A Conversation with Roland Busch and Marc Benioff | Dreamforce 2026
Siemens CEO Roland Busch describes transforming the 180-year-old company from autonomous units into a unified tech platform combining physical and digital worlds with AI. Siemens spent $7 billion on internal R&D and $30 billion on software acquisitions like Altair and Dotmatics, while partnering with NVIDIA to build AI-enabled products. The hardest part of the shift, Busch says, is changing people's mindsets through leadership workshops and hiring engineers with domain expertise.
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And now, our CEO and Chair, Mr. Marc Benioff.
All right. All right. Okay. Good afternoon, everybody. How are y'all doing? Good. Are you enjoying Dreamforce? All right. Please welcome Roland Busch, the CEO of Siemens. Hey. Welcome. All right. We're so happy to have Roland here. Roland and I have been friends for years, and we were just talking backstage because, of course, he's been to San Francisco many times. He spends a lot of time in San Francisco. He's even been—
Mainly in your tower.
Been to the tower many times. I was just at his headquarters with him in Munich as well. But he's never been to Dreamforce before. So I'm so excited that you are here. It makes a huge difference to us. We're so grateful to you. Siemens is obviously an extraordinary company, and you are an extraordinary leader. So I'm so happy to have this conversation with you so that people here can start to get to know you. We have so many people here in the audience, and then we have a huge group of people online who are also watching us as well. So Roland, I think we should just take it from the top and just have this kind of conversation. But I think a lot of people, maybe they know Siemens because they went through, they were in a CT scanner and they saw the logo up above, or maybe they saw some industrial equipment, you know, at a power station. But maybe they don't understand all aspects of the company, how big it is, the scale, what you do. the legacy of the company. Do you want to just give us that kind of orientation to Siemens?
Yeah, I do that. I give you a rundown of a— we are heading for 180 years in maybe 2 or 3 minutes. So that's a challenge. So, and the best thing is if I start in sharing with you what we do not do. We don't do mobile phones anymore. We don't do communication network stuff anymore. By the way, We don't do washing machines and stuff like that anymore. No white goods. You will find them with a Siemens brand, but it's not ours, it's Bosch. So, I mean, take that away. So, and why I'm saying that, because this company has one constant over the last 180 years, which is transformation. We really changed our company over and over again. And actually, the biggest change happens in the last couple of years, in the next years to come. Why? Because it's the fastest, by far the fastest change in our history. Think about it. When electricity— this is the time when Siemens was built, when electricity changed the whole world. It took 30 years for electricity to really penetrate society. Now AI takes 7 to 8. So this is the speed with which we are talking about. So what is Siemens about? You will find 3 Siemens companies. All of 3 of them are listed on this German stock market. Let me start with Siemens Energy. This is a company which is doing gas turbines, steam turbines, high-voltage equipment grids. And that's a company which is listed and we just hold 5%. We let finally go. Then you find Siemens Healthineers. They do scanner, MR scanner, CT scanner, blood diagnostics, ultrasound, and the like. Including particle therapy. So it's an acquisition variant, by the way, sitting in the Bay Area. This is a company where we still hold 67%, but we announced that we will spin off or sell off another roughly 30% beginning of next year. It's called Siemens Healthineers. And then you have Siemens. This is, I would say, the real thing, which is the company I'm responsible for. And we actually, we have 3 businesses. One is we call digital industries. We are actually automating each and every manufacturing discrete process hybrids in the world. We are the largest automation company in the world if it comes to that. So the automation business is one. And the other one is our digital software business, which is the the largest industrial software business in the world. If you want, short version is, if you want to build a digital twin of your product, of your manufacturing line, whatever, which behaves like the real thing, come to Siemens. You will get a digital twin which does it. The next business is what's called smart infrastructure, is about buildings. I mean, you would find, actually cannot walk one block in New York without passing by a building which is automated by building automation from Siemens. It's the whole stuff, safety, security, energy efficiency in buildings, building automation. And the other 2 are electrification, medium voltage, low voltage electrification for everything, grids, grid operators, distribution operators, but also data centers. And the last one is Siemens Mobility, which is our train business. We do locomotives, commuters, high-speed trains, as well as signaling systems and the related service. And we have a very strong footprint here. Amtrak is renewing the whole fleet, going electric with Siemens rolling stock. We are the market leader in signaling business. We are innovating. We bring signaling systems to the cloud so you can control a whole signaling system of Germany, for example, out of the cloud. These are the potentials which we have. In numbers, Siemens is an $85 billion company, including Healthineers. We still consolidate. We have 320,000 people worldwide. 85,000 in Germany, 40,000, 45,000 in the United States, 30,000 in China, India, and we are present in more than 100 countries in the world.
