activities in Sweden and Norway and the Baltic countries working with Volkswagen Group and all the brands there. About 3,300 employees in Semler Group. And we have a bold vision about being the most digital and customer focused player in the market of mobility services. And if we look at our strategic ambition here and our strategic goals, how does that align with our project goal here with the AI? Our ambition for our AI adoption project was actually to increase the understanding and adoption of a broad suite of AI tools for all employees in Semler. But also to be able to provide some great use cases to give some inspiration to the users and democratize the use of Jane AI tools in Semler. So we have a lot of data. One of our, one of our, we have a, right now we are working on a very large digital transformation. It's called our NASA program. It's a new data management system built on Microsoft Dynamics and we will go live next year. And we know that when we go live, this new system will have co-pilots, AI agents and so on. So it's also for us, it was also important to, to train our users before we have a new data management system. this big transition September next year. So, um, first we sort of, uh, we wanted to target a different types of, uh, of user groups. Uh, so we have, uh, in our car, uh, retail shops, we have service and sales advisors. Uh, who are using, uh, who have contact with customers every day. Uh, they are writing emails and we wanted to, to, to, to, uh, actually give them some tools, uh, to, to, uh, improve, uh, the customer experience, but also give them some tools to, uh, to, uh, to, uh, general knowledge, uh, search, uh, using, using our AI tools. Then, uh, we saw the group of employees at our headquarters, uh, you know, in, uh, in, uh, we have white collar workers, we have blue collar workers, uh, uh, so in the headquarters, it's mostly administrative, uh, white collar workers working for the brands. And they are, of course, heavily users already on, in IT and the office suite. And we want to give them some more, uh, tools, uh, like copilot, but also just, uh, again, uh, information search using, uh, similar GPT. And now I'm saying similar GPT is because we actually developed our own, uh, GPT. Uh, so, uh, that we have, uh, uh, uh, given access to for all employees. Uh, and then for all the similar, uh, employees, uh, give them, uh, a foundational training, uh, give them some knowledge about how to use AI, uh, some inspiration on the different use cases. And, uh, of course, also some, some training about ethical, uh, and, uh, and, uh, IT security governance. We targeted 1,600 users, half of the employees during this project. And we could see that we had out of the 1,600 users, we had 50% of them, 800 participants, completed the two modules in Gen AI Foundation. And these three courses was actually not tool specific, M365 Copilot was, but the others was not tool specific. It was more the general way of using AI, how to prompt, how to understand new ways of working and so on. So we made, together with Implement, we made these modules, webinars, where the users could participate. So two modules for Gen AI Foundation, one module for the leaders. Also, one important thing for us was also to give the leaders the right tools to be able to lead with AI and move, be in front of the users and help us fostering the Gen AI culture. And then we had about 70 participants working with Microsoft 365 Copilot. It's not like, in Simla, we have chosen not to just roll it out for everyone. It's by request. And I think right now we have about 300 users on Copilot. But last year when we did this, it was still quite new for us. And we had almost everyone participate in this training. The training was webinars and it was recorded and it was transferred to our LMS system. So all the other employees who wasn't able to participate in the training last year could take this as e-learning. And today we have more than 1,700 employees who have conducted these trainings. So this is very nice for us actually to have the work that we did with Implement, creating these modules, creating the content that we are able to reuse it. as e-learning modules in our LMS system. If we look at the training and the communication, we sat down with Implement and we designed this communication flow. How would this look like for this is an example for Amalia, who is a service advisor. How would that how would our communication trigger Amalia? Not only with emails, but also for training invitations, posters, a lot of communication initiatives. And this is an example for us. And this is a busy slide and you will get it afterwards. But it's it's very important for me to say that thinking about this as a. IT project with the right communication plan is very, very important. And it's yeah, you see here there's a lot of steps for AI training. When we talk about communication. When we talk about communication, it was also important for us to have the top management to sort of step up and tell the core story. So we did this with Ulrich, our CEO. And and it it helped, of course, to to to to convince our colleagues to participate in this training, but also have have we had we had we had we had we had an AI site where you we share links, we share tips and tricks. We have every Thursday we have an email with first aid treats for for using AI sort of to to keep the the keeper our colleagues have their interest up after participating in the training and and and and and and and and and and and make sure that we are talking about AI and share knowledge with each other. One other thing we did was actually with to have these small cards. This is AI you would say conversation cards. So these were in our cantina and at the coffee machine where colleagues meet each other. And if you flip the card, there's a question. So this one is actually in how way in which ways do you think AI can inspire to more creativity in your daily work tasks. So you could sit eating your lunch with your colleague and then then ask them a question. And it's actually quite funny. They have been used a lot. So again, just an example of the different tools we use for communication and for for user adoption. And here you see some examples. We also have a pop up for us, the AI experts. So we have a pop up every week where you can ask the AI