How Enterprises Can Be AI Frontrunners

Why do so many enterprises struggle to truly scale AI? And does it have to be this way? 🤔

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At the Six Five Summit: AI Unleashed host Daniel Newman is joined by Brenda Bown, SAP's Chief Marketing Officer for Business AI, who sheds light on the transformative power of AI in the enterprise sector. She reveals some of the reasons behind why many companies fail to scale AI across their business and how they can overcome these challenges.

Key takeaways:

🔹Bridging the AI Hype-to-Reality Gap: Uncover the reasons behind the discrepancy between AI's enterprise hype and its actual scaled deployment, gaining insights into why many companies haven't yet realized its full potential.

🔹Strategies for Scaled AI Success: Learn actionable strategies for enterprises to transition from isolated AI experiments to robust, scaled solutions that deliver significant and measurable business results.

🔹The Power of Enterprise Context with AI: Understand the critical importance of embedding AI with full enterprise context, enabling data to be leveraged more effectively, where truly intelligent applications can emerge.

🔹SAP Business AI & Joule Agents: Get an introduction to SAP's innovative Joule Agents and their role in making AI ubiquitous across applications, along with how SAP Business AI is empowering frontrunners to scale AI effectively.

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Learn more at SAP.

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Watch the full video at Six Five Media, and be sure to subscribe to our YouTube channel, so you never miss an episode.

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Or listen to the audio here:

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Daniel Newman: Hey everyone. Welcome to the Six Five Summit AI Unleashed, Daniel Newman here. We are in beautiful Bellevue, Washington. I'm very excited for this next guest. I have Brenda Bown. Brenda SAP's, CMO of their enterprise AI business. Overall, I couldn't be more excited to sit down with you. It's been a few years since I've actually had the chance to do a video with you, but what a big moment. First of all, welcome to the Summit.

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Brenda Bown: Thank you, Dan. It's great to have you here in Seattle. Thank you for visiting us. And it's sunny. You brought the sun with you.

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Daniel Newman: It is great. Now, I think that's a bit of a misnomer, by the way, sometimes. I know Seattle does have many cloudy days, but it's not always cloudy all the time, right? You've been here for a few years.

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Brenda Bown: Yes, over 20 years here in Seattle. Yes. That's where we met.

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Daniel Newman: You refuse to leave? No, it's really, really great here. But it is good to be here and I did bring the great weather with me and you are going to bring the insights for our audience. We are very excited. As you know, we've entered this amazingly fast moving era and here you are at SAP one of the world's most influential companies when it comes to enterprise business data and enterprise applications that run companies critical mission, critical businesses day in and day out. First and foremost, let's just start talking a little bit about, we are in this era of rapid change. Rapid shift. You are helping companies drive towards this, but what are you seeing out there as it pertains to what is going on with enterprises and moving their AI strategies forward?

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Brenda Bown: Well, first of all, then I think you're right. I mean, everybody wants to do AI because it's there, it's available, but I think that the major shift that I'm seeing is we're moving from the hype of AI to really using AI and it becoming real. So we talk about moving from last year being a proof of concept year to now actually deriving value from ai. So that's what I'm seeing mostly with our customers. One of the reasons that I was thrilled to join SAP is because exactly what you said, we run the most mission critical business processes in companies and we take that responsibility very seriously. We have a breadth of applications from HR to supply chain to customer experience. So back to your question, we see a lot of different journeys from different customers in multiple industries, but what is common across all of them is really deriving that value and making it real for customers, which looks different in every customer, right?

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Daniel Newman: So I love that you pointed out the hype, and I never want to necessarily call because I am a buyer when it comes to ai. I'm a believer, I think all that I jokingly call the AI bubble bearers. All the people that think that AI is going to collapse and not happen now, I think the timeline's very interesting. And so enterprise ai, Brenda versus sort of the consumer experiences, the chat GPTs and all the things that we're seeing in our apps has moved at a little bit of a different pace, but it's not hype. It's very, very real. But your customers, the ones that you talk to every day, they are sort of trying to navigate the journey. It sounds like they are trying to go from POC to bringing this to reality. What are some of the things that the customers, let's start off with, what are some of the things that customers are learning early on in this journey that are sort of maybe helping them get through? Because it hasn't happened necessarily as fast, but it feels like it's going to start to accelerate really quickly.

