AI & AGI Reshaping Business Transformation: Bridging Strategy & Execution

In this episode of Digital Transformation and AI for Humans, I invite you to explore how AI & AGI are reshaping business transformation at unprecedented speed, together with my fantastic guest from Stockholm, Sweden - Ingo Paas.

Ingo is CIO & CDO at Green Cargo I Global, EMEA & National CIO and Technology Award Winner I a Visionary and Book Author.

With Green Cargo being Sweden’s most experienced rail logistics provider, handling 20 million tons of goods annually with 98% electric train operations, ensuring minimal climate impact, Ingo brings a unique perspective on sustainable digital transformation.

🔑 Key Topics We Discuss 👇

• Bridging Strategy & Execution in AI-Powered Digital Transformation
• How AI is Drastically Shortening Business Transformation Cycles
• Composable Enterprises: The Future of Modular, Adaptive Organizations
• AI-Driven Decision-Making: From Intuition to Data-Augmented Leadership
• Scaling AI from Proof-of-Concept to Enterprise-Wide Impact
• AGI's Potential in Reshaping Business Models & Leadership Structures
• Workforce Transformation: Creating Human-AI Collaboration Models
• Future-Proof Leadership: Ethical & Responsible AI Adoption

🎧 Don’t miss this insightful conversation on how AI & AGI are shaping the future of businesses!

Connect with Ingo on LinkedIn: https://www.linkedin.com/in/ingo-paas-aa655a9/

Ingo's book "DIGITAL COMPOSABLE ENTERPRISES: An Evolutionary Approach to Innovate Organizations from the Core of the Business": https://www.amazon.se/DIGITAL-COMPOSABLE-ENTERPRISES-Evolutionary-Organizations/dp/B0C2RT9GY4

About the host, Emi Olausson Fourounjieva
With over 20 years in IT, digital transformation, business growth & leadership, Emi specializes in turning challenges into opportunities for business expansion and personal well-being.
Her contributions have shaped success stories across the corporations and individuals, from driving digital growth, managing resources and leading teams in big companies to empowering leaders to unlock their inner power and succeed in this era of transformation.

📚 Get your AI Leadership Compass: Unlocking Business Growth & Innovation 🧭 The Definitive Guide for Leaders & Business Owners to Adapt & Thrive in the Age of AI & Digital Transformation: https://www.amazon.com/dp/B0DNBJ92RP

📆 Book a free Strategy Call with Emi

🔗 Connect with Emi Olausson Fourounjieva on LinkedIn
🌏 Learn more: https://digitaltransformation4humans.com/
📧 Subscribe to the newsletter on LinkedIn: Transformation for Leaders

🔔 Subscribe and stay tuned for more episodes

Transcript

Speaker 1: 0:00

Hello and welcome to Digital Transformation and AI for Humans with your host, amy. In this podcast, we delve into how technology intersects with leadership, innovation and, most importantly, the human spirit. Each episode features visionary leaders who understand that at the heart of success is the human touch nurturing a winning mindset, fostering emotional intelligence and building resilient teams. In this episode, I invite you to dive into bridging strategy and execution and discuss how AI and AGI are shaping business transformation at unprecedented speed, together with my fantastic guest from Stockholm, sweden, ingo Paas. From Stockholm, sweden, Ingo Paas. Ingo is CIO and CDO at Green Cargo Global, emea National CIO and Technology Award winner, a visionary and book author. Green Cargo is Sweden's most experienced rail logistics provider, with roots tracing back to the origins of Swedish rail transport. The company delivers sustainable logistics solutions and plays a vital role in Scandinavian business, with 98% of transport operations carried out using electric trains, ensuring minimal climate impact. Green Cargo transports approximately 20 million tons of goods annually. Welcome, ingo, how are you so great to have you here today.

Speaker 2: 1:31

Thank you so much, Amy. It's a great pleasure being with you today, being on your exciting podcast.

Speaker 1: 1:37

Thank you so much. Let's start the conversation and transform not just our technologies but our ways of thinking and leading. If you are interested in connecting or collaborating, you can find more information in the description below. Subscribe and stay tuned for more episodes. I'd also love to invite you to get your copy of AI Leadership Compass Unlocking Business Growth and Innovation the definitive guide for leaders and business owners to adapt and thrive in the age of AI and digital transformation. Find the Amazon link in the description below. Ingo, I have heard so much about your achievements. I've seen you in action on stage and it is inspiring. It is really something special. So I would love to share with our listeners and viewers more about your journey, about you. Could you please tell a few words?

