What do you regard as the key moments in your career?
Choosing what I would study at university was an important moment for me. I went with mechanical engineering because I had the opportunity to participate in an extracurricular robotics class while I was in secondary school. Later, I got familiar with MAN and the Volkswagen Group while I was at university, and after that, I started as a trainee at Audi. Looking back, I’m really happy with that decision.

What is your typical workday at Audi? What sort of work do you do?
Since I've been at Audi, I’ve increasingly focused on data and production IT. These days, my colleagues and I at the P Data Factory make sure that valuable data is available where it is needed in Audi production. Data needs to be tended to just as much as machines or facilities. Well-kept data are a prerequisite for using artificial intelligence, for instance.

We’re also developing use cases for AI and data analytics, which we use to support inter-departmental teams in Audi production. Everyone is talking about AI language models because of ChatGPT right now, and we want to implement a similar use case in Audi production in the future. That would allow people who work in maintenance to communicate with a maintenance bot. The bot would then be able to offer tips and advice to support the teams while they’re servicing machines and facilities.

What do you regard as the key moments in your career?
After school, I started working as a consultant in the auto industry. During my first job I learned what it was like when you land in cold water and must swim. I had to put an automated small-parts storage system into operation, and everyone else kept telling me: “You can’t do this without experience or prior knowledge.” But I did do it. That was a real turning point for me, because I made a decision that I would always learn to swim. I took that with me into the future: I can do anything, no matter how cold the water is.

What is your typical workday at Audi? What sort of work do you do?
These days I work in Data Driven Production in the Data Analytics department. Our vision is to establish AI as a game changer for the future of production so that we can use data products to design Audi plants and processes more efficiently. My colleagues and I actively implement analytics and AI use cases. Predictive maintenance is one example of that. We continuously monitor the condition of our machines and facilities to avoid unplanned downtime and predict ideal times to do maintenance.

I’m convinced that data analytics and AI are crucial for Audi’s transformation and the path to data driven production. To some extent, we can even use it to revolutionize production. But that requires a strategic plan, which our AI program manager and I are working on in the form of the AI program for P. We’re planning strategic analytics and AI activity areas and drafting corresponding road maps for using AI in Audi Production efficiently and on a long-term basis.

What do you regard as the key moments in your career?
Deciding to go into IT was a really important step in my career. I was originally an industrial engineer with a focus on mechanical engineering. After a year as a trainee at Audi, I switched to become an IT newcomer. I found a great team that supported me in that transition. A year and a half ago, I made the decision to specialize further and deepen my IT expertise. That’s why I switched departments again, this time within IT, to Data Analytics.

What is your typical workday at Audi? What sort of work do you do?
I’m the Data Development Lead, which means that I’m responsible for a data analysis development team as well as for various IT products, including dashboards, reports, and analyses for various Audi departments. That makes the job very multifaceted. We see to it that products work properly and assess how we can improve them or create new products.

One demonstrative example of that is an analysis of battery data in electric cars during and after the production process. The information from the production process is linked to and augments data and information from the battery itself in the field. We can analyze those linked data with our software. Quality Assurance is working with Technical Development to use what we’ve learned from that to make further improvements to the next generation of batteries.

What do you regard as the key moments in your career?
I've always been fascinated by cars, particularly in motorsport. When I was a kid, my father used to take me to a lot of DTM races at the Hockenheimring and he explained the technology to me. That’s where my enthusiasm for motorsport started. I wanted to develop racing cars myself, so I eventually opted to study mechanical engineering. I was on the Formula Student team when I was in college. That’s where I learned to take responsibility and developed much faster than I would have in normal everyday college life. Another key moment for me was when I wrote my dissertation on sustainability in motorsport.

What is your typical workday at Audi? What sort of work do you do?
My team is made up of 16 people at various locations. As the manager, I set the parameters so that my team can function at its best. We work on functional safety and define the way that customer functions operate while driving as well as energy for upcoming Audi models. For instance, that means that we deal with questions of when and under what circumstances the automatic start-stop system should turn the engine on or off and what information that function needs to make that decision.

We support and take responsibility for the development process as well as the entire functional chain and ensure that the function ultimately demonstrates exactly the customer behavior we have defined.