So, I mean, it's an inspiring story, and Siemens is amazing, just the continuum of the story and the level of transformations. We've talked about this so many times, but now you've been the leader now of the company for quite some time now, and you took on the incredible lineage after, you know, Joe Kaiser. And so give us a vision of, you know, you see this incredible change happening. You've been living it, you've been driving it in many cases, especially when we get to AI in the enterprise.
Yes.
Well, in our last conversations, when we were in Munich only a few weeks ago, We really were talking about how the deterministic layer and the non-deterministic layer are coming together for the first time. You saw how I brought our conversation right into the keynote as well. Give us your vision of what's happening in the enterprise and what are the changes that we're going to see? Because I think you, maybe more than any other customer, have a truly unique and insightful idea of what is very specifically going to happen.
So my communication team, they really got to my nerves in telling Roland, tell me your strategy. And I said, well, I was telling the strategy and they said, no, no, no, make it in short words, bring it in one sentence. I said, yeah, okay. So here is the try. Siemens is combining the real and the digital world in the age of AI. Sounds simple, but there's a lot of truth in it. Because what we are talking about now is industrial AI. So this is when AI really hits the real world in the way how you design a product, how you manufacture, how you operate your assets. And that sounds simple, but it's super complicated because we are living in a world where failure is not an option. You cannot launch a design of a car or a product manufacture it, send it to the field, and find out it doesn't work. This is not an option. It costs you so much money. So each step from design to production, again, to operation has to be deterministic, has to fulfill safety, security requirements to the highest standard. And think about it. When you ask AI a question today, the same question, you get different answers. So this is not an option. You need a harness. You need to make that work in the real world. And this is, again, it sounds simple, but it's extremely hard to do that. You need domain know-how, you need a lot of data, and you need to have embedded harnesses which make sure that your models don't go off-road. I'll give you one example. When you, for example, people are saying you can now easily upload all your product designs, whatever product you have, and ask AI, give me a new version. You will get one, but eventually it will not work. So what you do need is you need a kind of a system behind, which brings me to one of our products, Teamcenter, which holds all the data. It has a contextualization of the data ontologies, which means which links the components of your product to each other with a certain semantic behind. So it makes sure that it works. And then we have simulation tools, which we obviously, we are accelerating with AI, we're enriching with AI. But at the end of the day, a physics-based simulation gives you always the boundaries. It works in the real world or it doesn't. So we have this loop of the harness, so to speak. So the idea behind it is that we will bring the AI to the real world, and this is where I believe the monetization will take place. You can write a new song with AI, but, and you can monetize so much, but if you really want to get a lot of improvement and return, then you have to go to the real world. To give you an idea, 30% of the global GDP is manufacturing-related. So let's say $100 trillion, 30% of it. If you increase productivity by 10%, 20%, you know what's on stake and how much you can win. And the 10%, 20% is possible if you really go for a real industrial AI world.
You kind of skirted by part of my question, which was a little bit of how things change now that you've— how long have you been the CEO for? It's not 10 years, is it?
I'm in my 6th year.
What's that?
In my 6th year.
6th? How many?
So I'm— so 5 years and I'm in my year number 6 now.
