Speaker 1: Bloomberg Audio Studios, podcasts, radio news.
Speaker 2: AI is moving beyond chatbots and onto the factory floor,
Speaker 2: helping manufacturers boost productivity, with industrial AI becoming a bigger
Speaker 2: part of the conversation. Joining us now is Semens CEO
Speaker 2: Roland Bush, who recently met with European Commission President Ursula
Speaker 2: Vonderleon and other tech leaders to discuss AI's role in
Speaker 2: Europe's industrial future. But I would note as well, Roland,
Speaker 2: you were the first conversation I had this year. We
Speaker 2: started twenty twenty six with Jensen Wang talking about the
Speaker 2: transition into the physical world. Just very simply to start.
Speaker 2: Why Semens is bedding so much on industrial AI.
Speaker 1: Actually, big ass Siemens is really geared for this moment
Speaker 1: to bring AI into the real world because its industrially.
Speaker 1: I why you need a couple of things. Number one
Speaker 1: is you need a technology stack, and the stack includes
Speaker 1: hardware and software. Both is super relevant. Number two is
Speaker 1: domain or how we know how to build things we
Speaker 1: are on the shop floor. The next one is data.
Speaker 1: We have a lot of data, our own data, data
Speaker 1: shared with our customers and partners, and we have the
Speaker 1: trust of our customers. Because when the AI hits the
Speaker 1: real world. Pallucination is not an option, so you need
Speaker 1: hardcore results. They should work. So we have all this
Speaker 1: and we can bring it now to the real world
Speaker 1: and husband at least we have great partners like in media,
Speaker 1: like some others who are with us in making this
Speaker 1: transformation for our customers.
Speaker 2: I asked you at CES in January, give me a
Speaker 2: case study, an example. There's some evidence of AI in
Speaker 2: a factory anywhere in the world. Fast forward to June.
Speaker 2: Is it real now? Is there to please? Can point
Speaker 2: to please?
Speaker 1: It's really now, and we can talk about the design face,
Speaker 1: the manufacturing face, and the operation phase when your assets
Speaker 1: are in the field. But you talked about an example
Speaker 1: on the on the shop floor. Actually, we now launched
Speaker 1: our iding engineering agent. What is it. It is an
Speaker 1: agent which programs an industrial PC for you. So if
Speaker 1: you have a cutting chop on the shop floor and
Speaker 1: the cutting is not precise anymore, now an engineer has
Speaker 1: to go there reprogram your PLC and so on. Iing
Speaker 1: engineering agent does it for you. You say, I mean,
Speaker 1: my cutting machine is not person they're not working precisely.
Speaker 1: Iron engineering agent analyzes the problem, breaks the problem down,
Speaker 1: looks for all the data, the machines the job which
Speaker 1: has to be done, analyzes it, develops a code, runs it,
Speaker 1: compiles it. If it doesn't work, it compiles it over again,
Speaker 1: fixes it until you can say now go and you
Speaker 1: push a bottom and then PLC is running with the
Speaker 1: same position as before. So we are brought about fifty
Speaker 1: percent higher productivity while the quality of your programming is
Speaker 1: increasing by eighty percent. So this is real factor. And
Speaker 1: now we're introduced using another function where electrical design comes
Speaker 1: also into this into the place. Well, there's a real
Speaker 1: and this also not available in the market. So far
Speaker 1: we brought it to the market and ready to expand
Speaker 1: to other use cases.
Speaker 2: To either by geography or bi sector. Is there a
Speaker 2: market where there's just more speed here? You know, we
Speaker 2: reflected on your meeting with European Commission. Notoriously red tape
Speaker 2: can get in the way. What are you seeing in
Speaker 2: different markets around the world.
Speaker 1: I mean the hardest market as we can imagine currently
Speaker 1: is AI factories in data centers. And yeah, we are
Speaker 1: really in the design phase together. It's in DDIA. We
Speaker 1: create a blueprint a white paper for how an a
Speaker 1: high factor in the future looks like guess what it's
Speaker 1: based on a digital twin, and this digital twin is
Speaker 1: optimized with AI obviously, But if you talk about other markets,
Speaker 1: for example, the fast growing markets which need really need
Speaker 1: productivity and speed. Semiconductors, a lot of investment going there,
Speaker 1: a lot of VABs bills, pharmaceutical there's a lot of
Speaker 1: investment also going to the United States and aerospace and defense.
Speaker 1: We are ramping up our capabilities to produce stuff. So
Speaker 1: there are a lot of sectors. And then last part
Speaker 1: of lease, I mean the car industry is also under pressure.
Speaker 1: They need to evolve faster, having faster cycles, being more
Speaker 1: flexible in their production. So I can go on and on, and
Speaker 1: the topic is always the same. You will be faster
Speaker 1: in your design process using AI, coming from simulation which
Speaker 1: verifies to simulation which creates new designs, and all the
Speaker 1: way in the factory, way down to the point that
Speaker 1: you were deploying more and more robots, and guess what
Speaker 1: robots are also AI based automation devices.
Speaker 2: Semens has an almost one hundred and eighty year history
Speaker 2: as an industrial company, an engineering company. You know the
Speaker 2: sense I've had from you, Roland in the times we've
Speaker 2: spoken over the last twelve months and more is you
Speaker 2: are positioning the Semens as a technology company. How will
Speaker 2: your investments, your attitude towards M and A reflect that.
Speaker 2: And when you think about the market of today, the
Speaker 2: volatility we see in the technology sector, do you think
Speaker 2: that Semens is being treated and valued as a technology company.
Speaker 1: Well, the short answer to the last point not yet,
Speaker 1: but we're working working on it. But the ons the point.
Speaker 1: Over the last fifteen years or so, we invested thirty
Speaker 1: billion dollars in building up our software suite. It's the
Speaker 1: most comprehensive digital twin can be built with Semen's technology,
Speaker 1: and it's a physics based digital twin with a fully
Speaker 1: realistic representation using a media technology for example, and that's unique.
Speaker 1: All in all, we have nine point four billion in
Speaker 1: twenty twenty five, nine point four billion euros in digital
Speaker 1: revenue including software. We are going to double it until
Speaker 1: twenty thirty so and this is a fast growing, high
Speaker 1: margin business and it's now even super charged with AI.
Speaker 1: We rewrite our software so it can be used by
Speaker 1: engineers and agents. So that means you can see higher
Speaker 1: growth rates because you can democratize it and the accelerating
Speaker 1: simulation and again we are supercharging our operation software on
Speaker 1: the shop floor. We say AI technology, so yes, and
Speaker 1: we have that advantage again to combine the real inted world,
Speaker 1: you need to both. Hardware is more important than ever.
Speaker 1: I think about the data centers built, think about how
Speaker 1: how robotics school there is through the market to the
Speaker 1: shop floor. So therefore this combination is unique and we
Speaker 1: keep on going investing. It's a transformation. You mentioned it
Speaker 1: almost on eady the years then the fastest transformation or history,
Speaker 1: and we are on the right track. But it requires
Speaker 1: again I was super fast adoption, but also for our customers,
Speaker 1: which we are supporting.
Speaker 2: Fresh from one of Europe's biggest keynotes, fresh from meeting
Speaker 2: with Europe's most important leaders, Roland versch seman CEO back
Speaker 2: on Bloomberg Tech, thank you very much. Indeed,