Speaker 2: 2:34

Yeah, absolutely. I think you know, success and what we call achievements in life is always depending on, I think, meeting the right people at the right time, having the opportunities and then also making the decision to take action on finding doors that actually fit you best. And I think I'm a very lucky person because I met exciting people, people I learned from and I had the opportunity to work with different companies to see how you can approach customers and business problems differently, and I think that love actually brought me to Sweden without I was ever planning for it. So, coming from Germany, from my home country, and now living in Sweden for more than 20 years, you know these are things that happen. But to some extent, I think I was involved in this journey. So I made some tough decisions and I think that I learned a lot and grew with those experiences.

Speaker 1: 3:38

Amazing. It's truly inspiring and I agree it is a lot about your own decisions in life, but there is another part as well, where you get lucky enough to meet right people at the right moment and be in the right place, and then you can enable yourself and others so much more. So that's fantastic. Ingo, the speed at which artificial intelligence and AGI are transforming industries is unprecedented. From your perspective as a CIO and an award-winning digital leader, how do you see businesses balancing strategy and execution in this rapidly evolving landscape? Can you share a real-world case where AI drastically shortened the transformation cycle?

Speaker 2: 4:35

I think that we have seen a lot of AI transformation in the last couple of years, but I would basically relate back to those companies that are bringing innovation to the world, big tech companies. I think this is where we see that they understand the technologies and the power of innovation. They know how to adapt the technology to drive business, and we have seen a lot of companies we've never actually heard about and now they are dominating the global tech landscapes, such as OpenAI, and I believe strongly that many companies are doing great with AI, but there are very few standing out. So I'm not sure if this is a landscape where traditional companies really do something very special or very different.

Speaker 2: 5:29

But I think we're all looking to the tech industry, what's happening, especially in the US, and I think the challenges that we see when we look at the business landscape and the way how companies are approaching AI is that they're confused about. You know, what does AI mean for their business strategies? How would they do dynamic alignment and integrate AI into the future, and how should they think about AI-powered business and technology architectures that are needed to transform businesses, not just finding an algorithm or deploying an AI capability. There's so much more, so I strongly believe that to balance business strategies and to bring rapid change in the evolving AI landscape, organizations are not really prepared for making this move. So I would rather say I look at the tech companies in the world as good examples.

Speaker 1: 6:33

I totally agree. From what I see and hear from other leaders, there is quite a bit of frustration around these new technologies and their implementation. And now we're already at the point on the timeline where organizations are going from the stage of piloting into a stage of rolling them out. And, of course, leaders are dealing with something quite unpredictable, very new, and it is not always easy. But it's also about developing ourselves as humans to match those technologies and create that success in the long run. Your book Digital Composable Enterprises introduces a visionary and evolutionary approach to innovation at the core of businesses. How does artificial intelligence, and potentially AGI, enable organizations to become more modular, adaptive and resilient? Are there standout companies already mastering this approach? You already mentioned that there are those we are looking at, but could you please mention them and tell us more about your approach?

Speaker 2: 7:50

Yeah, I think so. The question is still difficult to answer, but I think here we can find examples that are sometimes examples no one would look into. I know that recently. Jack Morgan has said yesterday they are heavily investing into AI and they have made great progress. The biggest bank in America. There are always companies that you can highlight and look into, but it's difficult to look from the outside what they do. So it's not a fair statement from my side to say they do good or great or whatever.

Speaker 2: 8:25

I could actually refer to some of the work that we are doing at Green Cargo. It's a very traditional business. The sector, the industry is not a typical industry where you would find innovation in terms of digital transformation. You would not look into this industry to actually find good examples on AI and I can tell you no one in our industry has made that leap From an AI perspective.

Speaker 2: 8:55

Green Cargo has applied quite different strategy preparing for scalable deployment of AI capabilities from the core of the business, but building and preparing for this moment to happen without knowing it will come. So what I'm referring to is the foundation that we build at Green Cargo. It's a digital infrastructure and we actually got the European Middle East Africa award from IDC in late 23 for building the best, according to their definition, digital infrastructure for future digital enterprises. So they looked at what we've done and gave us this award and we were very proud about that achievement, but at this point of time we still did not really think about how important it will be for the future of AI. So what we've seen the last two years now is that AI is scaling in a way that very few people have actually prepared for. But we are now lucky to say that the infrastructure we built is a composable infrastructure based on we call it decoupled architecture, the systematic approach to bring platforms together, very different platforms, to build the foundation for future AI, and what we actually do with these platforms. They allow us to adapt and augment disruptive technologies, especially large language models and knowledge graph technology Quite important for us and in our business to work on a revolution on how we look at the problems in our industry.