So it's not quite 10 years.
It's not quite 10 years.
So in that period of time, just tell us, how have things changed? I mean, we've gone through COVID, we've went through all these different diseases.
Good point.
And go ahead.
Well, the biggest change happened. My predecessor had a strategy for Siemens was, in a word, it was fleet of ships. So you have business units and segments below. We had 15 business units, another 20 segments. And the idea was let them go as individual companies and run. And you can do that. But I believe the value of Siemens sits in our technology stack, which we scale across as many verticals as you want, which is ultimately what customers expect us to do and what I believe makes us different, because nobody has the competence in automation, electrification, and digitalization like Siemens has got. This is the biggest change, because if you trim an organization for being Yeah. Everything thought, I have my own little ship. I mean, we ended up— I see Scott Gardner, who's running our sales for automation. We ended up in having— I can disclose that here, I guess— 700 job descriptions for our automation salespeople only, because each unit thought about having my own little— this is not going to work. And digitalization, AI is about scale. And you cannot scale if you put it into little boxes. Another aspect was digitalization or AI doesn't respect silos. You won't believe, maybe you do because you have a little bit of insights, how many data silos we have got. So the whole idea to say we go from a fleet of ships to one tech company. One means that we are one company actually, and we have businesses below, but this is, we are serving customers first and foremost. Number 2, a tech company because we are really, and this is Siemens DNA, I mean, we ever have been From the very first start, I mean, it was a tech company with our founder's idea in mind to really create technology which improves the world of people. So, and to bring that out and make people proud for delivering technology, forget your org code. I mean, we are super strong in org codes. When somebody introduces himself or herself, says, I'm Siemens DI SWMF, blah, blah, blah, blah, blah, blah. I said, who cares? Our customers don't care. They expect somebody from Siemens to solve your problems. This is more a cultural change than it is really a content change. So when I started off, this was the first thing, and we changed the culture, the idea of how we run a company. And then the next thing was each of my predecessors started with a reorganization. And I thought I saw it so many times. I'm in the managing board since, I don't know, 12, 13 years, the last 5, 6 years as CEO. I thought, why don't we try to run this company in the same structure with a different mindset and see how fast we can go? And we delivered one record year after the other. But then I found out if you really want to scale, if you want to reach the next level, we have to make some structural changes too. This is where we started off going for this one tech company. We changed our automation business completely. We did run it for business units. Now it's one. It's a CRM layer. You would like that. It's a technology layer, so technology units. And then you have the manufacturing. And manufacturing is also then one manufacturing footprint, so to speak, we optimize. So we changed a lot only where we need it. So in some businesses, we didn't really touch too much. So, and the last point is really getting AI technology all into what we do in the way how we control in our legal processes, but in particular into our products. And this is another big change. One more on products. We also saw that in this time of geopolitics, of export controls, We have to bring out more local-for-local products. So we get a lot of freedom to our China team to say, I mean, develop your local Chinese products and sell them, scale them as fast as possible, as we do for United States. So this is— is it always our wish? Maybe not, because it's great to have global products which you develop once and sell all the way. But we have to do that. And the other one on AI. We started off hiring and building up our AI competence center in the United States, in Seattle. We are ramping up as we speak. These guys are doing an amazing job in really bringing— creating products which are landing so well in the market. We do that with another team, a smaller one in China, with local Chinese models using there. So it's a lot of change. And along that, We spend a lot of money in M&A as well. We acquired for $10 billion Altair, closing our software suite in simulation. We spent $5 billion on Dotmatics. So this is about coming from the design of products to the design of molecules, which is a big thing, life science. So it's a— and it's fun.
When you talk about that cultural change that you've had to go through, because It's a radically different company already in just 6 years, right? It's amazing the shift that you've made. What have been the hardest parts of the cultural change?
