Let's take a seat on the Sofa of Wisdom.
Yes, that's what we call it. Because it is always occupied by smart and clever people who know how to innovate and use the right technology.
Right. Thank you for taking the time to dive a little deeper into our joint activities. Why don't you quickly introduce yourselves, so our audience knows who's who and which fields you work in?
Thanks, Christine. My name is Rob Smith. I'm the CEO of KION, the supply-chain solutions company.
Hello, everyone. My name is Kristina Wagner. I'm CTO—Chief Technology Officer—and Chief Digital Officer at OHB, which is a space company.
And, as you can see on the screen, my name is Peter. I look after technology and strategy at Siemens, among many other things.
Yes. Peter, you brought this group together. At first glance, it is quite an unusual combination of companies. We have Siemens, a leading technology company; KION, a champion in supply chains and logistics; and OHB, a pioneer in space and aerospace technology. What brings you together?
Well, first of all, these are great partners, and we get along very well. Second, it is all about trust. We have known each other for a long time, and together we want to master the major challenges we all face. Whether you are KION, OHB, or Siemens, we all face the same challenges. Geopolitics is obviously a major issue right now. Everyone is dealing with uncertainty in the supply chain; nobody knows what will happen next. Then there is demographic change. We cannot find enough people, and there is a massive shortage of skilled labor. There is also the need to become more resilient and resource-efficient, as well as more sustainable and energy-efficient. We all face the same challenges, and technology is clearly how we must address them. We solve them not by working harder, but by working smarter—by accessing all the available data and knowledge. I think that is what unites us. We want to succeed in our respective industries, and we want to do it more intelligently.
That is a great approach, but it is probably easier said than done. Let's dive deeper into the topic. Kristina, I will focus on you now. Where do you see industrial AI having the greatest impact in industry?
At OHB, industrial AI is a catalyst in two major areas. The first is accelerating the engineering lifecycle; the second is strengthening mission operations. Our satellites, space systems, and especially satellite constellations are becoming increasingly complex. Yet we are expected to deliver and develop them faster than ever. That creates a major challenge. Development that used to take many years is now expected to happen extremely quickly. As Peter mentioned, this is not purely an economic issue; geopolitical interests also have to be addressed. This is where AI comes in. AI helps us condense engineering cycles. Engineering changes that used to take weeks can now sometimes be completed in just hours. At the same time, digitalization improves traceability, reduces the effort required for simulation and testing, and reduces human error. That is critical, because time is not only an economic factor; it is also a matter of technological sovereignty. Once a satellite is deployed into orbit, AI comes in again. It helps us operate mission control autonomously and detect anomalies, which is essential. We clearly see the future of space as AI-driven and software-defined. In short, AI helps us develop faster, operate more securely, and stay ahead of the curve. And because space is an extremely document-heavy industry by nature, let me end on a lighter note. There used to be a joke that if NASA printed all the Apollo documents and stacked them, you could build a staircase to the Moon. I am convinced that was optimistic; today, you would need high-speed escalators. AI helps us move through the sheer complexity and volume quickly enough.
Okay, that is a nice example. I am actually very glad that AI is already heavily involved in sending those satellites into space. But that brings us back to Peter: you need to trust that what you have developed, and how you developed it, is safe and reliable. Rob, let me come to you. There are challenges, but there are also opportunities. Where do you see the greatest challenges and opportunities for industrial AI?
Happy to address that. Thank you, Christine. Let me start by saying how excited I am. We are announcing the strategic partnership between Siemens and KION here. Connecting the real and digital worlds, and bringing them together through physical and digital twins, offers a very exciting solution to significant supply-chain challenges. By design, everything in the supply chain is constantly in motion and constantly changing. Today's supply chains are more complex and vulnerable than ever. To make them future-proof, we need to make them resilient and flexible. That means designing in optionality and agility, and being able to operate and optimize in real time. The answer is a digital twin: bringing the physical twin and the digital twin together. You can design the next supply-chain node in the digital twin, including all the mechatronics and software. You can simulate, emulate, and validate the solution before you build it. The digital twin becomes the blueprint for constructing the physical twin, and then the brain that operates it, thinking faster than real time and instructing all the actors in the supply chain—people, humanoids, robots, and warehouse automation—on the next optimal step. That is what physical AI and industrial AI can do for the supply chain, and it is what we are doing. The real-time result is real impact. We have an autonomous truck operating in a full-scale greenfield facility. It recognizes what is happening, carries out logistics missions, and operates safely among people and other machines. With the solutions we are developing, we will be able to scale this across the supply chain.