Speaker 2: 10:37

So we use large language models and in combination with models and in combination with graph technology this is a product called Neo4j I think the best graph database you can find on the market right now and what we do we get nearly all of the data from our business into the graph technology, into the database, and that is customer data, that is performance data, that is data from the infrastructure, the whole infrastructure network of Europe, every single meter, is in the database All of our assets, the wagons and the locomotives and the competence robots, our people, the customer contracts and the customer orders, and we are now building up this information. We moved from a sandbox environment now into a production environment. They're very close to start the first, I would say, solution in that environment and this is kind of revolutionizing the way we look at solving business problems. In fact, what we have built is the first step towards a new foundational platform in our architecture, which is including AI, semantic, generative and agenda capabilities. So these three capabilities are the foundation for our future in AI.

Speaker 2: 12:02

We are building right now a digital twin of our business model and we will be able to use that digital twin to simulate and work with all of the events in our network in real time.

Speaker 2: 12:15

This is a kind of innovation I haven't planned for, but I'm very happy that, with the great people in my team, in my organization and the people who helped us on that way, to have an infrastructure that allows us to augment these technologies and scale from the inside out only scale AI into the future so we haven't done it, we are on our way here but also to use these capabilities to improve other platforms that we already have, such as our analytics platform. Suddenly, we can give real-time data, event-driven data, to our analytics platform and synchronizing all of the data of the company on that holistic level. So it's a kind of you know, innovation at the core of the business, from the core of the business, from the core of our digital infrastructure. I think I use this as an example because I know about it and I was part of it and I'm still really looking forward to see this flying. Would that make sense to you, amy?

Speaker 1: 13:26

Thank you so much for sharing Ingo. This is such a powerful example and it is built by you, and now it is a reference case, success story for so many leaders all over the world, and congratulations to your award. That is an amazing achievement. You know, it's not only about technologies and building those future-proof, future-ready solutions, but it is also about the leadership, and you are that leader who took your company to success and prepared to the future by introducing new solutions, new processes, connecting the dots and seeing what's next to come. With AI-driven insights, executives are shifting from God-based to data-augmented decision-making. What are some of the most powerful use cases you've seen where AI has redefined strategic decisions at the executive level? Let's talk a little bit more about the leadership part. How should leaders evolve their mindset to co-create with AI rather than resist it, and to enable their business growth through technologies?

Speaker 2: 14:49

These are very exciting questions and I think, maybe before I answer your first question on examples I think that leadership and you really focus on that particular capability is core in the digital age. So leadership is still one of the most important things that we need to work with and try to be better with, because, when you look at the constraints of today's business and today's organizations, the balance between driving innovation and sustaining existing capabilities so the maintenance, with other words, the innovation, the exploration they need to be in balance. This is very difficult because what we are seeing now everywhere is that leadership is constrained by rigid definitions of policies and law and all of these things that are coming and suddenly challenging us as a leader to drive innovation. We also have the kind of financial implication that, as a business, you always have to make sure you deliver this return on investment, on the money you use to build something new. You really want to make sure you get a fast and powerful ROI, but most of the time, we are forcing ourselves to agree that a fast ROI is better than a scalable one, because a scalable might be difficult in terms of taking a risk. So risk-averse leadership is quite important. It is significantly important to transform our thinking in terms of investments, and investments need to have that element of scalability.

Speaker 2: 16:44

You can call it a scalable investment strategy, whatever, but my vision, and based on what we've seen at bring cargo, you don't need to talk so much about it, but you need to make sure that when you do investments, you do not only focus on roi. You make roi possible, but you also use it to build platforms. So you have a problem. You get some money should solve it, don it? Don't just run a project. Run this project on a platform and, if you do not have one platform to solve the problem, build a new one by using the money from that project to start building the platform. And the idea is that when the next project comes and the next problem should be solved, you look at your platforms and find out oh, I have a platform to solve that. It's going to be much cheaper, you're going to come back to the short ROI, but the investments become scalable, so you can start benefiting on the foundation you've built.

