The Exchanges

Q I want to talk a little bit about the impact on the business, if you're right as well. Um, I don't actually know how SAP prices broadly today, but the question would be like, how do you price? And if you are, you know, delivering more outcomes for customers or serving them, you know, services, software in a different way, do you think that changes the business model for SAP?

A It does. Absolutely. I mean, there's no, there's no question. And we have prepared for this already. So, For me, it was always very clear. I mean, for the most part, SAP software is seat based, licensed, uh, uh, uh, today with a few exceptions like a conquer or a field glass, for example, or the business network. Um, but you know, Very clearly with AI, it was very clear for us that, you know, step by step, it will go towards this consumptive world, right? First consumptive, and then maybe in the next step, once we have more verifiability in the system, then also towards maybe an outcome-based license model to, for example, what Sierra is doing and so on and so forth. Um, but the reality is also, It is today for us. It's a hybrid model. It's consumptive, but it still has a certain element of seats in there and so on and so forth, because also it's a joint journey with the customer because the customer saying they are not yet ready in many cases, uh, for a purely consumptive model, right? Because they need one predictability, right? And then of course they are not yet fully also everywhere trusting the outcome, right? And well, no, then also of course, is the value already there, but then they are afraid of that the costs may Explode from a consumptive perspective, et cetera, et cetera. So what we, so what at the end of the day, what we have designed as a hybrid that is basically…

AI assessment note: “It does. Absolutely. I mean, there's no, there's no question.”

Q Do you, uh, have a strong point of view today as to whether, uh, agents operating against these business processes, uh, within SAP or otherwise in enterprise software? Do you, do you think it's going to be, um, computer use? Do you think it is all, you know, code and tool use on APIs?

A It's an interesting question. Uh, I have not a, a very, uh, a finite answer yet to this. So I think, um, given of course also how clunky UIs are and so on and so forth, and knowing the challenges also from UI automation from the past, I mean, it's phenomenal what they can do already today, quite frankly. I mean, it's still a little bit slow, right? And, and, and so on and so forth, but I still believe for the most part, uh, it will, The majority will live with tool calling, right? And agents running in the background and so on, right? Because you also don't, you know, maybe want to have the browser open all the time. Okay, we can do this with headless browsers and so on. But I mean, if you can do this right with a more structured approach from an integration point of view, I think that will be the preferred method. But then, of course, there will be always kind of things where an API is maybe not available or you have a legacy This, uh, system for a time being and so on. And then of course these computer use approaches and so on will nicely tie in, so to speak, um, as, as well.

AI assessment note: “I still believe for the most part, uh, it will, The majority will live with tool calling”

Q Yes. Innovation race versus outcome race. Um, uh, it's a, it's a good framing, like. The change is happening very quickly. That's hard for companies to absorb. Where, where do you see, um, challenges for the enterprise in adoption today, and where are customers making the most progress with, with you, or where are they most excited?

A Yeah, that's a good, good question, right? I mean, usually I say, The primary problem, as I said, is the problem of A data, right? Because most of the time, the data is, of course, very disaggregated in a company, right? I mean, for a variety of reasons, right? Either because you made certain decisions, how you purchased solutions in the past, or you did an M&A, right? So you acquired a company naturally, of course, they bring a very different IT system landscape as well. And so on and so forth, right? So you have to segregate information. And the problem is, of course, that limits the potential of what you can actually do with AI, right? And then the question next is, how do you integrate this safely? And what I see is clearly customers who did that kind of homework, right? Now, of course, it's not a new topic. We're discussing this for 1015, maybe more years, right? The ones that did their homework, they, of course, have a much easier life. Right. To then also reap the benefits, for example, of AI. Right. The second one, as I mentioned, is already is the problem of scale. Right. The bigger, the more complex the landscape and so on. Right. Then, of course, also then bringing this together in a unified experience is a challenge. And then finally, of course, everything around then security and so on and so forth. Right. Because then there's always then this gap between, oh, ther…

AI assessment note: “The primary problem, as I said, is the problem of A data”

Q Um, you, uh, now as CTO of SAP have like a, Very broad purview. It also includes the AI strategy piece of it, um, internal and for your customers. Like, what do you think of as your, your own top priorities for the organization, and where is SAP on this, um, reengineering or reimagination journey?

