A very warm welcome to my session. I'm happy to have you here.Just give me a note if you don't see the screen, but I think it should be alright. My topic today is, empowering exploration, building AI literacy in your team for a future ready organization. Why is this so important and, what do I mean with that and, why do I speak about this at a women's conference in particular? You will find out in the next, minutes. And, I hope also to to interact with you. I have, prepared some polls to also collect your input and, the session is really meant to be to get you started on your team, how can you empower your team.

And, also, there is some some questions for you to reflect and also to prepare what is coming up in, yeah, in your team, how can you empower your members, and, give you a little bit of guidance and, get them hands on afterwards. Who am I? My name is Jutta, Jutta Schoonlow. I have the honor today to be here. So I was, invited to this conference, and I'm very happy that, I'm speaking to you today and can offer this session. I am based in Munich in Germany. I am a Munich local. I have twelve years of experience in sales and marketing, and, my current job is with a, semiconductor company. You see it at the right bottom hand. It's Infinium Technologies, and I'm, leading the sales and marketing operations team in one of the three segments, which is the consumer computing and communication sales segment in our company.

It's a global role and making sure that our sales and marketing teams have everything they need in order to drive the business. How do I use AI personally? So, of course, in in my private time, but then also very much in the business context for content generation. And I'm very much looking into use cases for automizing data in sales and in customer interaction since I'm very much in a sales and marketing role and very customer facing and customer supportive. That's, what what I'm looking into and where I really wanna, leverage these, tools and make sure that also my team has everything they need to, make best use of it and increase efficiency, but also effectiveness and, offer better quality of service to our customers and also make best use of the data we have inside our company.

If you wanna connect, you can do that, with the QR code, on the lower right hand side. Feel free to do that, and, happy to then also follow-up on this discussion with you afterwards. A little bit about myself so you get to know me, more than just on picture. I have several passions. I'm very much into learning and into innovating. So I believe that education is the basis for success. A good education is, helping every one of us to get where we wanna be, to be able to express ourselves, to be able to learn, how to, do problem solving, to dive into content. And, it's really the foundation for success in in the job. And also whenever you have entered in the business world, I really believe lifelong learning is very important.

And with the changes that we see, it's very important also to adapt yourselves and say, okay, what new skill sets do I need? How can I use the skills I already have and build on them? And what additional ones do I need to work on? And, I'm very curious. I'm I'm really driven by, finding new ways of how to drive business and simplify operations. So I really am very much driven by setting the right focus, setting the right scope for our day to day work, simplifying things where we can organize things in a in a way that we have our hands free and full our full attention on what matters most. This is, very much on the learning and innovating part. Then in the center, you see leadership and empowerment. This is, what is really crucial and elemental for me is, I have been leading teams for for several years, and I always nudge my team a little bit out of their comfort zone.

I also do this with peers, by the way. They they come up to me, ask for advice, or or share some some of their stories, and I always encourage people to step a little bit outside of their comfort zone, learn a little bit more. And, at the same time, I don't leave them alone. I'm their biggest fan. This is why we have here the the picture with the cheerleaders. So I'm really on on the sideline coaching and and, money mentoring my team and, really cheering them up, whenever they they have successful, and it makes me super, super proud to see how they evolve. Then on the right hand side, also about myself, a very personal topic, which I do in in my free time, so to say, Since I'm coming from a very, yeah, rich country in the world, being very privileged in my life, I also wanna give back, to the world, and this is my way of doing is via UNICEF.

So I'm a volunteer there, and I advocate very much for children's rights and for sustainable development goals. So that's very important to me. I go in schools with my team here in in Munich, with the UNICEF group, and we educate school kids and teenagers on children's rights and, make sure that they reflect and they know what what is right in the world and, can really, yeah, make a difference on their own. So each individual person can really contribute on making this world a better place in terms of how we behave, how we act, and also drive sustainable behavior in this world. And at the same time, also a sort of balance to the the job I have, I have become a yoga instructor a couple of years back, and I like to do that also in my free time to give classes on yoga. What are we doing today? I will introduce you to the the chances of opportunities, in in this world when it comes to, AI, but also overall when it comes to learning.

