Celonis Celosphere 2025 | Marco Görgmaier, BMW Group

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Marco Görgmaier

Senior Vice President, Enterprise Platforms and Services, Data, Artificial Intelligence

BMW Group

play_circle_outline Exploring Automotive Process Intelligence: Marco's Role in BMW's Enterprise Platforms, Data, and AI Innovations

play_circle_outline Prioritization of new projects based on ROI and feasibility from technical and organizational perspectives.

play_circle_outline Transforming Process Intelligence: BMW Leverages 500+ Data Sources with Celonis for Global Optimization Beyond Siloed Approaches

play_circle_outline Creating a Thriving Company Culture: Balancing Automation and Human Innovation for Exceptional Customer Experience and Efficient Manufacturing

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Marco Görgmaier, BMW Group

Marco Görgmaier

Senior Vice President, Enterprise Platforms and Services, Data, Artificial Intelligence BMW Group

At Celosphere 2025, Marco Görgmaier, who leads enterprise platforms (including data and AI) at BMW Group, joins theCUBE’s Rob Strechay and Savannah Peterson to unpack how “no AI without PI” plays out at global scale. Görgmaier explains BMW’s ROI-first framework for mission-critical processes – asking whether a solution creates business value, is technically and organizationally feasible, and will scale – plus a 50/50 match-funding model with the CFO to accelerate adoption. He details how process intelligence underpins AI outcomes across production, logistics ... Read more

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Savannah Peterson

>> Good morning, Celonis fans, and welcome back to beautiful Bavaria. We're here in Munich, Germany, steaming through day two of our two days of live coverage at Celosphere. My name's Savannah Peterson. I'm bringing you all the brightest guests here with Rob Strechay. Rob, we get to talk about cars in this next segment and I'm really excited.

Rob Strechay

>> I'm really excited because the technology and the heart of process coming together, automotive is really one of the places that it has flourished from the beginning.

Savannah Peterson

>> Yeah, and it really brings together everything that we've been talking about the whole show. Without further ado, please welcome Marco from BMW.

Marco Görgmaier

>> Hello.

Rob Strechay

>> Welcome onboard.

Savannah Peterson

>> Thank you so much for being here. You work for one of the most recognizable brands on the planet, so I would be verklempt to not ask you just out of audience curiosity, tell us a little bit about what your day is like at BMW HQ?

Marco Görgmaier

>> Yeah, so I'm responsible for all our enterprise platforms, including our data and AI platforms and services. And of course, BMW is very much recognized for the cars. And we just launched the new iX3 here in Munich a few weeks back, we're really proud of. But my day is more behind the car, the digital company behind these cars. And we're really powering all our enterprise processes from production logistics to customer sales with our platforms and services.

Savannah Peterson

>> And when we think about process intelligence, and the thing that I like about a car is whether that's even the digital layer behind it or the physical manifestation of the hardware itself on the road, there are so many steps to making sure that that is not only manufactured, delivered and operates well, but that the customer experience on the other side is amazing. You're probably balancing a lot of decisions. How do you prioritize what to build next and identify the partners to do that with?

Marco Görgmaier

>> Yeah, absolutely. And when looking at the processes, I think the most important ones, of course, for us, and we see the biggest value are the mission-critical processes. And the way we approach building new solutions is very much looking at the ROI. So, what is the return on investment we're doing. Obviously, and specifically talking about AI, that's very important. And we actually always ask ourselves three questions. First is, will it return business value? Yeah, in regards to efficiencies we can leverage, in regards to better quality or better customer experience. The other part is it feasible from a technical and also organizational perspective? So, are we able to implement that soon? And then, the third part, of course, is will it scale? Will we be able to really scale it in the enterprise? And then, we have a funding mechanism. With our CFO where we say, "If you have a great use case, you have a great return on investment, you can apply. So, you get 50% of the funding directly out of our match fund bucket and the other 50% comes out of the business unit." And that is really a booster for adoption.

Savannah Peterson

>> Interesting. That's cool. I didn't know that.

Rob Strechay

>> Yeah, I was going to say that was a great way to think about the funding model. We also had Patrick from your team on last year, and we were talking about getting to an end-to-end digital twin. Can you update us with how things are going in respect to that and how things are going with process intelligence, reshaping things across the BMW Group?

Marco Görgmaier

>> So, I think when Patrick was here last year, we had around about 250 data sources connected to Celonis for process intelligence and I think we've doubled that number.

Savannah Peterson

>> Wow.

Marco Görgmaier

>> So, more than 500 data sources connected. We have more than 120 use cases live today.

Rob Strechay

>> Wow.

