About this transcript: This is a full AI-generated transcript of Global Keynote: The Beginning of Better — SAP Sapphire Orlando 2026 from SAP, published June 5, 2026. The transcript contains 11,930 words with timestamps and was generated using Whisper AI.
"Since the dawn of time, history has been defined by a series of world-changing innovations. These groundbreaking moments were not always met with the appropriate levels of enthusiasm. Well, that's the end of the raw food industry. Mm-hmm. It's called a sail. I don't know. We've always been more of..."
[00:00:00] Since the dawn of time,
[00:00:11] history has been defined by a series of world-changing innovations.
[00:00:18] These groundbreaking moments
[00:00:20] were not always met with the appropriate levels of enthusiasm.
[00:00:26] Well, that's the end of the raw food industry.
[00:00:29] Mm-hmm.
[00:00:33] It's called a sail.
[00:00:36] I don't know.
[00:00:37] We've always been more of a rowing-centric organization.
[00:00:44] We have.
[00:00:46] I call it inoculation.
[00:00:49] Clever, but we have a lot invested in leeches right now.
[00:00:53] There you go.
[00:00:57] Leeches?
[00:00:59] Well, that's the end of Shakespeare.
[00:01:11] That's the end of their careers.
[00:01:13] No doubt.
[00:01:14] No more mainframes.
[00:01:17] Well, that's the end of big data.
[00:01:20] What is this called?
[00:01:22] The Internet.
[00:01:23] I do not like it.
[00:01:26] They're calling it software as a service.
[00:01:29] They think people are going to rent software?
[00:01:35] SAP HANA, it's the end of legacy enterprise tech stacks with silo DRP and analytics.
[00:01:40] I don't even want to imagine a world without legacy enterprise tech stacks with silo DRP and analytics.
[00:01:54] So we're an autonomous enterprise now.
[00:01:56] So we're an autonomous enterprise now.
[00:01:57] You know what that means?
[00:01:59] It's the end.
[00:02:01] Yeah.
[00:02:02] The end of busy work, bottlenecks and silos, and the beginning of faster, simpler, better.
[00:02:11] Welcome to the autonomous enterprise.
[00:02:14] It's not the end of anything.
[00:02:17] It's the beginning of better.
[00:02:19] Please welcome to the stage, Christian Klein.
[00:02:22] Wow.
[00:02:35] Hello, everyone.
[00:02:36] Welcome to Sapphire 2026.
[00:02:40] Welcome to all our customers, partners, media, and analysts.
[00:02:45] And, of course, to my best friend, Joel.
[00:02:49] It's great to be back in Orlando.
[00:02:51] Sapphire is such a fantastic opportunity to connect with people from all around the world
[00:02:58] and to feel the energy of the wonderful SAP community.
[00:03:03] Especially in times of incredible change in speed,
[00:03:08] Sapphire is more important than ever.
[00:03:12] Some time ago, when we started to prepare this keynote,
[00:03:17] I asked myself the question,
[00:03:20] will SAP actually be a software company in the future?
[00:03:25] Are you scared by this question?
[00:03:28] I'm not scared.
[00:03:30] For me, the time right now is the beginning of something even better.
[00:03:36] And today, we want to show you why.
[00:03:39] So let's come back to this question at the end of the keynote.
[00:03:42] There is no doubt that AI is changing everyone's life, starting with my own life.
[00:03:50] As a CEO, I use AI for all kinds of tasks.
[00:03:53] I use AI to bounce around ideas for our next strategy refresh,
[00:03:59] or to analyze the market sentiment before earnings,
[00:04:03] and to prepare my customer meetings or this keynote today.
[00:04:08] And as a dad, I use AI to draw pictures with my kids.
[00:04:13] And AI does certainly a much better job than I could ever do.
[00:04:18] But take a closer look at this unicorn.
[00:04:21] The unicorn is not perfect.
[00:04:24] It actually has three ears.
[00:04:28] My daughter told me that at least it doesn't have two horns.
[00:04:32] So for her, an 80% accurate drawing of a unicorn is still good enough to make her happy.
[00:04:40] In business, it's different.
[00:04:45] If AI agents want your payroll, your financial close,
[00:04:50] or do the demand and supply chain planning,
[00:04:52] 80% accuracy is just not good enough.
[00:04:57] When you want the world's most mission-critical businesses,
[00:05:01] your AI agents, they should not guess.
[00:05:05] They should deliver accurate, reliable, and compliant outcomes.
[00:05:10] According to a recent Stanford AI survey,
[00:05:15] almost every company is now using AI.
[00:05:18] But many see only little value.
[00:05:22] Why do we face such huge challenges with AI in business?
[00:05:28] At the top of this iceberg, visible to everyone,
[00:05:33] is that large language models are getting better and better at tasks
[00:05:36] like generating text or images,
[00:05:39] or in specific domains like writing software.
[00:05:44] All of these use cases are related to publicly available content.
[00:05:48] The modules are trained on.
[00:05:51] But if you go below the waterline,
[00:05:53] beyond the level of sales demos,
[00:05:55] and into the real business world,
[00:05:58] you're going to find out that none of these models
[00:06:01] are trained on your business data and processes.
[00:06:05] These AI agents also don't naturally adhere to governance requirements
[00:06:10] like your security compliance framework,
[00:06:12] your data privacy requirements,
[00:06:15] or to your company's identity and authorization rules.
[00:06:20] All AI agents, including Juul, have faced these challenges until now.
[00:06:29] Let us now show you how SAP will solve this challenge.
[00:06:34] The path to the solution starts with the brain of every company.
[00:06:40] Do you know which brain I'm talking about?
[00:06:44] The brain of every company is the ERP.
[00:06:51] For over 15 years,
[00:06:53] we have been developing an ERP
[00:06:55] with incredibly deep process and data domain know-how.
[00:07:00] On top, all your governance requirements
[00:07:04] and customer-specific extensions are stored in the ERP.
[00:07:10] The ERP is the trusted system of execution running your company.
[00:07:17] So, how can we now infuse this deep business domain know-how
[00:07:22] sitting in your ERP into our AI agents?
[00:07:26] Let me illustrate this with the following prompt.
[00:07:31] First, I'm asking Juul to provide me an update
[00:07:34] on my total year financial forecast
[00:07:37] with the latest sales and pipeline data plus supply chain data.
[00:07:41] To understand my question,
[00:07:43] the prompt is processed by a large language model.
[00:07:45] So far, so good.
[00:07:46] But going forward,
[00:07:48] the LLM now has access to the brain of every company, your ERP.
[00:07:55] To first find the right process
[00:07:57] from thousands of business processes in your company.
[00:08:01] Then, with the knowledge graph,
[00:08:02] select exactly the right data from over 7 million data fields
[00:08:07] stored in your ERP landscape.
[00:08:10] And finally, before the outcome is shared,
[00:08:13] we check all your identity and authorization rules
[00:08:16] to ensure the outcome is not only accurate, but also compliant.
[00:08:23] Well, the team delivered.
[00:08:26] Building nothing less than a new SAP.
[00:08:31] We are bringing together LLMs with 50 years of business know-how stored in our ERP
[00:08:39] by merging our AI foundation with our business data cloud and business technology platform.
[00:08:46] And today, I'm super proud to launch our new SAP Business AI platform.
[00:08:55] Which forms the basis for our vision of the future of business.
[00:09:00] The autonomous enterprise.
[00:09:11] Where agents run the business and you can focus on what truly matters.
[00:09:18] Let me start with the foundation.
[00:09:21] The heart of this new platform is the rich context layer.
[00:09:25] Here, we infuse the deep ERP business domain know-how into the AI agents.
[00:09:31] Through our knowledge graphs, our AI agents have now a compass, a map,
[00:09:35] a map, to find the right process and data in your ERP universe.
[00:09:40] And to provide the agents even more context,
[00:09:43] we are also introducing our new SAP domain models.
[00:09:48] They have been trained on SAP's code to even better understand the business logic of your company.
[00:09:56] But we don't stop here.
[00:09:59] Because you run your business not only with SAP solutions.
[00:10:03] Actually, why not?
[00:10:06] Our AI agents have to also understand non-SAP data.
[00:10:10] That's why we included our SAP Business Data Cloud in the context layer.
[00:10:16] To build one semantical data layer across SAP and non-SAP.
[00:10:21] No more silos.
[00:10:23] No spaghetti data sprawl.
[00:10:25] Because no AI agent can compensate for a broken data model.
[00:10:32] Let's move on to the build layer of the new platform.
[00:10:36] Here, we are introducing Joule Studio 2.0.
[00:10:41] Our new build layer is open and agnostic.
[00:10:44] You can bring your own LLM or you use SAP's own models.
[00:10:49] You will be able to develop agents faster than anywhere else.
[00:10:54] Because Joule Studio 2.0 is integrated with the context layer and has direct access to all of your business logic.
[00:11:06] And finally, in the governance layer, we want all SAP AI agents for you.
[00:11:12] So you don't have to deal with the complexity and governance requirements sitting below the waterline of the iceberg.
[00:11:20] Via our AI agent hub in Lean IACs.
[00:11:23] We also invite you to actually maintain and provide together all the agents running in your company.