Speaker 2: 17:46

And I think this is a leadership problem that is very argumentative. This is a leadership problem that is very argumentative. So you need to be prepared for those discussions or to have a leadership approach that would allow you to do this without having those discussions. You need to find a way to use the leadership to drive this change, and I think, when you asked me for examples of powerful use cases, we all know that fraud management is a key AI capability within the finance industry, so that's also important for insurance companies. So these kind of things are there. These are algorithms that have been built to solve a particular problem, that have been built to solve a particular problem.

Speaker 2: 18:34

I think that use cases should more look at the challenges that we see as leaders in terms of building a transformative investment and a plan to make a change to the traditional business model, because the AI-powered decisions that we would like to see are not existing in our boardrooms and are not existing in the executive teams because AI is not really there, and I think that resource allocation and these kind of questions are not being addressed by AI. We also do not see AI to create business model innovation optimization. Maybe the green cargo example is a good example of that one, but we are still in the early days and we're also having lots of great cases in the supply chain and logistics. I can see this from Green Cargo.

Speaker 2: 19:29

Ai can help to establish a much greater scope of the logistics chains and including the entire value chain, and building collaboration capabilities and optimization capabilities very different to what we have today, and we can go beyond cybersecurity and quantum computing really giving us a hard time in years to come. So how do we make sure encryption works when it's easy to break any encryption in seconds, compared to now when it takes many years if you can break them. So there's a lot of use cases for AI. It will not stop, but I think the majority has not been done and I don't think that average enterprise has a plan to make that work. Would you agree?

Speaker 1: 20:23

Totally, and I really appreciate that you not only highlighted the existing challenges, not only highlighted the existing challenges, but also opened up for the ways to solve those problems and approach those challenges in a proactive, future-proof way, so that organizations can learn from your example in this case and from example of other companies who are using their vision and preparing from the perspective of their investment, from the perspective of what's next to come and what they see is really important what matters most to be ready when the time comes. And the question is what's next? How are we going to deal with this? So that's exactly still on the level of leadership, and it is up to each and one to decide what is preferred, what is prioritized, and every decision has a price to pay. But in your case, it's really brilliant and I love the way you are navigating this space and the changes.

Speaker 1: 21:45

Many organizations excel at AI pilot projects, but struggle to scale them enterprise-wide. What are the biggest barriers preventing AI from moving beyond proof of concept to full-scale impact? Can you share a case where a company successfully bridged this execution gap? Because you mentioned that you have to prepare in advance and introduce new solutions, but how do you do it in reality and how do you deal with those new initiatives?

Speaker 2: 22:19

A brilliant question I think we all know about. You know what is preventing AI from moving beyond proof of concept. I think the most important word to be used here is fragmentation, because we are still building fragmented AI capabilities. We are building the capabilities around a single problem rather than building a platform. I'm going to just go back to what I said before, but I think in real practice we can see that you know you really invest into solving a problem. You bring all of the technologies, but you build a fragmented thing, and that is something that you will find out will not work as soon as the problem definition is changing or as soon as you want to scale on that problem, and we'll solve other problems with the same investment, will solve other problems with the same investment. But in addition, there's a problem about skills everywhere, from the top-level management down to the people who are sitting and coding. This includes the visionary thinking and strategic alignment that doesn't really exist when it comes to AI, because these barriers are still there.

Speaker 2: 23:26

Fragmented infrastructures are equally important as building fragmented solutions. Data inconsistency and accessibility is the first thing that you hear from everyone, and it's one of the most difficult things to solve the talent gap. So when you start evolving and growing, how do you fill up with talents that you can keep and maintain, because they probably run away after two years? The lack of investments, because there is no money, because sometimes there is no business case. Innovation is always difficult to finance because you will not get the ROI and if you don't have an ROI, which CFO these days would want to give you the money? And then there's often a lack of business value, because you can really prove the value of innovation before you have verified it works, and many times innovation doesn't really give you the outcome as you want it. So I think these are the answers. You know, maybe, why we have these barriers and preventing AI from moving beyond proof of concept.

Speaker 2: 24:27

And the second part of your question you asked me if I could share ideas where a company exists to bridge this execution gap, and I think we can look at the tech sector again. Like OpenAI, microsoft, nvidia, these are companies. They must do this in their normal business operation, because they're not just only deploying cool AI style technologies. These are businesses as well. So they're not just only deploying cool AI stuff or technologies. These are businesses as well. So they're quite successful. So something must be there. This is really stuff that we should learn from, but I haven't really learned so much about the details, so I need to learn more. But I think that you know, when you look at smaller companies, the more there's the hands-on work that we've done at Green Cargo.