I think the hardest part is really the people part. So very often people are saying, when I talk to politicians, they have their hard time too. They say, you have an easy life. You are CEO of the company. You can say that we do this and off you go. Well, not quite. And you know that. At the end of the day, yes, you can, but you have always take your leaders with you. You have to convince and you better also listen to them because there's nobody who says, I know it all. So it starts at the top, building your managing board so they get in sync. We spend a lot of time in workshops, strategy workshops, to read from this, to have the same idea we want to go, have a buy-in. and to be sure that we have the same way of looking at it. Sometimes you have a meeting, 5 people, and they go off and you have 5 different opinions about what you decided. The next piece is addressing not only the top leaders, but my top 50, 60 ones. Still a lot of work. You need a lot of communication, but it's feasible. Then comes the next layer. We are talking about 25,000 managers in the company. This is super hard. I cannot touch them one by one, obviously, and it's really hard to reach them in order to make them follow because they are the transmission from decisions to really executing. This is hard, and also then also communicate to the 320,000 people in the company. So what here comes, communication is super important. Times of transformation to communicate, And to share what we do, why we do it, be open for questions, for feedback, listen to the people, super relevant. So I did quite a bit of— I built up a strong social media team. So we were working very strong on that channel. And that's very important that you really get your people on board. And for them, it's difficult because each of them have to change. They have to develop this what we call growth mindset. You have to unlearn what you learned in the past, and you have to learn new skills. And it's not easy for many people. They hesitate because learning something new means you obviously make failure. And failure very often is not an option. You say, no, no, no, you have a mistake here. No, failure is good. You have to learn, but you have to try it over and over again. This is another cultural element which you have to develop, and you have to take your people along. And so I think this is the biggest challenge. And it's about their own people, but also hiring talent from the outside world. to make them join, not only because of the package, but because they believe they really can contribute to something what Siemens stands for.
Yeah, I think you're making a really solid case that, you know, for an organization like yours, which has always been a leader in engineering for decades, and that everything is changing. And that AI is going to dramatically change how do you think about engineering, how you build products, how you sell products, the kind of people that you have, the culture of the organization. I kind of want to go in 2 different directions, honestly. One is, you know, I can make a big statement like that, but how you're implementing it in Germany or how you're implementing it in the United States and how you're implementing it in China are 3 different operating changes. So even though you want the same thing, you now have to translate it by geography differently. And I think this is very subtle. For those of us in the United States, we don't understand the subtleties of how to work, you know, the worker council in Germany, what that's going to mean for transformation, versus also you made a subtle point that you're in China, you're using a whole different architecture, including different models. That's one whole capability, the geographic distribution, and operating a company the size and scale of Siemens, that is incredibly complex. And then the second piece over here, which is, and yet across all 3 geographies, you have to transform how people are thinking about the problem. You touched on those 2 words that I think a lot of us connect with, growth mindset. How do we cultivate a beginner's mind? That in the beginner's mind, we have every possibility, but in the expert's mind, we have few. And yet we can end up with people in our organizations that kind of have that, you know, expert's mindset and not really aware of the huge transformation that's going on. How do you bring these 2 things together? How do you bring the geographic distribution and the growth mindset together to create that next version of the company?