[00:11:30] And we will govern non-SAP agents for free.
[00:11:35] So, let's take a closer look into our new SAP foundation.
[00:11:39] The SAP Business AI Platform.
[00:11:42] Joule, can you help me introduce the next speaker?
[00:11:46] Of course, Christian.
[00:11:48] Please welcome to the stage, Philip Hertzig.
[00:12:03] Good morning and thanks, Christian.
[00:12:05] We are so excited about Business AI Platform.
[00:12:08] A platform that is designed to close the adoption gap by delivering outcome, speed, enterprise readiness,
[00:12:16] and, of course, all the context you need.
[00:12:19] It's the place where you build, contextualize, reason, and govern AI end-to-end.
[00:12:24] And let's have a deeper look into build.
[00:12:27] In fact, before we actually start building anything, it would be great to know what to build.
[00:12:31] What has the highest impact on the business?
[00:12:34] In the past, you had to do time-consuming research or do this thing we propose called AI discovery workshops.
[00:12:41] Now, it is as simple as typing, show me my top three business challenges.
[00:12:46] Now, in this case, we are a pharma distributor.
[00:12:48] We move a lot of products around and need to align prices between manufacturers, hospitals, and
[00:12:54] purchasing organizations.
[00:12:56] Complex supply chains, razor-thin margins.
[00:12:59] Now, we have this new thing, the process consulting agent from SAP Signavio, that goes deep into the
[00:13:05] actual business processes of that pharma distributor to show us what has the highest impact.
[00:13:10] In this case, we have a huge margin leakage.
[00:13:13] In this case, we have a huge margin leakage.
[00:13:13] This year alone, 24 million at risk.
[00:13:16] A great use case where AI can help.
[00:13:18] And the proposed solution, a sales pricing validation agent that helps to resolve those inaccuracies.
[00:13:25] Now, where do we build this agent?
[00:13:27] Of course, in Joule Studio.
[00:13:29] It's the place where we extend, build, and integrate AI experiences like never before.
[00:13:35] Since its launch, customers and partners have built phenomenal things with Joule Studio already.
[00:13:41] Like ABB, that now handles more than 15,000 RFQs automatically every year, saving them millions.
[00:13:49] These are just a few great outcomes, but we heard your feedback loud and clear.
[00:13:53] You all wanted more.
[00:13:55] And today, we're super excited to introduce Joule Studio 2.0 to build agents for business outcomes.
[00:14:03] Now, what is this new Joule Studio?
[00:14:05] Now, first, it's intent-based, so it really understands your business challenge.
[00:14:10] And it's deeply contextualized in your business data and business process know-how.
[00:14:15] It, of course, comes with out-of-the-box connectivity to all your apps.
[00:14:19] And it guides you through full-fledged product requirements, documents, and technical specification.
[00:14:25] Also, super important, it's eval-based, so you can actually guide in a data-driven way your AI coding
[00:14:31] assistance, and it's SAP-managed and comes with all enterprise qualities baked in.
[00:14:37] In addition, Joule Studio is open by principle.
[00:14:39] You can choose from any third-party AI model.
[00:14:42] We have them all on the platform already.
[00:14:44] Of course, also SAP's own AI models.
[00:14:46] And you can build in the environment of your choice.
[00:14:50] No login.
[00:14:51] And, of course, your style.
[00:14:52] You can develop low-code, pro-code, everything in between.
[00:14:56] Now, let's build something together with one of our amazing partners.
[00:15:00] And for this, I'd like to invite KPMG on stage.
[00:15:03] Rob Fischer from KPMG Global Vice President right here.
[00:15:08] Rob?
[00:15:20] All right.
[00:15:21] Rob, you're a fantastic customer and partner alike.
[00:15:24] Tell us a little bit more where KPMG stands today with respect to AI and, of course, also SAP
[00:15:30] technology products.
[00:15:31] Yeah.
[00:15:31] Well, first, it's great to be here, Philip.
[00:15:33] And that's right.
[00:15:34] We're living AI transformation ourselves and we're learning from it every day.
[00:15:38] We're a grow customer and we know what it takes to modernize core systems on S4 public cloud
[00:15:44] while still keeping the business moving.
[00:15:46] We've got a final rollout with about 270,000 users.
[00:15:51] And we moved early on AI.
[00:15:53] We deployed Juul for consultants across 34 countries, and more than 3,000 of our consultants are using it already.
[00:16:00] And we're co-innovating with you.
[00:16:02] Our teams have built many agentic AI solutions, including 20 agents on the new business AI platform.
[00:16:08] That's right.
[00:16:09] And for one of the clients we're working with, we're targeting $120 million in reduced contract
[00:16:13] leakage.
[00:16:14] That is real, tangible value.
[00:16:16] Absolutely.
[00:16:17] It's amazing value.
[00:16:18] Hey, Rob, KPMG is a global leader in AI as well.
[00:16:21] And also, of course, very well recognized for its high-quality advice.
[00:16:25] What is the number one thing you're seeing here with customers?
[00:16:29] Yeah, I think it's this clear shift, right, from pilots to integrated AI agents.
[00:16:34] You know, customers seeing AI not just as workforce efficiency and cost savings,
[00:16:39] but as core to competitiveness and a driver for unlocking more business value.
[00:16:43] And where we're really seeing the leaders really separate from the pack is in the execution
[00:16:49] and the organizational adaptability.
[00:16:52] You see leaders pairing the AI investment with the workforce transformation
[00:16:56] and then embedding AI where the decisions and the accountability sit.
[00:17:00] And because most enterprises run on multiple platforms,
[00:17:03] that AI has to orchestrate across the ecosystem with trust built in from day one.
[00:17:09] And hey, that's where SAP comes in.
[00:17:12] Rob, thank you so much.
[00:17:13] That was a great setting up the stage.
[00:17:15] And now we actually would like to implement the pharma distribution scenario
[00:17:19] on the margin leakage we just saw.
[00:17:21] And gladly one of your colleagues, Chris, gladly accepted to do the demos.
[00:17:25] And we don't have to do the demo.
[00:17:27] You do the demo for us now.
[00:17:28] So that's amazing.
[00:17:28] Thanks for the partnership.
[00:17:29] And Chris, let's get up right on stage.
[00:17:43] I'm excited to show some magic and really build something powerful for an organization.
[00:17:47] Here we can see Juul Studio, where I can extend, build, and integrate agents.
[00:17:52] And what I really love about it, it's fully integrated with the SAP ecosystem.
[00:17:57] And I can build enterprise-grade agents without writing a single line of code.
[00:18:01] Juul has already taken the findings from the process consultant demo that we showed before.
[00:18:06] And I can use them to build the new pricing validation agent.
[00:18:10] This is where we tell Juul what we need to achieve rather than how we actually do it.
[00:18:15] It's a game changer for how we deliver value for our clients.
[00:18:18] And this is where we start to see Juul acting less like a tool and more like a colleague and coworker,
[00:18:24] where it checks and asks us critical clarifying questions, such as,
[00:18:29] what's the source of our pricing data?
[00:18:31] Or what really drives success in this scenario?
[00:18:37] And as I'm going through these answers, one of the things that I think is extremely powerful is
[00:18:41] it's fully integrated with our agent landscape.
[00:18:45] Where in this case, we can see that it's already identified two existing
[00:18:48] governed agents that we have deployed that are already do part of the job.
[00:18:53] This is automatically included in our solution.
[00:18:56] And from this generated intent, I get transparency into what is the problem statement?
[00:19:01] What is the business context?
[00:19:03] What are the relevant source systems and data domains that are included in this?
[00:19:07] As well as taking a look at is what is the recommended solution for this agent?
[00:19:13] From all of this context, what I'm able to do is automatically generate the product requirements
[00:19:19] document that have historically taken us weeks or days to generate this type of blueprint
[00:19:25] that we now have to click at a button and get in just minutes.
[00:19:30] What we're able to do is within this product requirements document is verify that this is the
[00:19:36] intent, this is what we need to build this agent, as well as if we need to make any adjustments,
[00:19:43] such as adding a margin threshold of 1.5% to make sure it has that baseline.
[00:19:52] Now it's time for Jewel Studio to start doing the building and we can build the solution.
[00:19:56] And that's kind of really all of the heavy lifting that's done on my side.
[00:19:59] And we're able to go and generate.
[00:20:04] And I'm just going to move over here as we generate the actual solution.
[00:20:08] And as we're going through this and as we're building this, what we're able to do is jump to
[00:20:14] a completed agent already.
[00:20:16] And from this completed agent, what we're able to do is take a look at all of the unit testing scenarios
[00:20:21] that were identified and built, as well as take a look at the underlying solution with the integration
[00:20:28] with N8N to see how each of these three individual agents are orchestrated together to solve this
[00:20:34] complex problem and being able to see what that entire end-to-end workflow looks like.
[00:20:40] As well as we're able to dive deeper into the design and take a look at all of the configuration and
[00:20:46] capabilities that are built into this solution, everything from what are the tools and skills
[00:20:54] to what are the individual evaluations that are needed for this solution.
[00:21:00] This is based on our data, our landscape, and really what is needed to check the success of this.