I will create a sense of urgency for AI literacy. And then I'm very curious to see how, is the AI literacy rate, in your team today. And then explain to you how, my way is, on establishing a culture of exploration and then empowering AI champions. And beyond that, when we talk about exploration, which is already a big step, I will also introduce the concept of ambidexterity, in the context of AI and then give you some guidance of how I would or how I develop a tailored AI literacy program in my teams and thank those with some key takeaways.

Yeah. I said that the chances and opportunities have never been greater in this world. So no matter where you come from, what your background is, where you live with the, access to the digital tools and with access to AI, we have such a great potential and such great opportunities, and, we should really jump on the train and leverage those. Here you see the market sizes on the left hand side for AI in general and on the right hand side for generative AI, so everything that is, producing content or generating text, images, music, whatever you can imagine. And, it's really a huge huge increase what we predict in, the coming years. So in the next five years, that the markets of both are growing really tremendously. So we wanna be part of this evolution, I would say, and make sure that we're equipped with everything we need to be part of it and, to scale it into our organizations. And I want you to be to be part of this. Yeah. Sense of urgency. So you see the market numbers. Market is really steeply increasing.

And, also what we we see when we ask or when this survey was conducted in, what we see is the adoption rate in organizations worldwide in the past years to 2017 to 2024. Adoption of AI in general has been going steeply up, and 2017 was very new. Then it has sort of, ridden the wave, on on a more between fifties and sixties. And then in 2023 to '24, we saw a steep increase. And also with the introduction of Gen AI, we saw really a steep increase from '23 to '24. And, this, I believe, is going just to continue like that. And, yeah, it's it's really showing this this this growth and also this jump from GenAI in particular is showing that it's not just, something which is, for a certain group of this world or certain members, but it's really, becoming more mainstream and it's, becoming a very widely used tool in companies and across the world.

And this is why, it's very important to know what we talk about and also to bring it in our teams. And I know it from from myself, from my own experience. There are some people who who were early adopters, so to say, and started with AI in in the very beginning and, we're just testing it. And there are some who are more laid back and more observing at the beginning and asking themselves, okay, where will this trend lead? What are the risks? What are the concerns? And, all of these, the the enthusiasts and more the the ones in the waiting position, we wanna get all of them on board and make sure they are equipped with the skills they need so that they can thrive and contribute to the organizations.

Yeah. Then also companies were asked, what is the biggest barrier to, AI adoption in companies? Why is it maybe taking a little bit longer, and why is is it not not increasing as expected? And interesting enough, the first reason or the highest rated reason, as obstacle is the lack of skills in companies. So not every company believes or 50% of the companies believe they don't have the right skill set for AI adoption in their company, which is quite a big number. So let that sink in. And then the second highest rated point is, the lack of vision among the managers and leaders, so which is us, right, as team leaders. And this is something we can also change and we can also shape and say, okay. How do I create a vision for my team? How can I use AI?

How do I generate ideas? And how do I come up with a good use of AI and really drive the adoption? And I think this is especially these two first points is something where we can clearly work on, where we can, make a difference. So lack of skills is something that is perceived by the companies, which we wanna change, and then also, make sure each one of us has a good idea of how we can make use of this, technology and also then make it visible to our management, to their management, and then to to the top level of company.

I think that will be very valuable going forward. And each each one of us can contribute here. Good. Since we're at a women's conference today, I also had a very particular look on, the skills of, women in this, world, when it comes to AI. And I found this very nice picture which I wanted to share because it really shows that also women are in the lab. Also women are working on this very innovative trend on humanoid robots, which is coming mainly also in in out of China, which is super exciting and, highly innovative and, where AI really plays a huge role in in training these robots that act like human beings. So what what is the skill set and how do women compare to men, in this, in this global context? And here I found a study, which is, wide span across many, many countries. You here see the the top countries, but this this list is much longer.

And it shows the the difference between females and males, so the females in black and the males in blue. And you can see that in overall, in India and The United States, AI skills of both genders are more developed and more penetrated. And, also in those countries, women have the highest penetration rate by far compared to all the other countries in the world. So India with 1.9 and United States with 1.7, a really exceptional high in terms of penetration rate when it comes to AI skills, and then followed by by really distant Canada, UK, Germany, Brazil, France, and so on. What is also really striking is that, in all countries in all countries, I think I just found one where it's not the case at the very bottom on a very tight, high level. But in all countries, let's say, the the men in this world have a greater exposure to AI.