Yeah, super interesting question. And the answer is multidimensional. One thing is, I mean, bringing people together, exchanging people. I do believe, and we lost it a little bit during Corona. After Corona, I had a hard time to delegate people to China and vice versa. And the basis at the end of the day is if you have mixed teams with different background, this is the best thing what you can get, also in terms of innovation and productivity. But you have to develop that trait again that you really want to exchange people and people feel also comfortable to change. I think that's part of our leadership. The political landscape doesn't really support it in all cases, but we have to do that. It's super important. And by the way, I missed out on India. India is the next place where you will have local for local products. You will see a super strong market evolving. It's another culture. So therefore, this is one element. The other one element is you have to always think about how can you leverage the particular strength you find in the different regions. What I find in China is an extremely fast innovation cycle. I mean, when we gave our China team freedom to develop new products, it took them 9 months to deliver 16 new product lines. Another 9 months, they come up with 26, and in the next 12 months, they come with 35. This is amazing. I mean, unthinkable in Germany to have that speed. So can we learn from that and what can we do and how can we leverage that? Talking about the United States, it's a different approach. I mean, you have number one, it's more the deep tech approach. It's very commercial. I mean, commercial sales in Germany is, I mean, doesn't really compare to what you see in the United States. Super professional. Can we learn from that? And also the deep tech stack, which we see, develop in the United States and in Europe. I mean, take it, you have such a strong domain know-how of how to build things. I mean, think about, I mean, all the machine builders, hidden champions, world-class, they work with Siemens technology. So we have such a strong, deep know-how of how to make stuff. And there are brilliant innovations coming from these guys which you don't find neither in China nor in the United States. So this is the beauty about this company that you have so many different strengths in business-wise, technology-wise, but also regional. And the key to bring that together to one and make it work as one engine to really deliver innovation as fast as possible to our customers. It's a huge opportunity, but it's a challenge and you have to work on it. Every day. It's not done. No, you always have to improve. There's one element, though, since I'm sitting here with you, where I spend a lot of my personal time when people are asking, so how do you spend your time? Yes, I communicate, I talk to people, I engage. There was one element which I really lifted up, which is forging partnerships. I spent time with you and your team because I believe you have a technology we should embrace and integrate as fast as possible because it's a leading technology and it helps us. I started my partnership with NVIDIA. I made it to a time when NVIDIA was, I don't know, $400 billion market cap. And it was very interesting. I had a meeting with Jensen. He was actually— it was even virtual. I was at his place and he was dialing in. It took us 5 minutes to get in sync. And since then, we go there over and over again and start working with each other. There's so many other companies, also smaller companies. I believe it's worthwhile spending my personal time with looking out what kind of technology is out there and can I bring it to our company integrated in our stack faster and deeper than in anybody else stack to make it work. Integrating Teamcenter into Salesforce, I mean, hardcoded, so to speak. It's not putting it on top, it's really integrating it. This is one example. I mean, world-class, number one CRM, number one PLM, make that integrated, it does magic. Thanks for your partnership.
Yeah, I think that that's— I find that too, obviously. I think innovation can come in 2 different ways. You can have organic innovation, obviously Siemens has a huge history of organic innovation across so many industries and geographies, it's endless. But also you can have inorganic innovation where all of a sudden you can find a technology outside the company and by bringing that in, it can also be very transformational as well. And getting both of those things to work is the right balance. Is that a fair way to characterize it?
Absolutely. And we had an intense discussion. So we are spending 8% of our revenue in R&D, which is we're heading for $7 billion, which is a lot, but it's just not enough to go in every corner of the technology stack what we need. So it's always short, which is good. I mean, R&D budget has to be tight. But it's, I mean, the world is much, much bigger. It goes so fast that you really have to see what is out there, what you can integrate. And you have, I mean, so we have basically 3 different ways. You can, number one, develop on your own. You can acquire. And we do a lot of that. I mean, our software business, we spend $30 billion pure M&A money to build that software suite. Or you can partner because you say it's fine to have this access to technology, but it doesn't have necessarily to be part of my own P&L. You have to make choices. And And it's the key question is, and we had an intense discussion on, in really genuine new innovations, I mean, you spend a lot of money and guess what? I mean, maybe 8 out of 10 times, maybe 9 out of 10 times you fail. I mean, it's innovation. If you make it in 9 out of 10 times, you didn't throw your ambition far enough. So therefore, So is that worthwhile spending 9 out of 10 times trying something and spend the money and then one hits? Why don't you just go out there, check for a company, and once their technology hits the market, you buy them? It's faster. It's maybe different money. No, it's not P&L money, it's M&A money. So it's a very interesting discussion. At the end of the answer, we found out is you have to do both. Do it right. Stop innovations once you start it fast enough so that you don't throw money behind any kind of innovation project which never makes it. Be very, very customer-focused. But you have to fire on all 3 cylinders, I guess, in a smart way. And the first one, genuine own innovations, is harder than you can imagine. I'm not talking incremental innovations, new features. That's fine. We get that done. I think you know what I'm talking about.