[00:21:07] And this type of solution is exactly what it takes to reduce pricing disputes and protect margin at
[00:21:12] scale. This is really how we turn expertise into agents that run the business from insight to impact
[00:21:20] to value. Back to you, Philip.
[00:21:25] Thank you so much, Chris. Fantastic demo.
[00:21:29] Thank you. Appreciate it.
[00:21:35] And that's Jewel Studio. That gets you to the outcome so much faster and far more accurately than ever before.
[00:21:41] We tested building this agent and many more on comparable platforms.
[00:21:45] And of course, while we cannot do the code generation faster, in fact, because of all the context a
[00:21:50] little bit slower, Jewel Studio wins in every other dimension it has been designed for,
[00:21:55] bringing you to the outcome 10x faster. And it does it at a far higher accuracy because it has the
[00:22:01] understanding of the SAP domain and it has the understanding of all the latest APIs you've got to use
[00:22:07] a lot more. And finally, developers love it. We have given this experience to a thousand developers who
[00:22:14] tested the alpha version of it and the feedback speaks for itself. And that's the next generation of
[00:22:20] Jewel Studio starting to roll out to first customers starting June. Next in the platform, let's talk about
[00:22:27] contextualize and reason. Because Christian mentioned it already, agents are only as powerful as the context they are
[00:22:34] operating on. But the problem still is, we know it, the data is fragmented and it's trapped in
[00:22:40] proprietary formats. And of course, it's not semantically aligned. Now, business AI platform starts
[00:22:45] on a strong foundation, SAP Business Data Cloud, which acts as the business data fabric that gives you
[00:22:52] universal business context across your entire multi-cloud landscape, both for SAP and non-SAP data.
[00:22:58] Business Data Cloud is one of the fastest growing products in SAP's history. Customers like Baker Hughes
[00:23:05] and Zalando are getting amazing business benefits from it already today. For example, by using any of
[00:23:11] the 300 data products that are coming out of the box managed by SAP, so you don't have to do the heavy
[00:23:17] lifting. However, these data products are coming only from the SAP world. But of course, there's so much
[00:23:24] more data that needs to get integrated to empower our agents, like customers coming from Salesforce,
[00:23:29] employees coming from Workday, or any other application. This is where Relto is coming in,
[00:23:36] allowing you to create the single golden record for all your master data end-to-end, so AI agents are able to
[00:23:43] take a reason over consistent master data. And to help you with your data modeling efforts, we are
[00:23:49] introducing Juul agents into BDC as well. For example, our all-new data products generation agent takes the
[00:23:57] heavy lifting away and the same experience we saw in Juul Studio to entirely create new data products or
[00:24:03] derived data products in virtually no time. BDC, of course, is open by principle. BDC Connect, introduced last year,
[00:24:11] allows you to integrate and share with a variety of data platforms. And today, we are excited to add
[00:24:18] Amazon Athena to the mix as well. But we didn't stop there. We're so excited about our latest intent
[00:24:25] to acquire Dremio, a high-performance data energetic lake house with cutting-edge data federation across
[00:24:32] any cloud and any traditional legacy database. Once this acquisition is closed, BDC will 100% support the
[00:24:40] open table format Apache Iceberg for plug-and-play interoperability with any data store. And combined
[00:24:47] with BDC, this will build the foundation to let your agents reason across data from any cloud, any
[00:24:54] environment, without data movement. Now, with this, we have a solution to build up tables and data on
[00:25:02] data on the fly. And this gives us the next stage which is predictions on the fly. Because the opportunity
[00:25:08] in business AI was never just large language models. They're fantastic, but they're just one part of the
[00:25:13] equation. It is AI for decision intelligence. Reasoning on structured business data. Predictions like demand
[00:25:22] forecasts and retail or predictive maintenance and asset management. To do such things, we had to
[00:25:28] rely so far on what we call narrow AI models. One for each task. Now, if you want to solve for 10 of such
[00:25:35] predictive tasks and save for 10 company codes, you have to train easily 100 AI models. Months of work, and you
[00:25:44] need a lot of data scientists, which oftentimes you don't have. And it's a significant investment. Hard to scale and
[00:25:50] adapt. So what we did is, we basically put all of that into a one giant model, which we introduced last year,
[00:25:57] called Rapid1. Which is the most performing tabular foundation model on SAP data. And today, we're excited to
[00:26:04] introduce the next model generation with Rapid1.5. This does not only allow for far better accuracy on
[00:26:12] tabular data, but also introduces an all-new chat API that allows you for on-the-fly what-if analysis and
[00:26:19] predictive simulation. And a big focus was on explainability, so you can always follow what the
[00:26:25] foundation model is doing based on the rows and the columns that led to the prediction. All of that without
[00:26:31] any AI model training because it just works on the fly. You can check it out today on rapid.cloud.sap.
[00:26:40] But there's one more thing because we're taking the next leap to the finders category. We're excited
[00:26:48] to share our intent to acquire prior labs, a front AI lab for tabular foundation models, and bringing the
[00:26:54] latest tab PFN model family to live actually today on their platform. While Rapid1.5 is best in class for
[00:27:03] the SAP data, their tab PFN model family is best in class for non-SAP data, unlocking industry-specific
[00:27:11] use cases, for example, financial trading. And these are just a few highlights of what's new and
[00:27:18] what's new and contextualize and reason in business AI platform. Next up, govern. You know the thing,
[00:27:24] right? Agents are now everywhere. Some are great, some are not. And almost no one really has a
[00:27:31] consistent picture, no central governance. And AI Agent Hub is the place that changes that. It's one command
[00:27:38] center to discover, manage, and govern SAP and non-SAP agents, MCP servers, and everything else in your
[00:27:47] landscape end to end. SAP AI Agent Hub is built on SAP LeniX. That's already used by more than 25% of
[00:27:54] the Fortune 500 companies, and today we're taking it to the next level. AI Agent Hub not only allows
[00:28:01] you now to discover all your agents in context, your landscape or your business processes, but once you
[00:28:07] identified each of those SAP or non-SAP agents, you can actually control their risk, define architectural
[00:28:14] boundary conditions or compliance rules. And once you're done with that, you can mark an agent as
[00:28:20] verified. And business AI platform and AI Agent Hub are making sure that only verified agents can operate
[00:28:26] in your landscape to ensure highest levels of control. Furthermore, once you then deploy these agents, of
[00:28:34] course, you want to see what they're doing. We bring all the telemetry, all the observability into one place,
[00:28:39] and now you can navigate seamlessly into cloud ALM from AI Agent Hub. So you can watch their health, the goal
[00:28:45] completion, or the tool calling correctness. In addition, you can then also from the AI Agent Hub go over
[00:28:51] into agent mining from Signavio. So you can watch their behavior and find further optimization opportunities
[00:28:58] against your KPIs. And finally, we're also mapping all your agents into SAP success factors. So you can see
[00:29:05] the impact these agents actually have on your workforce end-to-end. The full governance life cycle of
[00:29:12] AI Agent Hub will be available as generally available in Q3 this year and is now part of SAP Business AI
[00:29:19] is now part of SAP Business AI platform out of the box at no extra charge. And this is the platform the
[00:29:25] Autonomous Enterprise is going to run on. With that, back to you Christian.
[00:29:39] Yeah, thanks Philip. KPMG is a great example of how our ecosystem is already embracing the new platform.
[00:29:49] To ensure our Business AI platform will be the most loved platform in the market, we are making three
[00:29:57] further exciting announcements. First, all our SAP AI agents are open and exchange data with third-party
[00:30:07] agents without any limits and at no additional charge. Second announcement, we are excited that AI
[00:30:16] development with Joule Studio 2.0 will be available for free. And we will also offer the one-time for free
[00:30:25] until the end of this year. And third, we will invest over 100 million Euro into our ecosystem to build
[00:30:34] agents and drive AI adoption. All of these wonderful partners are already developing agents on the new
[00:30:50] new platform. And look at their fantastic feedback. So, let's hear more from our partner at Anthropic.
[00:31:00] We build Claude, the AI that enterprises trust most. At Anthropic, we build frontier AI systems. And I've
[00:31:11] learned that when the stakes are high, enterprises reach for the AI they trust. We've built the company around the
[00:31:19] conviction that as AI becomes more capable, enterprises need to understand how it makes decisions and to know
[00:31:27] it will operate within the boundaries they set. Earning that trust has costs. We've delayed launches,
[00:31:34] over safety concerns, and published research even when it's controversial. These are not easy decisions in the
[00:31:41] process. But we believe they're the fastest moving industry on earth. But we believe they're the right
[00:31:45] ones to make. Which brings us to SAP. The world's largest enterprises run on SAP. And that's exactly where
[00:31:54] trusted AI belongs. And that's why Claude models are available to SAP's customers on the SAP Business AI platform.
[00:32:02] By combining Claude with SAP's depth and scale, we can help hundreds of thousands of organizations
[00:32:10] use AI throughout every part of their business. Inside Juul, Claude will power agents that take action across
[00:32:18] finance, HR, procurement, and the supply chain. This puts AI to work inside the systems you've already invested in, and the
[00:32:26] processes your people already rely on. SAP is a great example of a company that is bringing AI into the enterprise in a way their customers can actually trust.