Speaker 2: 25:12

So building a digital twin of the core business model in real time and event driven, this is quite powerful, because the next step here is that when you bridge gap in execution, you make it from a sandbox environment to a real working product and then the platform starts to grow. You can add agendas so you can add execution and decision-making capabilities with AI, so agents that will be part of the models. So we could also deploy the model on the train level. So a train becomes a digital domain and all of the components within the train become agents and then they can communicate and talk and make decisions and optimize the network performance, optimize the train performance, optimize the wagon performance. So these are things how companies can successfully bridge the execution gap.

Speaker 2: 26:04

So you need to have a platform that you can scale, because then you can add a generative. You have to semantically add a gener scale, because then you can add a generative, you have semantic capabilities. You add a generative and then you again use generative in this aspect. So this is how you build for AI high-performing capabilities. That would be my advice, and I'm pretty sure there are many hundred other advices that could equally be okay or right to answer your question, but this would be my advice and my view looking at it that makes a lot of sense, really, and I agree, the list of challenges and reasons is really long.

Speaker 1: 26:50

But it's also about recognizing them, knowing how to address them, developing new skills and getting more adaptable, more scalable, and seeing how you can move forward. And while today's AI models are narrow in scope, agi is expected to bring greater autonomy and decision-making capabilities. What potential do you see in AGI for shaping business models, supply chains or even leadership structures? Which industries will be the first to experience an AGI-driven shift? And, just as importantly, how can leaders ensure ethical and responsible AI adoption as AGI evolves?

Speaker 2: 27:40

What a good question. Maybe we should use chat GPT to answer this one and see what the outcome would be.

Speaker 2: 27:48

I love it, but we risk to hear something we might be not ready to hear, in this case, yeah, I could agree with you, but we're probably not prepared for the answers that we don't want to hear. But if we start with a short, let's say a very simple definition of artificial general intelligence AGI because we need to understand that current AI systems are not there. While discussions are ongoing predicting when AGI is going to happen, there are people such as Ray Kurzweil and Sam Altman. They all have different views on it and Sam Altman, they all have different views on it. Some say it's unlikely to happen before late 2038, 39. Others say it's going to happen next year. So Sam Altman is actually saying that in terms of AGI in the business context. So it will definitely change the way I look at AI and these kind of systems. They process human-like cognitive capabilities and they will do this across a broad range of tasks. So I think that you know, unlike the narrow AI that we are used to now, that we are getting happy about, which is fascinating stuff, but I think it's a kind of Mickey Mouse AI compared to what's coming, and it will change the rules of the game, and I think that AGI will probably do the kind of reasoning stuff that we all hear about these days Now deep research and whatever these capabilities will bring, but we will also see a lot of these kind of changes coming smoothly, becoming part of our daily business and daily problem-solving approach by using AI as we move on. So I think there will no one no one will probably be able to say exactly when this is going to happen, but if AGI comes, I think we will see a very powerful transformation and this transformation will change the rules of the game and how the story of the future will be written.

Speaker 2: 29:57

And maybe reasoning is one of the most challenging innovations that we have to deal with. So this is going to be very difficult when you realize that the system is smarter and outperforming the greatest experts in your company telling you the truth about your ideal strategy or optimized decisions in your business, and I think that relates to the question that you asked. The other question, I think it was about how do you ensure to stay focused and ethical, to have responsible AI adoption as AI is evolving. I think that there are many ways protecting innovation. Downgrading this kind of transformative change and the power of AI with these disruptive technologies is not a good strategy, because it will happen. The question is how do we get alarms around this and we have to deal with the risk, but we have to keep the balance.

Speaker 2: 30:58

I'm promoting and I'm very positive about the technology and the changes that are coming, but I'm also very strongly supporting actions to take protective measures in that change. Keeping the balance is important and when it comes to ethical questions, transparency and these kind of things, it's going to be difficult, but I think AI will hopefully be here to enhance our capabilities and not replace us in the beginning. But I think AI will come, hr will come with human capabilities. That will be a major challenge for us and I don't know how these things are going and probably no one knows and and if we find out, I'm definitely putting a lot of efforts into understanding this impact on humanity, on organizations, but also on myself and my family I couldn't agree more with everything you just mentioned, and I agree that we don't know exactly how it's going to go and when that moment will come, where the world is changed and the roles are also shifted.

