SAP SE 2026 Q3 Earnings Call

Please go ahead. Good evening, everyone, and welcome.

Thank you for joining us. With me today, our CEO, Christian Klein, and our CFO, Dominik Asam. On this call, we will discuss SAP's third quarter 2026 results. You can find the deck supplementing this call, as well as our quarterly statement on our investor relations website. During this call, we will make forward-looking statements which are predictions, projections, or other statements about future events. These statements are based on current expectations and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to differ materially. Additional information regarding these risks and uncertainties may be found in our filings with the SEC, including, but not limited to the risk factor section of our annual report on Form 20-F for 2025.

Unless otherwise stated, all numbers on this call are non-IFRS, and growth rates and percentage point changes are non-IFRS year-on-year at constant currencies. The non-IFRS financial measures we provide should not be considered as a substitute for or superior to the measures of financial performance prepared in accordance with IFRS. With that, over to you, Christian.

Yes. Thank you, Alexandra, and welcome to everyone joining us. Q3 was an outstanding quarter. We brought the autonomous enterprise to life. Customers are now getting their hands on our latest AI capabilities, and the response has been incredible. Our strategy is not just resonating, it is being adopted. Here is what that looks like in the Q3 numbers. The growing cloud backlog reached EUR 24.1 billion, up 26%. Cloud revenue was EUR 6.7 billion, up 25% in constant currencies. The strong growth in cloud revenue was significantly driven by our business AI data and platform business. Continuing the trend from recent quarters, nine out of 10 of our 50 largest deals included AI and Business Data Cloud. Total revenue for the quarter was EUR 10.3 billion, up 12%. This is the first time in SAP's history that quarterly revenue crossed EUR 10 billion. Operating profit grew 18% to more than EUR 3 billion.

We are extending our leading position by winning market share at scale. According to IDC, we are growing about 11 percentage points faster than the market. In Q3, AI was the main driver behind our customers' move to the cloud. There are three key reasons. First, AI accelerates the RISE and GROW cloud migration. Second, AI makes the business case for our suite more attractive. Finally, our customers embrace our business AI platform with RISE and GROW. They know it's essential for building the data and process foundation required for high-quality enterprise-grade AI. RISE and business AI are winning across every sector. We added new customers in financial services with BBVA and FirstBank of Canada. Technology and research with Infineon and Fraunhofer-Gesellschaft. Manufacturing with NTN Corporation, and logistics with Nagiqu and the US Defense Logistics Agency. On the GROW side, AI is also a key differentiator.

For example, Greenbrier Maxion, South America's largest railway manufacturer, plans to use Joule to boost real-time operational visibility. Other GROW wins included Petroplus, A5X, and BLACKROLL. Industry AI is becoming a critical differentiator, especially in large enterprises. We saw wins such as AstraZeneca, where we are actively co-developing AI solutions for the life science industry. Decathlon will be leveraging our AI to build a foundation for a more intelligent, automated, and customer-focused business. Meanwhile, Danish retailer Salling Group uses industry AI to manage suppliers, classify new products, and trigger supply chain actions. Time to shelf improved by up to 66%. Manual category management time was cut by up to 70%. Further AI wins came from MAN Industries Limited, building what they call a once in a generation digital foundation to unify operations. Hengle chose our business AI platform for more efficient finance processes and improved decision-making.

Austrian Post, Commerz Real, and Fraport selected BDC. In solution areas and LOBs, Kao Corporation went with SAP Signavio, NTT DATA with our procurement solutions, and Helvetia Group with SuccessFactors. IDC estimates that SAP is growing more than 1.7x faster than the overall HCM market year-over-year. Many customers went live with RISE in Q3, including Mondelez, Panasonic, Roche, Infosys, and Anna Swiss. We also saw HUGO BOSS with SuccessFactors and WalkMe, Thalia Bücher with SAP Warehouse Solutions, and Bertelsmann with SmartRecruiters. In Q3, we already saw the great impact of the autonomous enterprise strategy on our business and in our numbers. Let's start with what customers see, Joule Work. This is where enterprise AI finally becomes usable. Our 400 million SAP users can now work with SAP in natural language and Joule gets the job done. It is based on three key capabilities.

First, conversations, the way users get work done. Here, users ask questions and delegate tasks in natural language. Joule handles every work directly, but when a task requires more than just a query, the user can use Joule to call a specialized agent. Take a supply chain planner. They can ask Joule to summarize the supplier contract, then delegate the resolution of a supplier shortfall to an agent that identifies an alternative source and triggers the production adjustment directly in SAP. Second, Spaces, the live view across system. Joule Spaces brings data together into a single, always up-to-date view, so users don't have to build PowerPoints and Excel spreadsheets. For our supply chain planner, they have a space combining live IBP and S/4HANA data with a real-time supply chain risk summary. They can see current demand, supply, and the risk all in one place.

Third, Joule Studio, the way to extend our agents or build your own from no-code to pro-code and with seamless integration of end-to-end. With Joule Studio, customers extend SAP's agents or create new ones for their specific needs. Here, the planners team can use the supplier resolution agent and tailor it to their own sourcing rules without starting from scratch. As the example showed, Joule Work serves every business user. It is much more than an AI chatbot. It is the workbench for the autonomous enterprise. This is true for users who need a presentation, a dashboard, an email, or solutions for even the most complex enterprise challenges, thanks to our 40 assistants and 300 agents across the autonomous suite. While I'm pleased with the progress we made, the focus is quality over quantity. One well-designed agent can outperform several fine-grained ones. That is how we build.

With Joule Work Desktop, companies like Reinhausen see the potential to permanently transform how their teams interact with business data. The same shift is happening in finance at Accenture. In their words, their Joule journey is not about deploying another AI tool. It is about working differently. Danfoss shared that the sourcing assistant has significantly improved the efficiency and quality of RFP creation. What makes Joule Work and the autonomous suite different is what lies behind this simple experience, our SAP Business AI Platform, the place to build, contextualize, and govern AI. Let's look at this in more detail, starting with build. Joule Studio gives every developer and domain expert the tools to create, extend, and deploy agents on top of SAP's platform. When building custom solutions, customers can select the best model for each use case.

SAP offers access to more than 70 models, both frontier and open weight. Unlike some of our peers, SAP is not committing to a preferred model. We give our customers choice, and we will always make sure that they have access to the best options available. Moving on to context and reason. Joule draws from the deepest business context in the industry through our knowledge graph, anchored in BDC, mapping more than 7 million fields and half a million tables, along with 400 data products and our full process knowledge. With our acquisitions of Dremio and Reltio, we extend that reach far beyond SAP data and give customers a unified context layer across their entire data landscape. This structured business ontology means Joule can solve even the most complex tasks with high accuracy, faster results, and better pro- Pardon the interruption.