[00:32:38] And Tropic is a great example of how we are working together with partners on our new platform. One AI customer of SAP is one of the oldest and largest financial institutions in the world.
[00:32:54] financial institutions in the world. And in highly regulated industries like banking, accuracy and compliance matter even more.
[00:33:02] Let's talk about their AI transformation. Welcome on stage, the CFO of JPMorgan Chase, Jeremy Barnum.
[00:33:22] Jeremy, welcome to Sapphire. Look at all of these people. Is this your first time, Sapphire?
[00:33:28] It is my first time indeed. It's impressive and intimidating.
[00:33:32] Every day, JPMorgan Chase serves millions of customers and you're actually facilitating trillions of dollars in transactions.
[00:33:44] So clearly, technology is the backbone of your company. How do you manage the trade-off between fast innovation without compromising on risk and compliance?
[00:33:54] Yeah. Yeah. Yeah. So let me give you a sense of that scale. We serve over 86 million US customers and 7 million small businesses.
[00:34:04] And we process about 12 trillion in payments across 120 currencies every day. And technology is the backbone of all of that. It's what allows us to serve our clients seamlessly and securely.
[00:34:16] But that scale brings complexity, which can slow you down and introduce risk. So we're very focused on moving fast without compromising safety.
[00:34:26] And that means investing in common tools and platforms that are easily deployed and available firm wide. So in that context, SAP has been a critical partner for us.
[00:34:36] And one particularly notable recent milestone in that partnership has been our decision to invest in a major upgrade of our general ledger to SAP's latest version in order to bring our entire financial ecosystem into one unified intelligent platform.
[00:34:54] So, Jeremy, I mean, when we talk about scale, this is scale. So we are super proud to be your partner on this journey. Now, this morning, we talked about how to make AI successful in business. Now, for you, especially as a bank, an 80% accuracy is not an option. Now, how can SAP and JPMorgan, how do we work together to make AI more accurate?
[00:35:19] Yeah, I agree. I agree. I have to say JPMorgan Chase, we like our unicorns with only two ears, please. Thank you very much. It's very important.
[00:35:28] But now, AI is the most significant trend in technology in a generation and frankly, in society at large in a generation. And as a result, everyone, I think all of us, are experiencing pressure to use it everywhere. But in a finance organization, the risk of that is that you sprinkle AI on broken processes. And you miss the opportunity.
[00:35:46] You miss the opportunity to retire technical debt and modernize the entire ecosystem. So from our perspective, AI is only as good as the data and processes underneath it. It can't reach its full potential in a fragmented legacy environment. So we're very focused on end-to-end process reengineering. And through Rise with SAP, we're embedding intelligence directly into the workflows. We're already starting to integrate agents to make the data
[00:36:05] management of the ledger more efficient. One example is an upstream agentic solution that proactively catches issues with systemic feeds so we can correct them before anything posed to the ledger. And over time, it learns patterns so we can fix root causes permanently.
[00:36:23] Importantly, the agents that we've built are not inventing their own business rules. Those rules, rather, come directly from SAP's embedded control framework and every AI-driven intervention is logged and fully traceable, giving us the transparency and audit trail that we and our various stakeholders expect.
[00:36:41] Sounds like music to me.
[00:36:47] JPMorgan Chase and SAP, you are not only a customer to us, we are also partners. We are partners in the payment space. We are embedding banking services of JPMorgan Chase into SAP's workflows for our joint customers. So what is your view on our partnership and any ideas for the future?
[00:37:15] JPMorgan Chase: Yeah. Now, the partnership between JPMorgan Payments and SAP combines enterprise software and AI expertise with an extensive set of integrated payment solutions at real scale. And what this means in practice is that clients can seamlessly access JPMorgan Payments solutions directly within their SAP system. Everything from trade finance and real-time reporting to global payment rails without leaving the workflows they already operate in.
[00:37:43] JPMorgan Chase: We're continuing to develop new solutions together that enhance digital experiences and help our clients grow. And this partnership is only getting deeper. We're now beginning to work with the SAP team on exploring agentic capabilities to create a much more automated and intelligent treasury environment for our joint customers.
[00:38:02] JPMorgan Chase: Could not have said it better. Jeremy, if you could summarize our partnership in a few words.
[00:38:09] JPMorgan Chase: Sure, Christian. I can do that. I'm going to use three words: scale, speed, and trust.
[00:38:15] JPMorgan Chase: Perfect. Jeremy, first of all, thanks a lot for the trust, for the partnership, the AI co-innovation. And I wish you and JPMorgan Chase only the very best. Thank you very much. JPMorgan Chase: Thank you very much. JPMorgan Chase: Thanks a lot.
[00:38:29] JPMorgan Chase: The power of the new AI platform enables us to transform our software application layer. And as a result, we are reimagining how your businesses will run.
[00:38:48] JPMorgan Chase: Our ERP and industry application, or let's call them systems of execution, having generated incredible value for our customers. I hope you can agree to that.
[00:39:03] JPMorgan Chase: From R2 to R3 to ECC to S4 to our modular cloud suite. I spent the first 15 years of my career working with finance transaction codes like PC02 or FB50.
[00:39:22] JPMorgan Chase: And I was a heavy power user of the BW analytic store. Still I am sometimes.
[00:39:27] JPMorgan Chase: Ten years ago, I performed right here on this stage a digital boardroom demo.
[00:39:33] JPMorgan Chase: Look at this picture. I'm not only got older, a couple of things have changed, including the CEO.
[00:39:41] JPMorgan Chase: The digital boardroom, I can remember these times really well, was a revolution at that time.
[00:39:53] JPMorgan Chase: Still, it was always about the end users to tell the system what to do, or to analyze the figures provided by the analytical solution.
[00:40:04] JPMorgan Chase: But now, this is changing. Today, we are very proud to announce that our system of execution will transform into SAP's autonomous suite.
[00:40:18] JPMorgan Chase: The new autonomous suite will span across five domains: Autonomous Finance, Band, Supply Chain, HCM, NCX.
[00:40:29] JPMorgan Chase: As well, we are building on our deep industry expertise to launch industry AI.
[00:40:37] JPMorgan Chase: Why do we consider this to be the biggest evolution ever in the history of SAP's application business?
[00:40:46] JPMorgan Chase: Because the autonomous suite is changing the game in five key dimensions.
[00:40:53] JPMorgan Chase: The autonomous suite is role-centric with a tool assistant for every persona in your company, always with the human in the loop.
[00:41:02] JPMorgan Chase: It's outcome based. Our agents listen, understand, steer, and manage the system of execution, what we just have heard from JPMorgan Chase.
[00:41:12] JPMorgan Chase: It's audit ready. We provide full traceability for every action performed by an agent with the highest compliance standards.
[00:41:21] JPMorgan Chase: And it is extensible by design. You and the ecosystem can extend the autonomous suite layer with new agents and skills every hour.
[00:41:32] JPMorgan Chase: And our autonomous suite is open by principle. Our free of charge orchestration layer will ensure SAP and non-SAP agents work hand in hand.
[00:41:44] JPMorgan Chase: This is the beginning of something better. Let's hear from one of our key partners how we are making enterprise software more powerful than ever.
[00:41:55] JPMorgan Chase: It's great to be here at Sapphire. What SAP and NVIDIA are building together is one of the most important platforms in enterprise AI.
[00:42:04] JPMorgan Chase: NVIDIA supply chain is incredibly complex. Millions of parts, hundreds of partners and factories, all connected through SAP.
[00:42:14] JPMorgan Chase: But what's changing is not just how enterprise systems are managed, it's how work actually gets done.
[00:42:23] JPMorgan Chase: From hand coded software to AI that can understand reason and act. AI no longer simply answers questions. It works for you. And enterprise systems are where work happens.
[00:42:38] JPMorgan Chase: Finance, supply chains, procurement, and every workflow in between. SAP is the foundation of enterprise. And now they're building the agents that sit on top of it.
[00:42:50] JPMorgan Chase: Trained on proprietary data with the skills to act. Soon, every company will have a workforce of agents. These specialized agents will not replace enterprise software. They will make enterprise software more powerful than ever.
[00:43:05] JPMorgan Chase: And with NVIDIA, agents can be built, evaluated, deployed, and governed. We created OpenShell so agents can act inside a company safely and with clear boundaries.
[00:43:18] JPMorgan Chase: And this work is happening as an open source project. So everything we learn goes back to the community. SAP is embedding OpenShell across its entire platform to secure enterprise AI at scale.
[00:43:33] JPMorgan Chase: Agents can take action, but only what they're allowed to do. They can access data, but only what they're permitted to see. They can execute workflows, but every action is traceable.
[00:43:46] JPMorgan Chase: This is how we make AI safe and useful. It understands the business. It follows the rules. It uses the tools. And it moves fast.
[00:43:55] JPMorgan Chase: Thank you, Christian, Philip, and the SAP team. The autonomous enterprise is no longer a vision. It starts now.
[00:44:05] JPMorgan Chase: Please welcome to the stage, Mohamed Alam.
[00:44:08] Mohamed Alam: A big welcome to Sapphire, and thank you for being here. So we didn't just build a new business AI platform. We built it, and then we used it natively to really completely change the portfolio of products we have into a truly new business AI platform.