Well, I think this is where we are right now in the industry. There's so much change and transformation happening that you can't just expect that you're going to be able to do it all. You're going to have to find different ways to bring that in and achieve that balance, but to kind of end up with the right result. Let me ask you, when we're talking about Engineering, you know, obviously is the preeminent engineering organization in the whole world. What is your advice to the next generation of engineers coming in? I mean, you can see how engineering has been completely flipped on its head because of AI, right? So you must be thinking about this. We even saw Jeff Bezos is creating a company just to become— to create a virtual engineer. How do you see that as the future? You must look at that opportunity as well.
Absolutely.
Very aggressively as something that you want to do.
Absolutely. And which goes back to the question very often people ask me, I mean, my child is going to study or I'm going to study, what do you advise me to do? Eventually not software or informatics, maybe data scientists, whatever. So I don't really know. But what I do know is the demand in the future will be will be linked and rooted into creativity, the way how you interact with people. I mean, so the social aspect, it will be linked to actually the physics, the real world. So I very often advise to say, if you go back and study mechanical or electrical engineering, where you really learn what is the physics behind, so the rock-solid mechanical engineering, it gives you a completely different way of using AI tools compared to if you're not, because you can make your personal judgment. I'm a physicist by education, and I'm always saying physicists have a very interesting way of thinking. What we do is in order to bring the world into formulas, We try to simplify the world as much as we can, and then you can put an equation behind. So a pendulum is super hard to calculate what's the frequency. But if it's a thin, weightless line with a point mass, you can calculate it with highest precision, with mathematical precision. So think about it. If you have that— trade, the capabilities to look at a problem and you can make a judgment. Is it really in the boundaries? Is that really working? That it's wrong? This is something what you— I think you need that for a while. Does it survive forever? I don't know, but you need it for a while. And creativity, some people say, I mean, study arts because arts gives you a completely different way of looking at things. That's something if you blend that into hardcore engineering, maybe you come up with new ideas. So, and finally, I mean, the best is if you love what you do, you will be good at it. And then embrace any kind of technology because standing in the door believing that if you don't use AI, it prevents you from losing your job or whatnot, it's not a good idea. So the combination, it's the tool. The genie is out of the bottle. I mean, AI will change the world in the next years. I mean, that's a As sure as we are sitting here. So you better embrace it.
So is this conceptual right now, or do you actually have real examples in Siemens?
Yeah, I mean, we are— we have examples. So we are on the one side, we are educating people in AI technology. So we have, God knows, 100,000 offerings. Even they are too big. So we use AI to make it personal. So personalized training with our AI platform. On the one side, on the other side, if you see our hiring pattern, I recently visited our software guys in Los Angeles, and they said, we are starting hiring mechanical engineers, electrical engineers again, and not people from— this is a hardcore software company. And they say, because this is the capabilities we need, our people need to be more in the specification. So the spec is super important. And then AI can do the trick and develop software, but the specification— that contains domain know-how and the way how the real world works. So yes, we do. And data scientists seem to be also a very hot thing, I guess.
Let's change the channel just for one second because I think that for a lot of us here in San Francisco or even in the United States, we're watching closely what's happening in Germany. It seems like there's a sea change happening, especially politically right now. Driven by many different factors, what's going on with the war, what's going on with energy, what's going on with immigration. You know, it seems that Germany really is in the hub of the wheel of the transformation of Europe. Can you give us some enlightenment on how you see the situation in Germany today?
Yeah.
What is changing and how— what lessons should we be learning here in the United States from that?