Marco Görgmaier

>> And I think the biggest change here was that we very much shifted from just process intelligence to really object-centric process intelligence. And that's really a mind shift there with the teams, how they not just go from use case to use case and more of, let's say a siloed approach, but really more go into a global optima in the company. So, having more of this overarching enterprise picture.

Savannah Peterson

>> So, you talked both about process there and about humans and about the team.

Marco Görgmaier

>> Yes.

Savannah Peterson

>> How do you balance automation and human innovation, and also still foster a strong culture around that?

Marco Görgmaier

>> Yeah. So, I mean, BMW, we love automation and I think that's really rooted in our DNA. When you look at our production, logistics processes, we've automated with every technology leap we've seen, and it's the same with AI now. Of course, everyone is eager to bring that into our processes. Nevertheless, we have great experts and we really rely on this business and process critical knowledge. So, of course we really try not just to bring the technology in, but really create teams between our technical teams, platform teams, the IT teams who build the business specific applications and of course our business teams themselves. And we started with more like a nucleus, where we sat with central teams, center of excellence, and now we're more moving to a hub-and-spoke approach. So, the teams are scaling out more and more into the business units. There's more and more knowledge how to implement process intelligence. So, yeah, it's really growing. And that's, I think, the moment also when you scale across the enterprise.

Rob Strechay

>> Yeah. And I think, again, just tying off on that and what Patrick had talked about and the use of copilots and things of that nature, but how do you see process intelligence being at the center, as you were saying, for AI and your data platform strategy? Because I think you guys are a massive organization around the world, you have data coming in from all kinds of different things, but really you have daily operations that have to be optimized. How is process intelligence really helping between the AI and the data platform strategy?

Marco Görgmaier

>> Yeah, I think it's really the powerful combination of having the process knowledge and then leveraging the power of AI on top of it. That's really the combination we try to bring to life in the company. And I think looking at all the hype around agentic AI. Everyone said 2025 is the year of agentic AI and I believe very much so in the consumer space. Yeah, that's already reality. I think in the enterprise space, you have all those extremely-complex processes that you also need to monitor, you need to safeguard them, you need to prove for some authorities that your process is actually working. This is adding a lot of complexity. And I think that's where process intelligence is so helpful because you really create this digital twin of your processes that you need to then leverage the power of AI to simulate, to predict. And now, with agents, even to execute on top of that.

Savannah Peterson

>> Which is really exciting and there's so many different layers to that. I'm curious as you've gone through this process working with Celonis, and I realize there's a bit of privacy and confidentiality related to the question I'm about to ask, but have you made any unique discoveries or were there some opportunities where you were able to achieve success quite quickly or really feel like you increased your efficiency?

Marco Görgmaier

>> Yeah, a lot actually. As I described earlier with this use case-driven approach or ROI-driven approach, of course, once we start a use case and implement it, we also look into, does it actually pay off? And we have some really interesting use cases. For example, churn management with customers. So, can we see that probably a order might get dropped from a customer for some reason in the process? And then can we already, when we detect that work against us? Reach out to the customer earlier. So, that's one example where we were very successful looking at this combination of process intelligence and AI. Another example is also when we ship our cars, of course there are a lot of free trade agreements and it's very important for us looking at customs, and you really prove how much of your card has been produced locally, and it's extremely complex because you have so many components in the car and that you have to do that for various countries. And that's another example where we could really optimize the process and prove these customer savings.

Rob Strechay

>> Yeah. Hence, Spartansburg, North Carolina, another, big place where a lot of the Xs are made. I know that and a lot of other things in the US. I think that the whole tariff and trade thing is so complicated and I think that you have to have that process. So, you're also going to be on a panel later today. Why don't you give us a preview of that panel and why you agreed to do it and what you're talking about there?

Marco Görgmaier

>> Yeah. So, really looking forward to the panel. I'm quite excited. For us, Celonis is really crucial in our platform stack. And so, first of all, I was very happy to participate and we always also really love to work closely together with the Celonis team, also shaping the product roadmaps together. I think that's just what really helps us then to implement it in our day-to-day operations. And in the panel, we will talk, of course, very much about this intersection also of process intelligence and AI. And I really see this as several layers you need. First of all, you need this process layer creating your digital twin. Then, you want to have the intelligence layer on top with AI that you say you can do simulations, predictions, and now with the agents, you actually get the orchestration layer on top to even execute based upon this. Yeah. So, this layered approach is really something which is absolutely top of mind for us and I believe for everyone else. So, I'm really excited about the panel and to dive deeper into this.

Rob Strechay

>> Yeah. I mean, just to follow up on that because I think it's really interesting and tie back to where you said you're at almost over 500 data sources coming in-

Savannah Peterson

>> Which is fun to think about.