[00:44:23] JPMorgan Chase: So we didn't just build a new business AI platform. We built it, and then we used it natively to really completely change the portfolio of products we have into a truly autonomous suite.
[00:44:32] JPMorgan Chase: Underpinning the autonomous suite are out of the box agents, hundreds of agents cutting across all core business processes.
[00:44:45] JPMorgan Chase: These agents come together into what we call assistants or dual assistants. We've mapped these assistants to roles across the core processes of an organization because we know that the first step in realizing value from AI is to empower your people to do more, do it better, or do things that just weren't possible to be done before.
[00:45:09] JPMorgan Chase: These assistants can be triggered by humans, they could be system triggered with humans in the loop, or ultimately set up to run autonomously collaborating across multiple assistants once you have built the right trust and confidence in the results of their execution.
[00:45:29] JPMorgan Chase: They're also designed with outcomes as a core objective.
[00:45:35] JPMorgan Chase: Each assistant has a defined set of KPIs that you can expect it to deliver. The outcomes are then tracked in the SAP AI agent hub that Philip showed to ensure full transparency and accountability to you and your business.
[00:45:49] JPMorgan Chase: Because ultimately, what you want is positive business impact rather than just a count of agents deployed as the measure of success for your business.
[00:46:00] JPMorgan Chase: We also know that no two businesses are alike. So not every agent is going to work completely out of the box for you. And for this reason, we've made extensibility a core design principle.
[00:46:14] JPMorgan Chase: You can extend any of these agents by adding tools, workflow steps, and even code through the same simple experience that you saw in Joule Studio earlier. This allows you also to connect them to your non-SAP application, because we know you're going to have to do that.
[00:46:30] JPMorgan Chase: You can, of course, also add completely new custom agents to any of these assistants to complete the autonomous execution for your enterprise.
[00:46:40] JPMorgan Chase: But we didn't just stop there. We know that the traceability and auditability of the agents is critical for you to build your confidence and leverage them at scale.
[00:46:52] JPMorgan Chase: And that is why we're proud to announce that we follow a SOX audit-compatible ISO-certified development process for building these agents.
[00:47:01] JPMorgan Chase: All our agents are built on this certified compliance framework developed in coordination with our own auditing firm as well as an external audit partner to ensure audit readiness at the agent level, particularly for the audit-relevant agents.
[00:47:20] JPMorgan Chase: Multiple assistants then come together to form an autonomous domain.
[00:47:26] JPMorgan Chase: In autonomous finance, for instance, we have assistance for AP, for AR, for Treasury, for controlling, and so on, an assistant for every role, each with its N number of agents and with its uniquely defined outcomes.
[00:47:42] JPMorgan Chase: We have built these autonomous domains, again, not just for finance, but across the entirety of your core business plan.
[00:47:50] JPMorgan Chase: So let's go through them.
[00:47:54] JPMorgan Chase: So let's go through them.
[00:47:56] JPMorgan Chase: In autonomous spend, we have assistance from supplier management to sourcing, contracting, and buying.
[00:48:00] JPMorgan Chase: For autonomous supply chain, we have assistance spanning the entire make-to-deliver processes.
[00:48:07] JPMorgan Chase: For autonomous HCM, we have assistance like recruiting, payroll, and career and development that cut through the entire HCM set of processes.
[00:48:17] JPMorgan Chase: And finally, for autonomous CX, we have assistance covering sales, service, commerce, and marketing processes.
[00:48:25] JPMorgan Chase: All of these domains then come together to help you become an autonomous enterprise, allowing you now as an organization to do things better, more efficiently, and unlock value that you just weren't able to unlock before.
[00:48:43] JPMorgan Chase: Across all of these domains, we're proud to be launching 224 agents and 51 assistants, a number that will only grow monthly from here on out.
[00:48:57] JPMorgan Chase: So we built all of these assistants, and we made extensibility a first-class principle.
[00:49:03] JPMorgan Chase: But we realized that there was still something missing, something big, your company context, the organizational memory of your company that sits in the minds of people that have executed those processes for years and years.
[00:49:21] JPMorgan Chase: This knowledge, often referred to as decision traces, often sits as unstructured data encapsulated in process models, policy documentation, even chats, and long emails.
[00:49:35] JPMorgan Chase: Making it effectively invisible to any agent on any agentic platform.
[00:49:41] JPMorgan Chase: So we built something to address this tribal knowledge gap, something we call the company memory.
[00:49:48] JPMorgan Chase: Company memory is a knowledge management layer.
[00:49:52] JPMorgan Chase: You can call it a context graph for your company specifically.
[00:49:57] JPMorgan Chase: It's built on the same foundation as SAP Signavio, so it's already natively aware of your process models and your process insights.
[00:50:07] JPMorgan Chase: You can additionally feed it your policies and procedures document, relevant content from teams and Slack channels, and even long email approval chains or exception chains, from which it then extracts what we call process atoms,
[00:50:24] JPMorgan Chase: which are small structured units of business process knowledge.
[00:50:29] JPMorgan Chase: Each one can guide an agent on what to look for, what to do, and more importantly, what not to do.
[00:50:35] JPMorgan Chase: When an agent makes a call, it also maintains traces for full transparency and control.
[00:50:41] JPMorgan Chase: When it runs into an exception, it adds to the company memory on how it dealt with that exception.
[00:50:50] JPMorgan Chase: You, of course, have the power to directly update a rule, review a rule, a process atom manually, and once done, all agents adapt to it instantly.
[00:51:01] JPMorgan Chase: This is what allows us to bring the best of the public LLMs, SAP's unique context layer, and your own company context together to really deliver the results that you can rely on.
[00:51:15] JPMorgan Chase: You can clap.
[00:51:16] JPMorgan Chase: I think there's a couple of people that liked it in the back.
[00:51:20] JPMorgan Chase: Now, I know what some of you may be thinking.
[00:51:27] JPMorgan Chase: You know, you love the assistants and the agents, and you love the company memory story, and you can't wait to deploy in your landscape.
[00:51:36] JPMorgan Chase: But you still might have a long way to go before you complete your modernization journey to our latest cloud applications.
[00:51:45] JPMorgan Chase: However, your business, of course, expects you to deliver value today.
[00:51:50] JPMorgan Chase: Well, we've thought of that, too.
[00:51:53] JPMorgan Chase: And we're really excited to announce that we are enabling a significant percentage of these dual assistants and agents to work in hybrid landscapes with the ability to connect to your S4 on-premises and ECC landscapes.
[00:52:10] JPMorgan Chase: I thought I would need to prompt an applause for this one.
[00:52:17] JPMorgan Chase: That turned out to be true.
[00:52:18] JPMorgan Chase: This will be available for our customers that have started their modernization journey on Rise, of course.
[00:52:24] JPMorgan Chase: We've done this so you can start generating value from AI today on the SAP Business AI platform while you're modernizing your estate.
[00:52:34] JPMorgan Chase: Finally, as you would expect, we're also proud to reiterate our commitment to openness and enabling A2A across all of these agents and assistants.
[00:52:44] JPMorgan Chase: Because we know that some of you may have, unfortunately, selected other agentic platforms for your organization.
[00:52:51] JPMorgan Chase: So instead of having to rebuild all of these core business process agents from the ground up, you can use A2A to connect these with your agentic platform of choice to get the benefit of the outcome-driven, out-of-the-box certified jewel agents and assistants.
[00:53:09] JPMorgan Chase: Okay, so we've talked enough about these assistants.
[00:53:12] JPMorgan Chase: Now let's take a look at one of our more popular finance assistants in action.
[00:53:17] JPMorgan Chase: Please join me to welcome Sophia Levins onto the stage.
[00:53:21] Sophia.
[00:53:22] Sophia Levins: Thank you, Muhammad.
[00:53:35] Sophia Levins: It's incredible to be here with all of you.
[00:53:39] Sophia Levins: You've heard about the autonomous enterprise, and what I get to do is show you how it feels to work in this new way.
[00:53:48] Sophia Levins: Today, we're looking at the financial closing assistant.
[00:53:53] Sophia Levins: And in an era where companies can run supply chains in near real time and answer customer questions in seconds, the close can still take a week, sometimes longer.
[00:54:07] Sophia Levins: Not because the work is hard, but because the work is fragmented.
[00:54:12] Sophia Levins: All right, let's dive in here.
[00:54:15] Sophia Levins: What we're going to start with is looking at last quarter and how that went.
[00:54:26] Sophia Levins: What you'll see is this company has 12 legal entities, four ERP systems, six different currencies, hundreds of different reconciliations that depend on a human in one country waiting for a human in another.
[00:54:41] Sophia Levins: The close is not slow because financial teams are slow.
[00:54:46] Sophia Levins: It's slow because the work is person to person.
[00:54:49] Sophia Levins: What I'm going to show you is a new model, not automation.
[00:54:54] Sophia Levins: Automation runs scripts.
[00:54:56] Sophia Levins: What you'll see here is that financial closing assistant, hard at work coordinating across all the different agents.
[00:55:05] Sophia Levins: It's also brought to my attention the 18 things that need a bit of approval.
[00:55:12] Sophia Levins: We're going to start here with the accounting accruals agent that has four proposals for me to review.
