Better Together: Mattias Ulbrich on Combining Coffee, Business, and Technology at Porsche
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Today, we're airing an episode produced by our friends at the Modern CTO Podcast, who were kind enough to have me on recently as a guest. We talked about the rise of generative AI, what it means to be successful with technology, and some considerations for leaders to think about as they shepherd technology implementation efforts. Find the Modern CTO Podcast on Apple Podcast, Spotify, or wherever you get your podcast. What does coffee have to do with artificial intelligence?

In this episode, Matthias Ulbricht will talk to us about how Portia is driving a culture of innovation and digital transformation with AI across all functions in the company. Welcome to Me, Myself and AI, a podcast on artificial intelligence and business. Each week we introduce you to someone innovating with AI.

I'm Sam Ransbotham, professor of information systems at Boston College, and I'm also the guest editor for the AI and Business Strategy Big Idea program at MIT Sloan Management Review.

And I'm Shervin Kodabande, senior partner with BCG, and I co-lead BCG's AI practice in North America. And together, BCG and MIT SMR have been researching AI for four years, interviewing hundreds of practitioners and surveying thousands of companies on what it takes to build and deploy and scale AI capabilities and really transform the way organizations operate.

Hi, Matthias. Welcome to the podcast. We're really excited that you could join us today. How are you? It's a pleasure for me to be with you. Thank you for your time. Can you tell us a little bit about yourself and your role at Porsche? My name is Matthias, and I'm the CIO of Porsche, and at the same time, the CEO of Porsche Digital, a subsidiary of Porsche, where we really focus on the new stuff for

for example, for AI, for cloud technology, for other like blockchain and where we are, let's say, more international. And that means we are in the United States like Atlanta and Silicon Valley, but we are as well in China, for example, we are in Tel Aviv and of course in Germany. So this is a company where we really look for digital projects that we can really support within a Porsche organization

But at the same time, we are looking at new ideas in the market and looking for new business ideas and business models within this organization. You know that I'm actually from Atlanta? Oh, I didn't know that. No. Yes. But you know that the Porsche headquarters is there, right? That's the reason why we're there, because we have a very close collaboration with the headquarters in the United States, in Atlanta, where we're really looking to find the best solution for the U.S. market.

I like the phrase new stuff. Tell us a little bit about how you yourself got interested in new stuff. You mentioned a fair number of new technologies as new stuff. Yeah, I'm personally very interested in new technology. Well, I started electronics when I started my career. I worked with Hewlett Packard.

That was a very innovative, at that time, it was a very innovative organization. So I really like to understand what are the advantages of new technology and what can it bring to the business to bring really technology and business together. This is what drives me and where I'm interested in finding the best solutions.

So tell us how that background started, like how you got from Hewlett Packard or from electronics to Porsche. I started my career at Hewlett Packard a long time ago in the 19s. Then I had the opportunity to join Audi at the time in Neckarsulm. This is a plant where the A8, for example, is built.

And there was a lot of new stuff between the car, the IT and the production side. So it was very interesting to see all the electronics and the software in the car and how you can handle that in the production process. And so I learned a lot about car business, IT business and production at the time.

And after that, I had the opportunity to move to SEAT, that is as well part of the Volkswagen Group as Audi is. And I had a great time in Barcelona, where I was the CIO of SEAT at that time. After that, I had six years in Wolfsburg, the headquarter of the Volkswagen Group. I was responsible for the IT services worldwide. And after that, I became the CIO of Audi. I took this position for six years. And then I decided to...

to get, let's say, a wrap up of the new technology. So I moved to MIT and St. Gallen here in Switzerland to learn more about the term of, let's say, transformation, digital transformation about new technology. And after that, I came to my role here at Porsche to drive the transformation of Porsche and as well getting all this stuff as well from this Porsche digital organization into the Porsche organization.

You mentioned your interest in AI. You mentioned your interest in technology and innovation. Why cars? Yeah, that's a good question, because I thought when I started with Hewlett Packard, it was really interesting. And I saw a lot of different branches and companies starting from trucks and going to ships, for example, as well for other things like chemical stuff.

And then I had those projects with Audi. And it was so interesting to see what technology really did to the car. So it was a time at the end of the 19th where there were so many different electronic devices in the car. And it was a huge challenge to manage that because in the beginning they didn't communicate well with each other. And so there was a huge technology challenge there.

And this was really interesting for me to understanding this challenge and bringing together production knowledge, IT knowledge and the car technology together. And so that was the moment when I changed to the automotive company.

What kinds of new stuff are you interested in right now, particularly Porsche? Yeah, the main focus is really AI, to be honest. Of course, we are looking how we can organize as well with, let's say, agile working. What can we do as well in our development centers for the car business? And of course, software and the car is a very important thing as well, because this is changing the world of driving.

But what we are focusing on as well is to look how we can use AI, for example, to improve our internal processes. How can we use AI to get a better contact and a better understanding of our customers? That is very important for us as well. And of course, yeah, to look what can we do in our product and really increase as well our product portfolio to have digital products available.

that we can deliver for B2C markets. Like we started, for example, with some ideas in the direction of

supporting sustainability as well, like Porsche Impact, where we developed a solution and how a customer can compensate, for example, his CO2 footprint that he drives with the car and how we can really increase our product portfolio for our customers and make driving more attractive.