Rob Strechay

>> It's incredible. I mean, I know the complications-

Savannah Peterson

>> How about getting everything out of data jail, like we were talking about?

Rob Strechay

>> Out of data jail. Yes.

Savannah Peterson

>> No silos if you've got 500 things pouring into a central plane.

Rob Strechay

>> But when you look at it, because you were talking and Dan will listen to this later on, the CPO for Celonis. And when you look at that, has that been a big push for you because just even those integrations and helping your team simplify those integrations. Has that been a great working relationship with Celonis?

Marco Görgmaier

>> Yeah, absolutely. And I think coming back also to this agentic optimization, which is actually a workflow orchestration very much. It's always a combination of AI and deterministic processes. And when you look into that in a large enterprise, the hardest part is actually to optimize processes across divisions and silos, that's really the game-changer. And that will be the game changer also for AI because you have to think the process is AI first. And that's really something where I believe Celonis is... And I don't only believe it, we could prove it, it really helps us to get this cross-process optimization. Because you have those insights, you see the dependencies and like optic-centric. Not only coming use case from use case, but looking at how do I define the different objects, a vehicle, certain parts,. An invoice? Yeah, these are all the objects we have and how's the dependency between those objects and how is it then, again, reflected in your processes? And I think this object-centric approach is much more difficult than going use case by use case. You need more governance, you need more ownership talking about this different data sources, but it also creates a better optimum from an enterprise level.

Rob Strechay

>> But it also helps you get your semantics-

Marco Görgmaier

>> Absolutely....

Rob Strechay

>> your business semantics tied to your data semantics in a better way. I think that's spectacular.

Savannah Peterson

>> Yeah. And I feel like one of the healthy tensions that exist in almost every corporation is people wonder why we're investing time or effort or energy into the activities that a business is choosing to do. It must be nice having Celonis to have that visibility and say, "Hey, we're actually optimizing these processes. These are the levers and here's the tangible result and value driven from that." It's got to make the culture feel more confident moving faster as well, yeah?

Marco Görgmaier

>> Yes, absolutely. And I think a benefit here also is, in a large enterprise, you have complex tech stacks. You have a lot of technologies in your enterprise historically grown. And with the Celonis offering, you have a very open integration and a lot of integration patterns at hand and that makes it easy to connect data sources, connect existing applications. And specifically looking at agents and the protocols you need to really move forward across these different technology stacks, I think that alone is really helping. And really also for our teams, if it's already a big hurdle to get the data in, if it's slow, then making progress fast. And I think specifically in this fast-moving times, that's crucial.

Savannah Peterson

>> Oh, 100%. And it helps keep everybody on the same page and understand why they're on that same page. All right. I've got one final very important question for you because you've been lovely. When you are on the show with us next year at Celosphere 2026, what do you hope to be able to say then that you can't yet say today?

Marco Görgmaier

>> So, I would be really proud if we can show that we were not only able to have this process twin, have the prediction simulations, but really, act upon these processes automatically with agents and then of course have an automatic process improvement also. I think that's really the ultimate goal to say, "Can I adopt processes on the fly if I see there's opportunities with AI?" And that's, of course, the big vision, very complicated one. Sounds easy in theory, very difficult to in real life.

Rob Strechay

>> I was going to say, you just made it sound easy. I don't think it is easy, but I would love to see that, that's for sure. That's great.

Savannah Peterson

>> Yeah, absolutely. All right. I got one bonus question for you. What do you hope that this whole technological revolution does? What do you hope that AI does for your friends and your family and your loved ones?

Marco Görgmaier

>> So, I'm always very optimistic when it comes to new technologies. I always see the chances, the opportunities in that. And I have two kids, so I just see that they grow up naturally using AI, that's probably then the real AI natives. And yeah, of course, I hope that we, as with other technologies, I mentioned that earlier, that we really use the potential for the good, of course, gain additional efficiencies, gain additional revenues out of that to make everyone safe and healthy.

Savannah Peterson

>> Yeah, absolutely. How old are your kids?

Marco Görgmaier

>> Five and nine years.

Savannah Peterson

>> Would you like to say hello? You can give a wave to the cameras.

Marco Görgmaier

>> Hi.

Savannah Peterson

>> We love the family moments. None of this matters if we're not making the world better for that generation. Marco, thank you so much. This has been absolutely fantastic.

Marco Görgmaier

>> Thank you very much for having me. It was a pleasure.

Savannah Peterson

>> Yes. And thank you, Rob. Always bringing the insights.

Rob Strechay

>> Always.

Savannah Peterson

>> And thank all of you for tuning in to our thrilling, exciting, even emotional, at times, very exciting coverage here at Celosphere. In Munich, Germany, my name's Savannah Peterson. You're watching theCUBE, the leading source for enterprise tech news.