[00:55:19] Sophia Levins: You can see these have the details we need and a confidence level that's been set by my company.
[00:55:27] Sophia Levins: I can see this professional services accrual is just below the confidence I set.
[00:55:34] Sophia Levins: I approve and the system remembers.
[00:55:38] Sophia Levins: Now, over in inner company reconciliation, which is typically the hardest part of close, you can see most of these are completed and working on it.
[00:55:50] Sophia Levins: You also see we have some variances, each with the root cause already done.
[00:55:57] Sophia Levins: You can see timing, cutoff, and the occasional genuine dispute.
[00:56:05] Sophia Levins: One click matches the records on both sides in both currencies.
[00:56:10] Sophia Levins: What used to take weeks of emailing back and forth now happens in a single click.
[00:56:17] Sophia Levins: A pattern was recognized because the system has that company memory.
[00:56:24] Sophia Levins: It learns how your controllers think.
[00:56:27] Sophia Levins: Every approval, every override, every comment becomes part of how the agents behave next period.
[00:56:34] Sophia Levins: The system doesn't close the books.
[00:56:37] Sophia Levins: It learns the company that's closing them.
[00:56:40] Sophia Levins: Let's look back to what changed.
[00:56:43] Sophia Levins: So I can easily go back to Q1 and ask the system to compare with what we just saw in Q2.
[00:56:50] Sophia Levins: And what we're going to see here is that in the Q2 close, it was faster with less variances, with less items for the human to deal with.
[00:57:04] Sophia Levins: Each close will teach the next one.
[00:57:05] Sophia Levins: The system gets sharper, the exceptions get rarer, the close stops being something you survive, and becomes something that can run itself.
[00:57:17] Sophia Levins: Okay, Muhammad, back over to you.
[00:57:21] Sophia Levins: I'm sorry.
[00:57:23] Sophia Levins: So as exciting and energizing the topic of financial close is, it's a bit of a joke, though I'm sure Dominic here, our CFO, is thinking it's actually a true statement.
[00:57:37] Sophia Levins: We have over 12 customers that are already on their way in deploying the close that you just saw on our new business AI platform in their environments, including Dominic as well, for SAP.
[00:57:49] Sophia Levins: For many of these assistants, not just this one, we've been working with early design customers, not just to build, but also to deploy and validate the results.
[00:57:59] Sophia Levins: So let's look through some of those stories.
[00:58:01] Sophia Levins: Kaser Compressor is utilizing our product design assistant to help define product requirements, create and update product design, and hand it over to the execution engine.
[00:58:12] Sophia Levins: On the HCM side, Ericsson is leveraging intelligent role recommendations to implement analytics.
[00:58:18] Sophia Levins: To implement aligned, consistent, and measurable goals across their 85,000 employees.
[00:58:25] Sophia Levins: So each one of them can have personalized recommendations on their own journeys.
[00:58:31] Sophia Levins: With the merchandising assistant in CX, Petco turns fragmented and inconsistent content checks into a guided workflow that scores content readiness, optimizes the product data, and surfaces assortment gaps.
[00:58:47] Sophia Levins: For AI based discoverability across all their channels.
[00:58:51] Sophia Levins: We're proud to be working with these organizations and many others to unlock value through SAP Business AI.
[00:58:57] Sophia Levins: Now there's one thing that we've shown you all throughout the keynote, but we haven't yet explicitly talked about.
[00:59:06] Sophia Levins: And it's actually been present and working hard to even introduce all the speakers.
[00:59:13] Sophia Levins: And that's Juul itself.
[00:59:15] Sophia Levins: With Juul, we are fundamentally reimagining how users will interact with SAP applications in the future.
[00:59:24] Sophia Levins: It's probably no surprise to anyone here that as SAP, we're really very famous for our amazing user experiences in our core ERP applications.
[00:59:36] Sophia Levins: Though I think infamous might be the right word.
[00:59:39] Sophia Levins: I think our CEO actually was brave enough to show even some of our great screens from 10 years ago, I think.
[00:59:45] Sophia Levins: So we thought since we're so famous, why don't we just completely change the paradigm of user interaction?
[00:59:53] Sophia Levins: Some call it zero UI these days, though the word headless also seems to be in vogue.
[00:59:59] Sophia Levins: We like to call it an appless experience and a no apps experience.
[01:00:05] Sophia Levins: Appless meaning an experience layer that allows you to interact with your underlying applications without having to be in them.
[01:00:14] Sophia Levins: And no apps meaning you don't even need now an app for it.
[01:00:21] Sophia Levins: The capability will generate itself on the fly for your users to use either one time or repeated use without you having to go build them.
[01:00:31] Sophia Levins: All of this and more is what is available in spaces in Juul.
[01:00:38] Sophia Levins: Spaces is also where our agents interact very immersively with the user, what you saw just now in the financial close assistant with their human counterparts.
[01:00:50] Sophia Levins: Let's roll the video to take a deeper look into what spaces are.
[01:00:55] Spaces in Juul work have been designed to help you get your job done.
[01:01:00] Sophia Levins: These spaces are unique, context driven, built for the task at hand.
[01:01:04] Sophia Levins: They are outcome driven, where humans and autonomous agents work together in harmony.
[01:01:09] Sophia Levins: The right information and actions are generated for you, providing structured insights and full control.
[01:01:15] Sophia Levins: Work directly with your content, confirm decisions, complete workflows, all without switching between applications.
[01:01:22] Sophia Levins: They are dynamically generated transactional and analytical content that bring powerful business insights directly into your workflows.
[01:01:30] Sophia Levins: You always stay in control.
[01:01:32] Sophia Levins: And Juul work comes with a full dark mode because great software adapts to the person, not just the task.
[01:01:38] Sophia Levins: This is how modern work will get done.
[01:01:41] Sophia Levins: Hopefully that's exciting.
[01:01:44] Sophia Levins: Juul spaces.
[01:01:50] Sophia Levins: On the basis, what you just saw, along with a completely reimagined Juul conversations experience and a brand new Juul Studio 2.0 that Philip showed you, is now part of what we call Juul work.
[01:02:07] With Juul work, we're excited to announce that we're taking a massive step forward in supercharging the capabilities of Juul as we know it today.
[01:02:17] Sophia Levins: Internally, we even referred to it as the V10 version of Juul, though our marketing folks didn't like as branding it like that externally.
[01:02:24] Sophia Levins: So we kept it simple, Juul.
[01:02:25] Sophia Levins: Today, the Juul you know is rag-based, limited in context, governance, and its action space and scalability.
[01:02:32] Sophia Levins: With Juul work, we're bringing a claw-based, agentic harness to Juul along with computer and file access, better support for open standards such as MCP and A2A, access to a more complete knowledge base.
[01:02:46] Sophia Levins: And, of course, amazing visualizations on the fly.
[01:02:52] Sophia Levins: In the world of SaaS, we believe not all applications and application providers are created equal.
[01:02:59] Sophia Levins: At SAP, hopefully you see that we're busy rewriting the apps and the platform and the experiences playbook in a way that will unlock value for you that has never been possible before.
[01:03:12] Sophia Levins: Through the power of our business AI platform and our autonomous suite, we have agents that drive outcomes, assistants that empower every role, autonomous domains that transforms entire functions, and a Juul experience that reshapes employee engagement.
[01:03:31] Sophia Levins: But we're still not done yet.
[01:03:35] Sophia Levins: While the autonomous domains cut across all core processes, we know every industry has its own unique value chain.
[01:03:43] Sophia Levins: How we help you unlock the potential of that value chain is up next with Industry AI and Sebastian Steinhauser.
[01:03:53] Sophia Levins: But before we do that, let's hear from some more of our customers who are deep into their AI journey with SAP.
[01:04:01] Sophia Levins: A big thank you for listening and thank you for your trust.
[01:04:03] Sophia Levins: AI is an important element for us.
[01:04:12] It's about identifying those use cases that really provide the most value.
[01:04:17] Sophia Levins: SAP Business AI has been designed into the core functions of Data Extreme's Omnus+ platform.
[01:04:23] Sophia Levins: It's the Swiss army knife of IT.
[01:04:26] Sophia Levins: This transformation not only saves thousands of work hours annually, but also optimizes costs.
[01:04:34] Sophia Levins: SAP's CX AI Toolkit, it works and it helps our refs focus on our customers and what suits them best.
[01:04:43] Sophia Levins: The invoice assistant with S/4HANA is cutting the average invoice inquiry from 30 minutes to just two minutes.
[01:04:50] Sophia Levins: Our accounts payable backlog is down by 25%.
[01:04:54] Sophia Levins: Every large enterprise is somewhere on a transformation journey.
[01:05:00] Sophia Levins: The companies that get this right won't be the ones with the most AI.
[01:05:04] Sophia Levins: They'll be the ones with the AI that understands how their businesses operate like SAP does.
[01:05:10] Sophia Levins: It's the most important part of the world.
[01:05:12] Sophia Levins: Thank you very much.
[01:05:13] Sophia Levins: Please welcome to the stage, Sebastian Steinhäuser.
[01:05:16] Sophia Levins: Hasn't this been great so far?