experts questions again. It's it's it's it's about keeping keeping the fuss about AI and and make it easy to to to to ask questions and adopt these new tools. If we look at our cultures and ways of working like a call also said, we see we have five core elements that we consider very critical for our long term anchoring and the continuous learning journey. So we need to after participated in the AI foundational training, we need to have other training ways as well. So continuous learning is very important for us. We have we have workshops we have we also do more. You could say face to face training. We also see of course, we can also see of course, the usage of co pilot, the usage of similar GPT and other tools. And then very important, the leaders are leading the way. One of the things we have done is actually in our leader training to have AI specific questions and AI dilemmas they need to solve. Also to have the leaders give them some tools and make them more aware about the process of AI. If we look at our performance management here, I think our numbers tell a great story. We have created a very high momentum of of Gen AI usage in similar group. So we did a large survey earlier this year. we have created a great approach. And we did a great day. And we did a great day. So we did a great day every day. And 60% of our leaders have participated in our leadership training. We see that the growth in using similar GPT, especially is it's growing. It's not like implementing other IT systems where when you log in Monday morning, you were suddenly forced to you to be in the new system. AI is actually something you see. select, you choose as a user to use this and it takes some time. It takes it takes the adoption rate is a little bit lower than than you might expect. And then we have the users, 89% of the users with a license use also M365 Copilot. So our adoption journey has revealed these three ingredients. The leadership engagement, make sure that the leaders move first, train the leaders. They need to sort of set the pace for the rest of the teams and also focus on the benefit realization. Is it do you want to increase your customer satisfaction? Do you want to automate some tasks? And how can you measure this to see if this is a success? And then also have a long term AI strategy, whether it's with a copilot or your own AI product. It's very important because as a call also mentioned, things are changing every day and it's difficult. It's it's it's new features are coming every month and you really need to to have this strategy. Thank you so much, call call more than I'll just stick to this for a second because I just have a few questions for you. Yeah, sure. So AI adoption is a long journey. It is. It's not something that ends with a project. No. It's not something we can finish and complete in three months. Definitely not. So what have you been doing? What actions have you taken in Sempla after you completed your AI adoption program with the training and the communication and the whole nudging program? Yeah, so we have as I said that the outcomes of the training and the webinars is now a learning module and we have divided it into smaller snippets so users can can can take this training and we also doing a lot of of workshops to inspire and to to get some more yeah more hands on training actually for the users. and we see it's a combination. So both the e-learning but also have the dedicated workshops. I think that the core mentioned also one of the obstacles we are seeing is the lack of time. So do I have time in my day to day work to to get a to get knowledge about AI? Can I take the training or is it am I too busy and what we see is actually most colleagues are feel they are feel they are too busy to participate so what we do is actually if we have the two hours workshops or the full day. We can we can give them a lot of info there and some training. Yeah. Thank you. And maybe just a reiteration on the whole why you're doing this because you are spending time you're spending money on AI adoption. It's a focus for you in your corporate strategy on AI. Why? What what is it you want to gain as an organization as a company going back to the benefit realization? We want to be the most digital player and we know for sure that AI will be a generative AI is is is a part of our new IT tools in the future. So we want to make sure that our employees our colleagues are able to use these new tools and and that we keep being ahead of all our competitors in the market. and I think that this is actually something using these tools is is increasing our competitive advantage. Thank you so much more. Thank you. All right. So thank you to Morten for the insights and the learnings about Sender Groups AI adoption journey. We hope that you've been inspired to actions to take to boost adoption in your organization. We are almost there. Almost done out of time. And we've gone through the characteristics and barriers of generative AI adoption. We've also given you a short introduction to implement best practice generative AI framework. And you've been inspired with a concrete case from Simla. So before we wrap up, we would love to know what you would like to hear more about in upcoming webinars about AI adoption. You see six themes on this slide. Please write in the chat. Please write in the chat which ones you find the most relevant for you by writing the number of the theme in the chat. I'll just read them out loud for the ones that are in cars or maybe on the bicycle listening in one building and leveraging management ownership to effective communication for adoption three culture cultivating cultivating an organizational AI culture for designing and delivering impactful generating generating AI training. Five, how to approach performance management of your adoption efforts. And six, best practice in UX and functionality within Gen AI tools. And while you submit your answers, we would like to take the opportunity to thank all of you for dialing in this morning. The presentation from today will be sent to you all, as well as a small gift from us, an interview with Rick Maurer, a thought leader on change management, on how to overcome the barriers of AI adoption. Thank you so much for tuning in. We look forward to seeing you again in upcoming webinars and have a great Wednesday, everyone.