And, this is really something that is striking, and, this is why I'm I'm really advocating and encouraging every woman to jump on the train, get familiar with the technology, and develop some skills. And, this is something where where I encourage every team leader to have a special look, special eye on, the the women in their team to make sure that they also understand the importance of AI and that it's it's easy and fun to get started and to use it. Also, when we look at the right hand side at the second graph here, it's, it was a survey or it was a statistics on the apps that have been downloaded with relation to AI, so the AI related apps. And it was shown by, kind of type of the app. What does it do? If more men or more females have downloaded them, and here it's really striking. And it's really a very clear result that, between 232489% of the of the apps, especially on utilities, were, downloaded by men. So the usage of men is striking. And, the only thing where where women have a share of at least 30%, which is the highest already, is on educational apps.

But everything else when it comes to support and writing tools, photo and video generation, yeah, music generation, etcetera, is dominated by males. So this is also very interesting, and I think we we can make a difference here. And with that, I invite you to, take part in this survey. So let's see if that works. It's a survey on on Menti, for some of you might know it. So scan the QR code and then, you you will get all these responses and you can choose, several ones to to let me know which competencies you have within your team. So what are your team members capable of doing? And, on a ratio, so are they more, on the side that they have never touched AI or they're a little bit overwhelmed or maybe also scared?

Or on the other extreme, do you have people in your team who have implemented maybe an AI tool already or who are into coding or even even one step further who are developing AI tools, in in your team, in your company. And with that, I stop sharing for a second to make it a little bit smaller so that I can look at the results of the poll and, see how it's how you're answering the questions. And if you don't have a team, that's perfectly fine. You can, look around what is what is right, what is left, what are your peers doing, are they engaging in II or or a little bit less. So please answer. I hope that it's working. Oh, I just see in the chat that you had some problems with the slide. That is weird. That is weird. Let me just share again so that you get the QR code, which is a pity. So I hope it works now.

Just give me a heads up that you shared see the screen. Okay. Perfect. Rather late than never. Good. I will go in full screen so that you can scan the code, and then I invite you to to do the poll. And then I have to to go back to the the browser and, see the results. Give you a second also to to reflect and to to see how you wanna respond on the AI competencies you have within your team. Then let me check. So I see people responding. Very nice. Great. Yeah. We're going to to full screen right right in a minute again after we finish the poll. So a few more seconds to give you the chance to answer, and then I will show the results. Good. Let's go back. And, these are the results we see.

Go back to presentation mode. Yeah. We have a mixed picture, I would say. So, the feedback you have given is, many folds. We have some, and I think here the biggest portion is very curious about AI, which is very good because I think that's the starting point that, we have here a good portion of people. Oh, yeah. I wanna know more. At the same time, also, we have, re responses here more on the the Apple side. Okay. Some in your team might not have touched AI so far or they're overwhelmed with the tools or even some are scared or even seem to be scared or admit it openly. And then when we go, here, we have also 17%, already experimenting with AI tools, which is great, because there you have the first experience then and, you learn more. And then, what what I really like is also tutoring others on how to use AI, these 4%, because those, can be ambassadors.

Those make a difference in your team and, really show that people can learn from from others and, you have some which are which are leading the pack, so to say. And, also, what what I really like is bringing ideas how to make use of AI at work or defining use cases or even here 8% have already implemented an AI tool in the system. So that is really great. And this is then really also on on, how to apply AI in the business context. So here more on the the upper part or here the right side of the circle is getting started, being scared, overcoming, something where you say, okay. I don't even know how to do it yet. And then you move into getting started, trying it out, experimenting, teaching others, and then also scaling into the organization. So it's a very good mix. And, thank you for for sharing, how, the composition of AI literacy or skills is in your team.

With that, I wanna move forward into how to establish a culture of exploration. So exploration is a term that, refers to new things. It involves searching and involves, yeah, a little risk taking, and it's very much about, trying, experimenting, also in a very playful way and discover something new and really looking for innovation and and looking into how can I disrupt this industry, how can I find a product or developing something which has not been there before?