So is there some particular example of how AI has made a big difference in a way that other technologies would not have that you're particularly fired up about?

Yeah, what we really found out, for example, in production, that we can really use AI to predict, of course, a lot of things. For example, in the order management systems, how we can predict for order to deliver markets to have the right cars in the dealerships. That is not easy, for example, in China. So sometimes it's really...

a challenge to understand what kind of cars they would buy in three months. So it's very important to get feedback from the market and understand what is the most important driver for that, but as well to understand what can we do in the production process, for example.

These are some very, very great examples of use of AI. You mentioned a whole bunch on the marketing side, a whole bunch on the supply side and supply chain and also production. Are there also some examples where roles or functions that are typically more like

engineer driven like design or some of the trade-offs in terms of performance, et cetera, are aided by use of AI? Because we see that in other industries, which is sort of a new thing because these are typically things that engineers have a strong sort of discipline and playbook for. Is that something you can also comment on?

It's very interesting that you mentioned design, for example. So because I was in the design studio here in Weissach two weeks ago and we had a long discussion on

how they use AI to really support their design ideas. And they have a program that they're using for new cars, for example. They can use different models and really reshape the digital model before they go into the first physical model. And they are using AI to supporting the designer, for example. But as well, we have, of course, in other areas of engineering as well,

support tools that really use AI to improve technical development. When you guys implement these AI tools in these areas where a strong collaboration between man and machine is needed, do you find there is a fair amount of sort of

culture change needed or reskilling or change management needed for the human to become friends with AI? I think the collaboration between the machine, the IT machine or the AI machine and the person is very important. And you need to understand how you can use that. And it's totally different if you go to production, for example, or to engineering, because you

Sometimes it's a supporting tool and it supports the worker, for example, in the production line. In the other area, in engineering, they're like friends, like colleagues that work on the same issue. And it's very important to understand that AI is further developed now.

by the business area. So it's not an IT task anymore. It's really a collaboration between the AI expert, but as well the business expert and the machine. And you have to manage that. So this is a huge difference to normal IT projects. So we have a totally different approach to

to go together on such pilot projects. We have, for example, an acoustic anomaly assistant

that works really with the engineer to understand anomalies that we have, for example, in the door and how he can really understand what is the reason for the noise. And this support, it's only possible if you worked really together for months to understand all the noises and then you can adapt it to a different part of the car. But it takes a while and you learn, you have a learning curve like this

And it's only possible if you have a very good collaboration. When you implemented this system, what were people's reactions? Did they say, oh my gosh, this is taking my job? Did they say, oh my gosh, this is a great way to do this? How do people react the day that you turn the system on?

Yeah, like always, people react totally different. Of course, we have a lot of very technical-oriented guys that see the opportunity and see really how this can help them in doing their task better, in doing their work better. You mentioned a little bit about the fears that some people have about when you say AI in general, and they think a machine will rule versus AI.

machine vision to help understand the right label or the acoustic anomaly system on the doors. Like, how did you come up with these sorts of, like the acoustic anomaly system, for example? I wouldn't have thought of listening to a door. I would have thought of looking at a door. How do you get someone to think about listening to a door? My doors haven't said anything as far as I know, but maybe I'm not listening.

Listening to a door is already a task that has been done in Porsche and at Volkswagen, for example, and the whole industry for years.

But the idea to use AI to really improve that noise that a door makes, that came really from drinking coffee. Now, it was in the lab that we have in Berlin. And a specialist wrote an application that could listen to the coffee machine and know what kind of coffee is done. So he knows this was a cappuccino, this was an espresso, for example.

And then there was the idea, what can we do with that, with this acoustic system? And then we...

had some discussion with our R&D people and they said, well, we are listening to our door all the day, but we can't listen at the night, for example, because we are not there. And sometimes there is a noise and we're coming back in the morning. So together we started this project then. And it was the beginning of a success story because right now we are doing this in several places in R&D and it was a good example how it can work.

Yes, for sure. And the step to really educate, I'm sure it really, really helps too, because as you said, lack of information could create a lot of anxiety. And so how widespread are these programs? Is it tens of people or hundreds of people or thousands of people? Yeah. How many people in the organization need to know about these technologies? Everyone? Yeah.

I think, yeah, I started to train really every IT person in my organization so that we have a broader view on that and a common view on that as well. But of course, the AI program is, let's say, it's 200 persons that really work on that in the Porsche organization and that are connected, of course, to others, but

You need a very small core team that is driving this change and bring the best use cases in place and really tell about that. And so we have a good mixture of business people that drive that. And some people came as well to the IT organization that was new. They moved from engineering to the IT industry.

to drive this as a platform. We have an AI platform and they had really fun to drive this program together with the IT people. And so we have a good mixture of business and IT people that are driving this program. That's great. Thanks for clarifying that. And then another question I had is you mentioned 200 people.