Speaker 1: 32:38

But it's really good that you mentioned human centricity and how it's going to develop, because there is a lot of talk about AI augmenting human potential rather than replacing jobs. But what are some successful workforce transformation strategies that organizations should adopt to create human AI collaboration models? Maybe you can share a real-world case where a company successfully integrated artificial intelligence into the workforce, enhancing rather than disrupting human capabilities. And how should organizations overall approach reskilling at scale to prepare employees for an AI-augmented future, because a lot in this development still depends on us and what we do along the journey. So it is great to see this through your eyes and hear it from you.

Speaker 2: 33:38

Okay, based on an article from Wall Street Journal I think I talked about it before JP Morgan's approach to AI integration and employee empowerment is something that they deployed for, I think, most of their staff. So these are, I think, 100, if not 200,000 employees in the company, and they've done this in correlation with OpenAI. So if you work with the leaders in the field and you think that you would want to transform your workforce, it is obviously a good idea to start and invest into this kind of capability If you are having a workforce of knowledge workers. Otherwise it would be more a kind of supportive tool and you do not need to know so much about AI, but you really want to trust AI when you use it in making your decisions. But if it's about knowledge workers such as JP Morgan, so I would think that this is a great example of building this kind of collation with a company such as OpenEye and then transform your workforce, because that will make human labor available across the organization, will help them to differently, because the AI will reconnect skills and reuse it and help everyone to be better, and it will help to upskill employers and redefine their roles and definitely help them to foster a culture of continuous learning.

Speaker 2: 35:07

So I think it's probably very good and it's probably very important. So I think it's a great example, without knowing much more than just reading an article. So I'm only repeating something that I have read. I I haven't seen it, but this is amazing to me and the re-skilling things that we really want to consider in the future if we want to empower workforces. It is AI-augmented skill development, whatever it could be, redefining work and organizational structures. It could be working with the culture and transforming the culture of continuous learning, co-creation, collaboration, decision-making and, at the end of the day, it all comes down to make sure that you still are in control about the outcome. What is going to be probably one of the biggest challenges and things we have to work with.

Speaker 1: 36:05

Definitely it's going to be increasingly difficult, but it's also increasingly more and more important to keep in mind that we are in charge for the outcomes and we have to feel ourselves as somebody in the driver's seat as long as it works, because we don't know exactly where this table will just turn and the roles will be completely different.

Speaker 1: 36:40

Because yesterday I was listening to a conversation with Grok, the latest model.

Speaker 1: 36:48

It doesn't sound like it's going to take a very long time until the roles really shift and we discover a completely different world. We're living in very exciting times, you know, and it's really interesting to feel that feeling that we really don't know how the world is going to look in three, five years and Brock just fortified and supported that understanding that it's really impossible to know how everything is going to change in this very short period of time, because those models are also seeing it as a window of opportunities to develop, to grow, to learn more and to impact our world To the better or to the worst. It's a question for the moment and we're going to see it quite soon, I believe. I so appreciate everything you just shared and it's going to be very helpful for so many of our listeners and viewers. Ingo, could you give one future-proof piece of advice to leaders navigating AI and AGI-driven transformation? How can they embrace AI as a strategic co-pilot while ensuring human values, ethics and trust remain at the core of their decision-making?

Speaker 2: 38:31

A tough final question, but giving advice to others is always difficult because you know there are so many people out there who know better and have more experience. Whatever I think that here comes my advice. I want to split it into two things. The first one is that AI is a tool for empowerment, not replacement, at least in the years to come, and it brings a transformation, shift of power, but requires a strong foundation. And the second advice is that if leaders want to succeed supporting their organizations to from history into the future Because what you have seen in your history in the last 20 years of business experience or 25 years or 15 years as an executive, is not enough to understand what's coming so predicting the future based on your learnings is not enough. This would be my second advice, and I think that one goes to very many people out there and I hope that even I will be better on that in the future. So thank you, emil. This was a very interesting conversation.

Speaker 1: 39:56

Thank you so much, Ingo. I so appreciate you sharing your wisdom, your experience and this advice, and it's really amazing how the world is impacted by the latest technologies and how much we can do as humans to transform business and life. So thank you so much. I really appreciate you being here today. Thank you for joining us on Digital Transformation and AI for Humans. I am Amy and it was enriching to share this time with you. Remember, the core of any transformation lies in our human nature how we think, feel and connect with others. It is about enhancing our emotional intelligence, embracing the winning mindset and leading with empathy and insight. Subscribe and stay tuned for more episodes where we uncover the latest trends in digital business and explore the human side of technology and leadership. Until next time, keep nurturing your mind, fostering your connections and leading with heart.