And I think a good example, this is why you have it on the right hand side, is, landing on the moon or discovering really new planets or looking and searching for for life, which is, not on our earth but might be somewhere else in the universe. This is, I would say, an extreme case of of exploration. And this is, combined with a lot of invest, a lot of time and effort spent, and the outcome is uncertain. But, it's very connected also with a growth mindset, to be successful in exploring new ways and, new ideas. And when you say, okay, I I try it. I dare to die dare to try. And even when there is a setback, I'm not discouraged. I try again. I try to make it better or different, and, this is very much, what exploration is like.

And then when when it comes to AI, this is something, where we all need to experiment. We many of us start from scratch and say, okay. How can I make use of this? What is it? How how can I really start engaging with it? And, this is very nice that, this is possible. Yeah. When how can we make use of this? How can you make it a habit or implement it in your team that this exploration has a a place in your team? And, what what are some ideas which which I can share with you? So for instance, there's some, AI exploration sprints, which I can suggest where you can have some kind of a team challenge where you say, okay.

I have a very specific topic and, it's, the the scope is, very well defined, and it's it's a on a smaller scale. And AI can potentially have a very positive impact if you use it. And then you give them a rather short amount of time and, come back with ideas how AI or which tools could make a difference. And, yeah, set up sort of a challenge, and then they come back after this one or two weeks with their ideas shared in the round. And, you will see that, out of a sudden, they they have a clear scope, a clear clear goal in mind in what way they will search for AI tools. And I think that's making it easier than just opening up the whole wide set of hundreds of different tools saying, okay.

I have a very specific topic I wanna solve, which is business related, and what can you come up with? Because then it's really targeted to a certain, idea and to a certain challenge. And also really debriefing then in the whole team, will then have the benefit that they learn from each other and, that you can share the very different approaches to the same problem are being shared in the team and also, fostering the creativity and inspiration among each other.

Then, what is also something I have, done in in my team is the so called I a AI showcasing sessions. And, this is something where I invite team members. We we do it once a month, for fifteen minutes. So I call it the quarter of an hour for AI. And they showcase and share how they experiment with AI. And it can be in the private sector. It can be at university. We have some students with us. Can also be in the business context. No matter what they wanna share, and it's it's more hands on. And they say which tools they have been using and what was the outcome they have, achieved. And it's a it's a practical and interactive session, very short, just pitching the idea, pitching what they can do. And it it was a tremendous success for us.

So really eye opening. And, the the youngsters learn from the elderly ones. The older ones, learn from the youngsters, and everyone has a very different angle and different innovative ideas what to do with it. So, this is something I highly recommend, and it's also fostering learning from each other. And we have created this safe space, so there is no right or wrong. It's really about, collecting ideas and, could yeah. Bringing together what can be done and showcasing. And, then when you wanna be a little bit more sophisticated is, also when when you know a little bit better what, what experience levels you have in your team, you would then can go a step further and really define a role based, AI learning path in your team. And for this, you would need to know, okay, what knowledge and what what skills would you need with your teams? What do you want them to be capable of.

And this can also differ role by role in your team. So, it's not the same probably for everyone and also the starting point for each person might be a little bit different. And then it's about, helping them to, find the right, material to learn. It can be courses, it can be articles, it can be tutorials so that you guide them into what you want them to learn. And, I think here important is to to, define, achievable small steps and, define some milestones with your team member together and, then also say, okay. Be a little bit a companion on the way.

Check back how is it going and, what is easy for you, where do you need support, and, then really reward them and compliment them for each module they, they achieve. And, step by step, you can really expand the scope. And I think this is something, which which I also recommend to to guide them in a certain direction, also to offer them little projects or tasks that guide them in that direction where you want to have them developing AI skills. I talked a lot about, exploration now, and this is very important to get to know this very new technology or maybe not so new, but still new when you look at how many people are using it. And, lately, Arvind Krishna, the chairman and CEO of IBM, has, made a very interesting and very good statement where we say, okay. AI has moved from experimentation to real focus on unlocking business value. So what does this mean?

This means we spend a lot of time on exploring the technology, on doing some experiments, and of getting to know it. And now the time has come that we leverage it into our organization and that we show some results. How do we really benefit? How can we make things efficient? How do we really deliver, and how can we make it measurable and tangible, what do we save, or what do we create by using AI. And this is where now exploitation comes into place because exploitation is the the side, where, you you go into productivity mode. You wanna relay efficiency. You wanna implement. You wanna execute. You wanna duplicate the effort, or you wanna when you have a success story on on one topic, you wanna duplicate it or bring it to another area and do the same again and really scaling the success into the organization.