[01:05:30] Sophia Levins: Now, as Mohammed said, there's at least one more thing to complete this.
[01:05:36] Sophia Levins: The autonomous suite.
[01:05:38] Sophia Levins: Let's start with a quick raise of hands.
[01:05:39] Sophia Levins: Who of you is using SAP 100% in standard?
[01:05:40] Sophia Levins: Raise your hand.
[01:05:41] Sophia Levins: Trick question.
[01:05:42] Sophia Levins: So now, raise your hand if you are using SAP with industry-specific solutions and extensions.
[01:05:58] Sophia Levins: Yes?
[01:05:59] Sophia Levins: Yes?
[01:06:00] Sophia Levins: Yes.
[01:06:01] Sophia Levins: Yes.
[01:06:02] Sophia Levins: Yes.
[01:06:03] Sophia Levins: I thought so.
[01:06:04] Sophia Levins: Industry solutions have always been the superpower of SAP.
[01:06:11] Sophia Levins: And this year, we bring that power back with full force.
[01:06:17] Sophia Levins: While some are just now discovering concepts like forward deployed engineering, we have always known since our founding days,
[01:06:25] Sophia Levins: Real enterprise transformation requires deep industry understanding.
[01:06:35] Sophia Levins: And we understand how your assets are maintained, how your manufacturing processes run, and how your brands win on the shelf.
[01:06:44] Sophia Levins: And we do so across 26 industries like no other software or AI company on this planet.
[01:06:54] Sophia Levins: Hey, Jules, tell me more about the industry-specific capabilities SAP provides.
[01:07:00] Jules Verins: Hey, Sebastian.
[01:07:02] Sophia Levins: Here's an overview of SAP capabilities across more than 25 industries.
[01:07:07] Sophia Levins: So now, we are taking this deep domain expertise and turn it into the world.
[01:07:12] Sophia Levins: This is what industry AI is all about.
[01:07:19] Sophia Levins: Industry AI is how we bring that industry-specific process logic, the data context, and the regulatory rules into unique AI-powered solution tailored to your core business.
[01:07:34] Sophia Levins: And we do this together with all of you on the business AI platform.
[01:07:41] Sophia Levins: Delivered end-to-end by SAP as an outcome instead of SKU patchwork.
[01:07:47] Sophia Levins: We are starting with a select group of customers given the high demand, and we are delivering autonomous industry solutions starting with seven.
[01:07:56] Sophia Levins: From autonomous adaptive production to autonomous project delivery, close to your core operations and tightly integrated with your core execution systems.
[01:08:09] Sophia Levins: Where each one caters to multiple industries delivering values for customers like CHS, Roche, Deloitte, Vestas, and so many more already now.
[01:08:19] Sophia Levins: The initial feedback has been phenomenal.
[01:08:23] Sophia Levins: Let's dive deeper into one of these industry domains.
[01:08:26] Sophia Levins: Let's take autonomous regulated manufacturing.
[01:08:31] Sophia Levins: What you see here is a typical pharma process from planning to production to batch release.
[01:08:38] Sophia Levins: Every batch, every change, every material must be traced, documented, and audit ready.
[01:08:47] Sophia Levins: Already today, the life science industry - where is the life science industry? Anyone?
[01:08:53] Sophia Levins: Already today, the life science industry bets on SAP to manage this highly complex and regulated process.
[01:09:03] Sophia Levins: Now, with industry AI, we take it to a whole new level and deliver end-to-end multi-agent audit ready processes that detect disruption early,
[01:09:15] Sophia Levins: Keeps operations within regulatory limits, and simulates compliant recovery options in real time.
[01:09:23] Sophia Levins: Ultimately, enabling a fully validated market specific batch release as a business outcome.
[01:09:30] Sophia Levins: A great example here is Takeda.
[01:09:35] Sophia Levins: They see outcomes such as an up to 25% reduction of revenue loss due to stock outs,
[01:09:42] Sophia Levins: and an up to 5% reduction in safety stock levels.
[01:09:47] Sophia Levins: Let's take another example.
[01:09:50] Sophia Levins: Revenue growth management.
[01:09:53] Sophia Levins: Kona, the IT group of the largest North American Coca-Cola bottlers,
[01:09:58] Sophia Levins: manages a very complex direct-to-store delivery process.
[01:10:03] Sophia Levins: In today's volatile environment, exceptions during delivery settlement can happen very, very frequently.
[01:10:10] Sophia Levins: The starting point was a fragmented and manual exception handling process.
[01:10:15] Sophia Levins: Now, with industry AI, they can auto-resolve standard exceptions across all routes,
[01:10:21] Sophia Levins: and escalate non-standard cases with clear route causes and recommended actions.
[01:10:28] Sophia Levins: Or, let's take a final example.
[01:10:32] Sophia Levins: Let's take autonomous unified commerce.
[01:10:36] Sophia Levins: Here we are working, for example, with Selling Group,
[01:10:40] Sophia Levins: Denmark's largest retailer.
[01:10:42] Sophia Levins: Introducing new products across categories, suppliers, and channels is complex.
[01:10:48] Sophia Levins: Before, this was a manual and fragmented process.
[01:10:53] Sophia Levins: Now, industry AI helps to orchestrate the entire flow.
[01:10:58] Sophia Levins: Products are automatically classified, promotion decisions are AI-driven,
[01:11:03] Sophia Levins: and supply chain actions are triggered autonomously.
[01:11:07] Sophia Levins: But now, let's hear from one of our customers directly about their industry AI transformation job.
[01:11:17] Sophia Levins: H&M is one of the world's largest fashion brands with over 4,100 stores across 81 markets.
[01:11:30] Sophia Levins: And I am super excited that they are joining us today to talk about how business AI looks like
[01:11:37] Sophia Levins: when it's truly embedded in a company at global scale.
[01:11:41] Sophia Levins: I am thrilled to be joined here today by H&M Group's Chief Digital and Information Officer, Ellen Swanstrom.
[01:11:50] Sophia Levins: Welcome.
[01:12:04] Sophia Levins: Thank you, Sebastian.
[01:12:06] Sophia Levins: It is so good to be here.
[01:12:09] Sophia Levins: And I'm so happy to be talking about our digital and AI journey.
[01:12:13] Sophia Levins: Because we are on a journey to strengthen our position as a fashion brand.
[01:12:18] Sophia Levins: And our customers are at the heart of every decision that we make.
[01:12:23] Sophia Levins: To succeed, we've been focusing on building a strong digital foundation so that tech at H&M becomes a true growth enabler.
[01:12:33] Sophia Levins: Well, Ellen, before we go deeper into that, can you tell us a bit more how your journey looks like so far?
[01:12:40] Sophia Levins: What your transformation journey is at H&M?
[01:12:42] Sophia Levins: Yes, love to.
[01:12:44] Sophia Levins: We're focused on leveraging the latest technologies to enhance both precision in demand and supply.
[01:12:52] Sophia Levins: Gaining real-time access to data across our entire supply chain and financial processes.
[01:12:59] Sophia Levins: To unlock the full potential of new technologies like AI, the right digital foundation is needed to ensure that we can standardize and harmonize key business processes.
[01:13:12] Sophia Levins: And SAP sits at the core of our processes enabled by RISE, Business Data Cloud, Commerce Cloud, and SuccessFactors.
[01:13:22] Sophia Levins: Awesome.
[01:13:23] Sophia Levins: So, with such a robust foundation in place.
[01:13:26] Sophia Levins: Now, what's next?
[01:13:27] Sophia Levins: What changes for H&M and where are you today on your journey?
[01:13:31] Sophia Levins: Well, on top of this foundation, we are layering in AI, using it to improve our operations, reimagine our stores and supply chain, and empower our store colleagues with more precise decision-making.
[01:13:47] Sophia Levins: To make this real, we introduced a new innovation framework designed to help us test, explore, and scale new ideas faster.
[01:13:57] Sophia Levins: Through this way of working, we shaped a clear vision for a more data-driven supply chain that gives us real-time insights into our store operation, which is actually what you're seeing here on the screen.
[01:14:12] Sophia Levins: And we brought SAP with us on that journey.
[01:14:17] Sophia Levins: We feel the collaboration with H&M, between H&M and SAP is truly unique, and it lets us test, explore, and scale digital and AI capabilities.
[01:14:28] Sophia Levins: Of course.
[01:14:29] Sophia Levins: I'm glad to hear that.
[01:14:30] Sophia Levins: So, can you give maybe one specific example of what we are doing together?
[01:14:34] Sophia Levins: Yes.
[01:14:35] Sophia Levins: I'd love to.
[01:14:36] Sophia Levins: One example is our Store Intelligence app.
[01:14:39] Sophia Levins: It is a comprehensive solution for tracking store performance in real-time, and all the way from the sales floor to the market level.
[01:14:51] Sophia Levins: It allows us to understand and steer our business based on live feedback.
[01:14:56] Sophia Levins: And together with SAP, we developed the Store Intelligence Agent that prepares store readiness and suggests next best action for our store managers.
[01:15:07] Sophia Levins: This is what you're seeing, again, on the screen.
[01:15:10] Sophia Levins: And this isn't just a single agent.
[01:15:13] Sophia Levins: This is a system of agents working end-to-end across our value chain.
