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Jürgen Hill: You’ve now been group ½¿É«µ¼º½for about four months, and lead an IT team made up of around 11,000 employees. How do you assess the situation so far?

Katrin Lehmann: We’re looking forward to the future. Since we live in a challenging, but exciting time, this applies both to Mercedes-Benz as a whole and to the entire tech industry. All you have to do is look at the speed at which technologies are changing at the moment, and my department is very well positioned for this. I have a great team of very experienced, globally networked employees who are not only high level with their skills, but are incredibly curious. And the topic of innovation has always been a top priority at Mercedes. You can see that in everyone, that the curiosity is there to try out new technologies.

And on the flipside of that, what complications have you had to address?

In every large company that has grown historically, there are topics you may not like to tackle, but it has to be done. In other words, illuminate the dusty corners with a spotlight and sweep them out. So we’ve rolled out this internal initiative within the IT department worldwide and the teams have cleaned up. So I looked at all applications and cataloged them. The aim of the campaign was to consider what we still need, where to invest and transform, what our IT landscape should look like in the future, and paring down programs.

Which topics are particularly exciting for you?

Let me start with the global issues. These are exciting times due to the macroeconomic situation, as well as the state of the markets and resulting implications for the way we set up our IT. It’s a particularly exciting time for Mercedes-Benz because we’re positioning ourselves more broadly in terms of business models. I’m thinking here of the sales of the future, for example. Ordering a Mercedes must be as much fun as driving one. With the further expansion of our online stores, we’re offering customers the opportunity to complete the car purchase and leasing process completely digitally. This has major implications for our IT landscape, both in terms of availability and the integration of various applications. But the way we develop and build automobiles is also changing. Just think of digital twins or AI, for instance. With a sense of proportion, we want to digitize everything that can be digitized. When I started coding 20 years ago, I could only dream of the possibilities that exist today thanks to AI.

What does this mean in practice?

You have to keep in mind how AI is already accelerating development at Mercedes-Benz today, as more than 5,000 software developers use the GitHub Copilot in the group. They confirm a daily saving of at least 30 minutes. In total, this is already a huge number of hours, which makes development much easier. All areas of the company are currently experiencing a rapid rate a transformation. AI will speed up the world just as much as the invention of the automobile. We decided to be in the driver’s seat.

Are there areas within your IT team where you see room for improvement?

An inherently curious IT organization that’s been around for a long time needs opportunities to learn and to develop further. We’re well on our way, but we can’t let up. We can only build the most desirable cars in the world if we have the best processes in IT. In the same way, we can only be successful if we continuously learn. I’m a big fan of taking time to study on a regular basis so I use the Mercedes-Benz Direct Chat, our internal generative AI solution. My colleagues and I often share the great things we find.

Everyone should express this curiosity, or if something didn’t work so well. There are still colleagues who find it difficult to talk openly about mistakes. The failure culture must be further promoted because you learn more from mistakes than from successes.

For me, this is also part of a learning organization. Because none of us knows the issues that are still to come, and none of us has already done the job as it’s coming to us now. That means we all have to learn and we all have to be able to talk openly about it when something goes wrong, even if most of it goes well for us.

With huge investments committed to increase IT productivity, how do you intend to achieve this considering legacy systems and running costs?

We need to streamline and invest more in standardization. We call the whole thing Radical Standardization, an initiative to take the complexity out of the processes and to go back to standards where it makes sense. If we don’t already have a solution with which we can solve a business issue, we see if there are standard products we can use, or if we can reuse existing components over and over again. In this way, we want to create freedom to invest in new innovations. This is especially true for AI. We also expect this to increase efficiency and enhance the value of our products. You can’t just do the cool stuff. You also have to clean up. You can invest, but you also have to save. Of course, it always has to happen in a good balance. Only then can we be successful.

What is the state of employee acceptance regarding AI in production?

It’s like a Gaussian curve, but people who work at Mercedes-Benz are curious and find innovations exciting and always want to work with the best product. The basic prerequisite for a broad acceptance of AI is trust. That’s why we created our own principles for the responsible use of AI back in 2019. But my perception is it could be even faster for most colleagues. We have a very large funnel of use cases, so we can hardly keep up with implementing these ideas at the moment. So for us, the challenge isn’t to find use cases, but to qualify them and get them on track so they comply with our principles. It’s important we deal responsibly with AI innovations by identifying and minimizing risks.

We only use AI where we see real added value. To this end, we’ve set up a use case database where we collect and evaluate ideas. After the evaluation, we prioritize and start implementing. For this purpose, I have a team of experts at our subsidiary, Mercedes-Benz Tech Innovation, which has set up the so-called GenAI Accelerator.

This has been going on since the middle of last year and now we’re taking it up a notch so we can maximize the benefits of generative AI for Mercedes-Benz and become even faster in implementation.

What kind of use cases are you talking about?

There’s a variety of categories along the entire value chain, and at the moment, all departments have ideas. In sales, for example, we use AI to support our customers in their search for automobiles during the information phase. A virtual assistant supports you with questions about our products and services around the clock. Or in after-sales, in our Customer Assistance Center, we use AI to categorize and prioritize incoming emails, which are forwarded to the respective specialist teams according to content. This allows colleagues to concentrate on the e-mails with a real need for action, and process them carefully and in the interests of the clientele.

But AI is not an end in itself. If a car breaks down, you don’t want to deal with a chatbot. Human contact in this case is irreplaceable. That’s why we use AI in a targeted and conscious way where it brings the greatest benefit, without neglecting the personal touch. There’s a lot of potential in all areas where large amounts of data and documents are available to help employees process faster with AI support.

Another example is internal database queries. With AI, we no longer have to spend a lot of time on getting the relevant data up to date. And our employees get a correct answer to their question almost immediately.

Global IT is also subject to different regional compliance requirements, like the EU AI Act. To what extent does something like this affect your progress?

Our IT department has worked closely with our compliance and legal departments from the very beginning. This is the only way we can identify legal risks at an early stage and systematically address them with foresight, so our IT systems comply with regulatory requirements. With the EU AI Act, I think we’re well positioned because we imposed our rules in 2019, which aren’t so far away from the EU AI Act. For us, it’s a matter that we use AI in accordance with our AI principles globally. Naturally there’ll be gradations, and use case will vary regionally.

Also speaking about progress, specifically representation, there’s still relatively few women leading in tech professions. What do you see as a way forward to address this?

This is a topic close to my heart. First of all, Mercedes-Benz is already very far along in this respect. The fact alone that three out of eight board members are women is something I personally find sensational. Also, the proportion of women in senior management positions is currently around 26% worldwide. This spirit is also noticeable in areas including IT.

In the end, though, when it comes to filling leadership positions, it’s not important to me whether it’s a woman or a man. You have to do a good job. But you have to give women the chance to present themselves. And we do that and see we can promote a lot of great women to important positions. As a result, we’re getting more applications from younger colleagues who are trying to prove themselves.