Hi, everybody. Nice to welcome you in my session. I would, share my presentation. Thank you.My session will be dedicated to, my experience with, driving the AI transformation in the company and, to try, together with my team, make out of our company, AI native and AI driven organization. Over the last year, one year plus, AI have moved, from the direction of being the innovation to something what is becoming fully transformative for, our organization. It is, reshaping, not only the way, how our organization is operating, but also how we are making the decisions and, how we are building our products and how we collaborate together. And from my experience, leading, transformation across the, technology operations and also focusing on the AI adoption in our organization, I learned, something very important. The biggest challenge, I think, not surprising for anybody at the end is not the technology.

The real challenge is, whether we are able to transform our way of working and our organizational model fast enough, as fast, or even faster as the technology is changing. And I would like to share with you today, three major points, about how and what we have learned around transforming, solved group to be the AI first and AI native organization. My focus in the company, which is the insure tech organization of Allianz Group, is mainly as a chief operating officer to focus on the post integration automation where we are having separate and different processes across different companies, and we aim to integrate them into single customer experience.

But my job is also to transform organization through AI at scale and scaling the innovation as such. The three points which I would like today to share with you will be focused on why AI transformation from my perspective fails or opposite when it succeed, which role in this, success or failure at the end place, the the leadership, the trust, and the cultural change in the organization, And last but not least, what is our experience and framework or approach, how we are dealing with my team and with my colleagues to bring the AI into the full impact and scale on how we do the business?

Because at the end, AI transformation and our job as a leader is not to do only AI as a technology, but to redesign how people, technology, and, operations work together. Why these topics, today matter? I think, is, not connected only to the fact that AI is everywhere. But, I often hear speaking with the the several peers in the different organizations. We are now testing, this, cloud code. We are testing, open AI models, and we are doing the proof of concept. But the the reality and the fact is that, everybody, is talking, about first experiences and first implementation while AI is evolving and bringing the new capabilities, new possibilities within matter of weeks, maximum months. However, what I see, also in our organization, but also with the peers is that organizations in which all this technology is landing at the end need for the change and transformation several months and usually even years.

This at the end for me creates, very clearly the gap between how the technology is fastly evolving and how slowly we as a human or organizational bodies are transforming and making ourselves ready to benefit out of it. This tension at the end creates the, the huge gaps which are needed to be considered before the transformation starts in order to avoid the specific pitfalls which we can find during the transformation. If we look on the AI transformation, usually, the most failures are not coming from how the open AI LLMs are operating, or do we have enough tokens. That are technical topics which we can fix very quickly. But the major obstacles and at the end sources of the failures or not relevant results are coming from my point of view from organizational aspect. And I would see usually three types or I saw on the part as we are progressing three types of the major obstacles or three barriers. First, legacy operating model.

The model in which, we clearly can see that the decisions are done. Here, actually, that the people need, special approval of the committees for the innovation, barrier which is connected to fragmentation, to segregated platform, segregated organization across the globe. And at the end, not ready enough culturally the organization to adopt the AI. And this, of course, becomes all these barriers, which we consider business as usual, become especially visible in regulated industries because the governance is much much more stronger. The decision making is much more control. What I have learned, very quickly when we, started to onboard on the first major AI adoption is that, simply, you can talk about AI, but you cannot run iGentic AI on the top of the organizational legacy and fragmentation.

In that situation, AI transformation or transformation of AI organization will fail when nothing on the ground is changing and will fail before even any deployment of the AI capabilities into the production. The reason, which is very strong behind it, is that AI at the end is not changing the technology. It's changing the something what I would say are the structures of the power. It is, changing how the decisions are made because they are becoming or in case of the real success, they are becoming more distributed. The core of what we consider as a valuable expertise is changing. It is not anymore can I called, but can I control the AI agent? Transparency is increasing because, of course, AI agents are not politically correct, what they say and which error they expose.

And at the end, all this together shifts completely what makes influence in organization or how to influence the organization. Different decision making, different core expertise, and transparency at the end leads to the way that the dead people are influencing the organization, which are fast and adaptable. One thing which, surprised me, I would say, is personally the most was that, when and how quickly AI exposed in our organization all the obstacles. So when we started to deploy the first agent, process automation, it became very click click quickly clear what is not working in the current processes, what is not working in the ownership, in the resolution of the product, customer problems. And this is the core which at the end, from my point of view, before we talk about technology and automation, we had have to address. So internal transformation and making the company ready for AI.

Many companies, thinks that AI will come, even my colleagues or my my colleagues in the board are thinking, okay, Luba. This process is very complex. Let's just take AI agent. It's much faster, much smarter. It will fix everything. But the reality is that it's not working like that. This is what also the colleague before in the previous presentation say. The AI put on the top of the legacy process will just multiply the complexity and will accelerate it. It will amplify it. If processes are fragmented, AI will scale the fragmentation. If the trust in the people of the people into AI is missing, the AI will not scale. They will not use it. They will pick up the phone. They will not support it.