And this is very much which is then bringing the the efficiency up, but also is then increasing the return on invest on all these activities. And this is a concept, so exploration on the one hand side and exploitation on the other side, what is called ambidexterity in, in science. And it's it's a concept where every company needs to do both. So if you wanna be innovative, first you have to explore the opportunities. But then if you wanna make money with it, you have to exploit and you have to deploy it and make sure it it's running in the company. And, always right. Yeah. On the learning path, learning new things, but then also deploying it and, using this existing or this new build knowledge is is something which which you have to balance and to make sure, and this is not the the statement from from the IBM CEO, when it's time to move from exploration to exploitation.

And, in some teams, we might already be at that stage. When I recall, how you answered the poll, I think some are still already in exploration and getting to know the technology. But just make sure where you are on this continuum, this can also change. Some might already be be more sophisticated and say, okay. I know it. I know what to do, and now I'm I'm ready to, deploy. And some others are maybe, a step, before that. But I think it's it's very important that for business success, we need to move to the right hand side. Yeah. And this is basically the the summary and the thing is how can we accelerate this?

How can we make sure that the learning is happening and all the the understanding how AI works and, the experimentation? But how can we accelerate then coming from the learnings we have in the team and move to, real optimization and realizing the benefits that AI has to offer and making them visible and creating success stories That is very much, important. Good. When we talk about skills, it's, very important, that the use case you have or you wanna realize in your team is determining then, which which skill set you need. And here you see, yeah, different different areas, I would say, where AI is used. And here it's Gen AI, so everything that's content generation, and in in the statistics. So marketing strategy and content support is the highest ranking where currently or last year where where companies were engaging in, what they were seeking to to realize.

Then it's about knowledge management, so hide and seek of all the documents. Who doesn't know this? Right? Personalization, so really, targeting the right audience with the data you have collected and offering them the content on a personalized level. Design development and code creation are very, very important, and, this this goes on. But for you, it's important to keep in mind, okay, what what is it that you wanna realize because with that, you, define that what skill set you need. And here, I give you the chance to to answer the poll on this one because I would be curious what you were trying to achieve, what you were looking for. This would be very interesting for me. Please scan the code, and you can then answer in the background.

And, yeah, with that, I would, really encourage you when you have defined your target, make a training plan based on the analysis. What skills do you already have in the team? What do you need, and then how do you overcome the gaps, what kind of, yeah, how do you get there? How do you get your team there? How can you upscale them? Fostering a growth mindset, we have talked about that before. Every failure is also something where you can learn and encourage that really. And your people say, okay. Try it again. Try a different way and encourage them to keep going. Very much connected to that is reward successes. So monitor how they progress on their way and, reward achievements and share also the achievements in in the team.

And then really scale into the organization, make sure that the AI skills you you build and, the learnings you have are then really contributing to your team's success. And with that, I'm at, the end, and, I wanna thank you very much and give you, these key takeaways to think about. So really, AI skills are key. We have seen that, it's a very quickly growing AI market, and, it's important to empower your team and support especially women on the way because, we have seen then in the statistics, they're not so much exposed to AI yet, not so much experimenting with it yet, that we have a focus here and, that everyone in your team is developing, skills on AI.

Then a very important point is make time for this. Take the time. It it will never come to you, but you make it. It's a conscious decision. Okay. Today, I dedicate for learning. Make it a habit and also advocate for this behavior in your team. And then as I said, scale fast, move out of this purely experimentation and say, okay. What is my goal? What is my plan? What I do I wanna achieve to really, then also come back with the business results and make sure that we that we have something tangible and say, okay, we have realized this and have success stories which are measure measurable. Something for you to reflect on is really what you wanna do. And then at the end, I wanna send you off with a question. What will you have implemented in your team by May 31, so end of this month, that you get started and get into action and what is the step you wanna realize now after this presentation.

And with that, I say thank you very much to, the, Women in Technology Global Conference for inviting me and for having me. It's been a great pleasure being here today.