So let me start with a— and this is a super interesting question, Wissen. You know that if you look into not only Germany but Europe, there's a shift in the political scene from voters to the right wing or left wing, so away from the middle parties somehow. And it's not only Germany. You see that all over the place. So that means it's not really linked to one individual culture or economy. It's really a pattern. And I was thinking very long and discussing very intensively with political people, with leaders, what is— there must be a commonality. Why does that happen? And I give you my humble interpretation. Maybe there are more other reasons. One is the people have the feeling that they're losing control. So how do I explain? Losing control means if you, for example, if you're a worker, you work hard, and you still cannot feed your family, this is a loss of control. If immigration comes uncontrolled and you have people there, these people are feeling they lose control. So if, for example, if you go to your government and you ask for a new passport or whatever, and you find a completely non-service-oriented, super non-digitalized department tells you, I mean, come back in a week from now and then let's Talk is loss of control. And this is a pattern you see that, and that, to my understanding, is firing to the parties who have simple answers, which do not work, but they tell you, we give the control back. We solve this and we solve that. I don't know how they do it because it's not really a good program. It's just soundbites. So that's a situation you see all over the place. Going back, how did it come so far? It's a blend. It's a blend of, number one, is we are— our political leaders did not really do the hard job and the hard decisions. They just throw money for the people to consume more rather than invest. It's about also we are working not enough. I mean, Germany is sitting, you might know that, but if you look at the working hours per working person, Germany is on place 40 out of 40 OECD countries. Switzerland works 5, the people work 5 weeks more than in Germany. So we have to change that. I mean, The sheer input of working hours is a super relevant part. And so it's a lot of things. Then we are putting regulations over regulations over regulations, and they make us slow and expensive. We are regulating, for example, our social housing with energy efficiency and noise cancellation, whatever you have, to a way that you cannot build cheap anymore for social housing. So it's self-made, and I can go on and on. Our energy system, it's just too expensive because we made a lot of mistakes in changing that. And so it's a blend of maybe not doing the right reforms, don't do it fast and consequent enough. And then the last one is that Germany is on the spot because we are one of the most industrialized countries in the world. 40% of our GDP depends on export. If it comes to head workers, so headcount, every, I think, 25%, 20-25% of the people are working for export in Germany. And China really took up such a fast pace developing good products with super high competitive prices, this goes to the market against, again, what Germany does. So there's a particular situation for Germany as well. Complicated situation, but we need to get our reforms done. It needs to be done consequently. We have to take our people along, also communicate why we do it, because it requires a certain hardship for the people, at least for a while, in order to go and ultimately We have to go back to 1%, better 2% growth of our economy. Growth allows you to control your destiny. If you don't grow, it's a fight for distribution of what's left, and that's not an option.
As we— thank you. As we start to wrap it up, I just want to ask you one last question about You know, thinking about all these incredible young people you're bringing into your company right now and your message for them, you know, looking at the political situation, the technology situation, and the corporate situation, as well as the pan-geographic situation, what is your core message right now for your next generation workforce?
I think the key message is that Yes, we have to recognize that we're in a very difficult situation, but it's in our hands. I believe in the people. I believe the people which are working for Siemens, the people also coming back to Germany, the competence and the quality of the people. And we have to get it done. There is a future for us, but we have to— it's in our hands to make it, and we will make it. So stay optimistic on the one side, recognize that it's not a walk in the park. So rolling up your sleeves and give yourself into it. I think this is super relevant, super relevant. We have to have that fighting spirit, and hard working is not bad. I mean, some people say work makes sick. I don't believe that. I mean, I work very hard and I don't feel sick. So anyhow, so this is a— to paint a positive picture and say, this is where you want to go, and you can contribute. You can make it work for the sake of you, your family, but also for your ancestors.
Roland, we're so grateful for you to come to Dreamforce and to spend the time with us. And thank you for everything that you've been doing for Salesforce as well. I'm so grateful to you personally. Would you please thank Roland Busch?
Thank you. Thanks, Marc.