And that's why the transformation must happen in organization before the technology is brought in place for automation. Before scaling AI, the organizations needs to define the clear ownership of the initiatives. Simplify the operating model to create the space for AI as part of operating model next to human together with the human. Make sure that everybody trust to the data which are input and the process, and at the end to assure that via transformation, also, the leadership is able to transform its capability. AI, success is not defined by is the perimeter or model or algorithm better. AI success and implementation of the AI in organization is about making core of the organization better.

This is the part of the transformation which usually companies, including our, underestimate the most. Technology can be implemented easily. It is, I would say, commodity. But what is important is it will succeed when there is a trust. When we first time came to the colleagues in operations which are processing motor claims, none of them has asked, okay. Are you using OpenAI or are you using something else? All of them has in the center of their mind only one question. How this will work for my daily job? What is happening with my role? Can I trust the outcome? Can I present it to the customer? Do I still have any value in the process?

And this is what at the end step by step in our AI adapt adaptation in our organization became clear is in the core of any transformation which we are doing. When the people are exposed, they have to be comfortable. They have to be part of the journey and embrace the change to make it theirs, to understand how they are going to benefit from it. And then if whatever technology we do, if the trust is there, we are successful. And here, I think, is the core where leadership, female leadership has fully open space to take over the the way how we lead organizations towards the AI. Because when you are facing the competition between AI and people, the core of the leadership values which can drive this, technological change and cultural change are system thinking, ability to collaborate with all the parts of organizations without the ego, adapt quickly, and build the trust in the people.

And that's what my experience over the years is saying. If we are, as a as a female leaders in technology, strong somewhere, it is to collaborate, to to act as a protector of the people who are not having the skills to think how they can succeed in the future in the new organization. And, therefore, I believe that core of the AI transformation in organization gives the new possibilities to the female leaders to take all the responsibility and empowerment and drive it. When we are working together with my team over the last eighteen months, we are constantly updating the way or the framework, how we engage with the AI and bring AI into our processes. I would say our framework has, one, I would transformational and preparation of, part, and second, which is more technical for the implementation. So I would again amplify what was said by the previous speaker. We always start with the alignments. Where is the value? Where is the out outcome of which matters?

Is it the the call center processes because we are not able to scale when there is a natural catastrophe? Or is the value internal productivity? After we have decided what are the core processes and areas which are the critical for our focus, then we focus on simplification or I call it radical redesign. So to do it like we were never thinking about, to do it from the perspective of the AI agent and to simplify which people are involved, which processes are involved, which technology. When we have simplify, we empower specific people who today do the process to make best out of it and drive the change and bring the change into the next step, which is design of the real AI agent, implementation in the operations, training of the people, and at the end, learning out of it and adaptation.

For me, one thing in this process is critical. Focus on the people and purpose in the middle of all these activities. So in all the transformation, I have just regular meetings which are saying and revising how the people are reacting. Are the people on board? Do they know? Are they trend? Because AI 19 transformation is not about scaling the technology. It's about scaling the meaningful impact across the organization. And this is what we are doing, in our implementations, Repeating this process and this approach in the operations, in the software development or internal AI driven, software development life cycle, and last but not least, in design of our products for the claims processing.

Do we have the KPIs? For sure. But do we have the KPIs which are only quantitative or we also measure qualitative one? Answer is simple. Without measuring also the perception of the customers, Adaptation of our organization and our people, whatever quantitative KPI, improvement of the productivity, improvement time to market, or decreasing the cost will be very short term. And what we see actually, the teams which are prepared, are trained, are onboard, are driving the transformation by themselves, have a much better result, and continue improving the results even in the production on the regular basis. Because, at the end, it is about transforming the people and bringing people to the new organization, which is people and AI together as a hybrid organization working, in our case, together for the people who has damaged card, who are not able to travel, for the people who need our support, and we deliver together the results.

So before, we finish my session, I would, like that you leave this session with the three consideration or three actions. Whenever you are thinking what we can do, how we can improve, improve our way of working, our results with the AI, think in the three direction or take three actions. First, always simplify before you start automation. Second, build the trust and continue building it continuously along the journey. Last but not least, redesign the organization to the continuous adaptability. Bring to the people understanding that part of the organization is change is happening each day and will continue to happen. And as they are onboarding on the new way of working, the mindset which they and we have to create together with them is to be ready to adapt continuously because the future of the organizations which are going to succeed with AI is not the one who are having the best AI engineers.

We'll be the ones which are able to keep the people running along the change and being continuously adapting faster than the technology is able to do. Be the leaders who can bring your team along and change the organizations towards the future AI driven hybrid organizations.