A No, look, I mean, we, we are, we are in the meantime, all in on AI, right? Uh, so, I mean, everybody in the company is using agentic coding, right? Like, because that's of course an amazing, uh, um, uh, productivity boost, right? That our developers have no matter in which programming language they are building, uh, the, the software for the customers. But of course it's also really, um, again, focusing on customer outcomes. Right. And we've seen this, for example, early in the early days now with consulting, for example, right. We built this thing called Joule for Consulting, which is phenomenal because it's one of our fastest growing AI products, because what this actually helps is to build the, um, to, to help the consultants, right, in the, in an SAP project or in a complex landscape, if they are, I mean, again, right, we are serving some of the largest customers. They have a lot of heritage. They have a lot of complex landscape to help them actually To move into the cloud, to adopt the latest AI capabilities, and so on. And with Jufor Consultant, they can reduce, like, 30% of their efforts, right, to get to the outcome faster, which, of course, then directly reduces the cost, not just the time, but also the costs that are necessary in order to get to, to, to get to the, to the latest software. And we've seen this, of course, with Conqueror, for example, right, where now ou…

AI assessment note: “we are in the meantime, all in on AI, right? Uh, so, I mean”

Q way, the way they have in, uh, generic code generation. Do you think it's possible in terms of verifiability or the ability to, um, go understand and evaluate against that intent? Because it is much, um, I don't know if I would say it's more diverse than code, but it is, uh, uh, it's not It's not obviously verifiable, as you pointed out. Like, do you think it can be?

A That's exactly the point. That is where the starting condition is great, right? I think in terms of, like, two lanes. The first lane is, of course, you have the system of record today, right? You know exactly in the system, hey, given this or that instruction, right, what is the outcome, right? Because you can see it in the database, right? And then you can construct, hey, if the order to cache process runs like this, then you need to expect, right, that the, The cash, like the accounts receivable needs to come in this way, right? With the following taxes and so on and so forth. So that gives you verifiability. Now the challenge, of course, is rather this is never enough, right? Because, uh, if you just look into the system of record today, that data is insufficient for this grand vision that everybody has, that it becomes this autonomous enterprise or like the agency of these agents is increasing right over time. So At the beginning, the agents, of course, are coming back to you. Some people call this human in the loop or whatever, right? So they need to come back to you, like also still with cloud code or codex, and still ask you some clarifying questions. Hey, I have no, I could now go this way. I could do that way. And with that, what you want to design for is that you start to capture more of that context, right? I always call this the tribal knowledge, the stuff that is n…

AI assessment note: “So that gives you verifiability. Now the challenge, of course, is rather this is never enough”

Q opportunity for new players. Um, what, what do you, like, uh, SAP, you know, even today is the, um, I believe the largest, like, market cap enterprise software vendor versus Sort of the, the last generation of the new guard, like the sales forces of the world. Um, how has that happened? Like, how did you, how did you do it? And what does make, what makes it so durable?

A Well, what makes it so durable, right, at the end of the day, I mean, if you think about this, and it's happening a little bit the same way also when we talk about the SARS-Estat narrative or the SARS-pocalypse, I mean, anyway, I have the feeling like in this market last year, AI was in a big bubble and everybody was kind of saying, no, it's not, and now this year, SARS-Estat and so on and so forth. Look, the reality is now, of course, with the, the, the costs of Building being so low, right? With specifically agent decoding and all these latest powerful models. I mean, something has always prevailed over the years because even when SAP was founded, right? In 1972, right? A long time ago. Um, I mean, why was it started? Because actually in the seventies, when the founders of SAP worked still at IBM, what did they do? They went to each customer, right? And they implemented the finance system again and again and again and again. And then he said like, hey, this makes no sense, right? Because the economics, it doesn't scale, right? Because of course you can do this, right? But you can only add so much value, right? In any given time. And by the way, we are basically programming the system very similar. Of course, there's always a little bit that is specific then to the customer. And this was the idea where standard, the notion of the standard software was born essentially, right? …

AI assessment note: “this was the idea where standard, the notion of the standard software was born”