[01:15:18] Sophia Levins: So, when the store receives a recommendation, it is based on what's happening real-time across different business processes.
[01:15:26] Sophia Levins: For example, a week before a major staging show here in Florida, a new trend starts to gain momentum.
[01:15:34] Sophia Levins: The Store Intelligence app scans market signals local demand.
[01:15:40] Sophia Levins: And based on this, it recommends which key item to feature, in what quantities, and where to place them for maximal impact.
[01:15:49] Sophia Levins: The result will be a store that feels fresh, intentional, and perfectly aligned to what the customers want.
[01:15:57] Sophia Levins: So, this is really an awesome example of business AI in action at scale.
[01:16:03] Sophia Levins: What else are you looking at right now?
[01:16:05] Sophia Levins: Well, another example is a customer-facing solution that we're exploring.
[01:16:10] Sophia Levins: This is featured in the in-store mode in the H&M app, where customer gets a personalized and locally relevant store experience.
[01:16:23] Sophia Levins: Together with SAP, we are developing an AI-powered store concierge agent.
[01:16:31] Sophia Levins: This goes beyond optimizing the store, and it connects the entire customer journey across digital and physical channels.
[01:16:39] Sophia Levins: The store concierge brings the online and in-store experience together in one continuous personalized experience with outfit recommendations,
[01:16:51] Sophia Levins: Real-time availability, and contextual advice.
[01:16:55] Sophia Levins: It's about making every interaction relevant, helpful, human, powered by AI in the background.
[01:17:04] Sophia Levins: Well, in fact, Sebastian, if you were this morning asked the agent what to wear for Sapphire,
[01:17:12] it would actually have had an answer for you.
[01:17:15] Sophia Levins: Well, take a wild guess, I might have had that problem just this morning.
[01:17:19] Sophia Levins: Big keynote, big stage, and I wasn't really sure what to wear.
[01:17:24] Sophia Levins: Well, then let's see what the store concierge would have suggested for you.
[01:17:30] Sophia Levins: So, here, if I wrote, Sebastian is giving the Sapphire keynote in Orlando together with H&M, what should he wear?
[01:17:38] Sophia Levins: Then, see, now the agent will have an answer for you.
[01:17:44] Sophia Levins: See, they know Sebastian very well.
[01:17:57] Sophia Levins: So, and the good thing is that there's also a shop to look option.
[01:18:03] Sophia Levins: No?
[01:18:04] Sophia Levins: So, Ellen, look at my outfit.
[01:18:06] Sophia Levins: The store concierge, I think, did an awesome job, right?
[01:18:09] Sophia Levins: Advising me what to wear.
[01:18:11] Sophia Levins: Actually, my daughter said, Dad, it was perfect, you look like you always look.
[01:18:15] Sophia Levins: Yeah.
[01:18:16] Sophia Levins: I'm very happy with what we put here together, and I'm overall super excited about the journey we are on together.
[01:18:24] Sophia Levins: Me too. I think we're off to a really good start.
[01:18:28] Sophia Levins: Thank you, Ellen.
[01:18:29] Sophia Levins: Thank you, Sabato.
[01:18:30] Sophia Levins: And with that, back to Christian.
[01:18:36] Sophia Levins: What a great use case delivered with our partner H&M.
[01:18:52] Sophia Levins: It shows really well the opportunities we have together in industry AI.
[01:18:57] Sophia Levins: If you have an idea for your company, just call Sebastian.
[01:19:03] Sophia Levins: I mean, it's serious.
[01:19:06] Sophia Levins: Our new AI platform, together with our autonomous suite, give you the ability to transform your company into an autonomous enterprise.
[01:19:15] Sophia Levins: Bring the autonomous enterprise to life will help you to gain resiliency in times of uncertainty, where we sometimes don't know what will happen tomorrow.
[01:19:26] Sophia Levins: But technology alone and blocking AI agents into your existing system landscape will drive zero value.
[01:19:36] Sophia Levins: Moving to the autonomous enterprise requires serious change management.
[01:19:42] Sophia Levins: Adoption of AI goes hand in hand with business process redesign and end user enablement.
[01:19:51] Sophia Levins: To support you in this transformation, today we are launching a new Rise and Grow with SAP offering.
[01:20:00] Sophia Levins: First, our architects, AI developers, and industry consultants, as well as LOB consultants, will come to you on site to drive change management and AI.
[01:20:11] Sophia Levins: An AI adoption.
[01:20:12] Sophia Levins: No matter if you are starting on an S/4HANA or ECC system.
[01:20:17] Sophia Levins: We contractually commit to kickstart your AI journey.
[01:20:22] Sophia Levins: We will activate and drive adoption of three tool assistance of your choice and these associated agents within year one.
[01:20:32] Sophia Levins: And with our max success plan, we commit to set every assistant and agent life.
[01:20:39] Sophia Levins: Second, the modernization of your legacy system landscape is still very important.
[01:20:48] Sophia Levins: Harmonized data foundation and simplified process layer is important for the AI agents to deliver accurate outcomes at scale.
[01:20:58] Sophia Levins: We will support you in this journey with our AI powered ERP migration platform.
[01:21:06] Sophia Levins: You already know tool for developers and tool for consultants.
[01:21:10] Sophia Levins: Thousands of customers are already using these tools and they see up to 30% efficiency gains from these tools.
[01:21:19] Sophia Levins: But now we are taking it to the next level.
[01:21:22] Sophia Levins: We are supercharging our ERP migration tool chain with new tool assistance.
[01:21:28] Sophia Levins: These AI assistants take on the most complex tasks, including data migration, test automation and business process re-engineering.
[01:21:38] Sophia Levins: All in all, we are aiming to reduce migration efforts by up to 50%, making your migration even faster and more cost effective.
[01:21:50] Sophia Levins: Something you will hear more about tomorrow in the customer keynote delivered by Thomas and Jan.
[01:21:57] Sophia Levins: In all of this, our ecosystem will play a key role and today we are excited to announce the partnership with Palantir and Accenture to offer AI migration tools for the most complex migration scenarios.
[01:22:14] Sophia Levins: And with SAP Grow, we are offering our new family members, our new SAP customers, a clear path to the autonomous enterprise.
[01:22:25] Sophia Levins: At no additional cost, we will activate over 20 AI assistants out of the box.
[01:22:32] Sophia Levins: In a nutshell, no matter where you start, we will enable you to start using AI tomorrow.
[01:22:41] Sophia Levins: So, we are already coming to an end.
[01:22:46] Sophia Levins: Let's come back to the question I asked at the start of the keynote.
[01:22:51] Sophia Levins: Will SAP be a software company in the future?
[01:22:56] Sophia Levins: Who better to answer this question than Juul?
[01:22:59] Sophia Levins: SAP is becoming a business AI company.
[01:23:03] Sophia Levins: That's 100% accurate, unlike your unicorn drawing.
[01:23:08] Sophia Levins: Thanks, Juul.
[01:23:10] Sophia Levins: I promise to improve my drawing prompts.
[01:23:13] Sophia Levins: Juul, can you do me a last favor for today?
[01:23:17] Sophia Levins: To close out the keynote, can you give me, in a quick summary, the key takeaways?
[01:23:24] Sophia Levins: Today, we showed how to turn the promise of business AI into reality.
[01:23:30] Sophia Levins: SAP Business AI platform provides the data, process, and governance AI needs to deliver accurate and secure outcomes at scale.
[01:23:38] Sophia Levins: We introduced the autonomous suite, where applications reason, decide, and act for you.
[01:23:43] Sophia Levins: And we showed how we manage change management with RISE.
[01:23:47] Sophia Levins: Together, with customers and partners, we showed how SAP is helping companies realize the vision of the autonomous enterprise.
[01:23:56] Sophia Levins: Yeah, Juul, this is so great.
[01:23:59] Sophia Levins: You can run the full keynote next year.
[01:24:02] Sophia Levins: But in all seriousness, this is the evolution you can expect from SAP.
[01:24:10] Sophia Levins: We have been reinventing businesses for over 50 years.
[01:24:16] Sophia Levins: And now, by infusing SAP's ERP brain into the new business AI platform, we are solving the biggest challenges business facing today.
[01:24:28] Sophia Levins: How to turn AI into true business value.
[01:24:32] Sophia Levins: It's the end of long negotiations, supply chain disruptions, timesheets, financial blind spots, and hopefully the end of being overworked.
[01:24:44] Sophia Levins: It's definitely the beginning of better.
[01:24:48] Sophia Levins: Welcome to the autonomous enterprise.
[01:24:51] Sophia Levins: Thanks for your trust into SAP and welcome to Sapphire 2026.
[01:24:57] Sophia Levins: Thanks for your trust.
[01:24:58] Sophia Levins: Thanks for your trust.
[01:24:59] Sophia Levins: Thanks for your trust.
[01:25:00] Sophia Levins: Thanks for your trust.
[01:25:01] Sophia Levins: Thanks for your trust.
[01:25:02] Sophia Levins: Thanks for your trust.
[01:25:03] Sophia Levins: Thanks for your trust.
[01:25:04] Sophia Levins: Thanks for your trust.
[01:25:05] Sophia Levins: Thanks for your trust.