How many of these people are new people or reskilled people? Because, of course, some of this training is to educate, but some of it could also be to really build new skills. Do you find that you have to bring talent that may not exist, a massive amount of that talent from outside? Or do you find that it's more about reskilling and training the existing workforce? It's different in different business areas.

For example, in engineering, you have a lot of good trained people that understand technology and that really understand as well the possibilities of AI. In finance, for example, you have a totally different approach and you have to bring more external people to really understand.

those ideas because there's no technology knowledge on the business side. So if I look at my organization, we have maybe,

40% new people and 60% that were already in the organization. But some are, of course, really focused in the past as well to new technology. So they are very adaptive and they would like to learn. So for us, it's a very good mixture because you need really to understand the business process to find the best solutions. That is very important as well.

It's all about continuous and ongoing learning at all levels, right? For people, for the algorithms, for everybody. Yeah, that's right. And creating a culture that is really open for that. That is very important as well. So what are you excited about? I mean, you've mentioned new stuff, the new stuff from the beginnings of Hewlett Packard days to new stuff now. What's the next new stuff that you're excited about?

Yeah, the most thing I'm excited about is to work together with great people, to be very honest. I like technology, of course, but to work with people, it's the best thing you can do and really to learn together as well. So we are just in the beginning of AI. So there's a long way to go because we have done some really great projects, but we are still having a

a lot of things to do with AI. And I believe really that AI is the biggest challenge that we are facing right now still. And all the other things are not such a game changer like AI is right now in the technology field. And I believe that AI and

as well other technologies, but AI in this very special situation can really drive the change that we have right now in society, all the challenges that we have in society, for example, sustainability. And I believe that digitalization can really help in those very important fields. And if you look, Porsche is doing a lot to getting better cars on the road, like the Taycan, for example, to have better cars.

That really helps as well the environment and doing a lot in terms of sustainability. And I think those things are driving me to really creating a better world and looking what can technology really do for that and improve.

Of course, supporting people to really focus on the most important things in life, but as well helping the world to getting a little bit better. And I think this is a great motivation for me. And this is very helpful for me. Matthias, thank you for joining us today. We appreciate all the time you spent in the interesting conversation. It was great with you. Thank you for your time. Thank you very much. Yes, that was great.

Matthias was really interesting. Matthias hit a lot of very key points.

that we see in our work, we see in the survey this year, we saw it last year. He made the point around culture of innovation and creation of new ideas. He made the point around it's not tech, it's about business and technology coming together. He also, you know, underscored the importance of, I mean, just by being who he is and the role he has, the importance of

This being a senior executive role. And then the other thing I really liked is the point he made about...

different roles of AI. I mean, we say that in our report that there are at least five different modes. And then he talked about it. He talked about vision and automation of that. Then he talked about design where AI gives some ideas to the engineer or to the designer. He talked about AI as generator of insights for supply chain or for the marketer or for the product designer.

I really feel like Porsche is getting it. It's really, really impressive. Yeah, Matthias had a nice combination of excitement about technology, but also a methodological approach towards it, which I thought was a nice combination. He both exuded excitement about technology, but at the same time, a very realistic view about how to implement it. The other thing I was quite impressed is the extent of...

culture change that Porsche is undertaking that he underscored with training, with education, with re-skilling, with getting a base level education for everybody in his organization. And it's hundreds of people, not a handful of people.

Right. And they have to because of the number of applications that they're, I mean, he listed off dozens of places that they're using it and they were just all across the organization. Yeah. When he was talking about introducing it, he said, oh yeah, we don't talk about bringing in AI as a big, scary, general thing that's abstract and who knows what baggage it's bringing with it. Yes. He said, we're bringing in this application. It's very specific and very narrow. And then people can get their mind around what that means versus, you

bringing in a lot of baggage from every sci-fi movie that anyone's ever seen. Yeah. The other thing I really liked is the coffee example. It was a great question you asked, you know, why sound?

And I didn't think he's going to go to coffee. I thought there's a million other places he could go. But that's a great example. And I think we also heard that from some of our other interviewees that a success story or an anecdote or an example somewhere else translates into a completely new idea in a completely different field. Yeah, that's a very human role of still that creativity of thinking

recognizing that this situation isn't exactly where we saw that technology before, but it's a great place we can use the technology now. And that's still a very decidedly human creative part, but it still requires expertise. And he was very clear about that, that you had to have that expertise as a baseline. And it sounds like they're working very hard to make sure that

most people in the organization have some expertise in there. You're going to ask him about new technologies he's excited about. He didn't bite on rattling off the latest, greatest new AI thing. He's all about getting the people excited about it. Yeah. That was not where I thought he would go there. Yes, that's right. We really enjoyed speaking with Matthias today. He really combined an enthusiasm for technology with an enthusiasm for business. And that was a fun combination.

Join us next time when we talk with Arti Zegami, head of AI at H&M. Thanks for listening to Me, Myself, and AI. If you're enjoying the show, take a minute to write us a review. If you send us a screenshot, we'll send you a collection of MIT SMR's best articles on artificial intelligence, free for a limited time. Send your review screenshot to smrfeedback at mit.edu.