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Brenda Bown: Yes, it is accelerating, and some of the realities that we see today is the fragmentation of the landscape. I mean, the reality that customers live is they use different tools, they use different systems. That's why getting your data in order is so important. And at SAP, we launched earlier this year, business data code, which helps you do that, right? SAP and non SAP data, bringing it together. We have a great partnership with Databricks that we launched earlier in the year. So that's one aspect that heterogeneous landscape that customers are dealing with. The other thing that I see a mindset shift, right? Customers I think are moving from the traditional way of doing things into experimenting with AI. And that's to your point, that's different in enterprise because your tolerance for risk is much lower, that when you use AI for any consumer things here, you got mission critical processes.

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So we see customers thinking about particular use cases because they got to start somewhere. So we talk about 400 use cases that we have in SAP that we're helping customers find value out of those use cases in the applications that they're already using because they're making it real. So we want to make sure they're very mindful of where they can apply that AI that is very tangible and that they can derive value from it. And the other risk is that I see is in reality is that sometimes customers don't think that they're moving fast enough. And one of the things that we reinforce is that we're going to move with them at the pace that they need because different customers are in different parts of the journey. Some are some in the cloud, and we're going to go through that journey with them, but at the same time, AI moves very fast, so we want to make sure that they have the latest and greatest so they can derive value from that investment that they're making.

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Daniel Newman: Now, that's a pretty big challenge for these companies. It feels like they have lots of options being thrown at them. You mentioned the partnership, the business data cloud,

Having such a vast data landscape, SAP of course works with companies of all different sizes, but bread and butter, you work with the world's largest enterprise customers. I mean, that's a lot of the heritage of the company. These companies have built data estates, I'll call them, that have thousands of business applications, different database tools, operational and transactional and analytical databases. And then of course they have different apps that have data, and then they have segmented and fragmented data that sits on people's laptops and on their Excel spreadsheets, all this stuff. How much are you seeing, how difficult is it to bring all that and create that kind of enterprise context for these businesses so that they can actually get access? I hear what you're saying. You have a lot of the, a large majority of the most important enterprise mission critical data sits an app, an environment like SAP. Having said that, all the other data contextually becomes super important.

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Brenda Bown: Yes, yes, exactly. And we talked about business data cloud. So we launched Business Data Cloud earlier this year. We have an amazing partnership with Databricks, and that helps you bring together all the SAP and non SAP data. We also are creating that flywheel that we talk about earlier in Sapphire too. We have our applications, which is an amazing breadth and depth of applications, like I said, from customer experience, supply chain finance, business operations. And then we also have data with business data cloud that brings in all that data estate and that heterogeneous landscape that customers are dealing with. And we also form great partnerships like with perplexity specifically for AI, with launched a partnership in which it's not only the business data, but it's also contextual data. So when you are actually using AI in your systems, it also derives that data from perplexity and it suggests actions because it's not only about reasoning with ai, but it's also about acting and we're implementing that.

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And then you have AI on top of that. So we have the applications, we have the data layer, which was business data cloud, and then we have ai. And the way that we have AI is we have it embedded in our applications, but we also have it with JUUL and with JUUL agents, which we can talk more about. But all of that is really integrated into the system, and that helps you not only bring all the data state together that we talk about, but it also helps you integrate with any other data that you have in any other system. But it integrates with your most mission critical data, which we know that lives in SAP, but we want to make sure that that is all together and an interoperable.

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Daniel Newman: And you and I have had a few conversations over time about how SAP is making AI sort of pervasive, and I think this is probably worth noting here. I'm going to get into JUUL here because I have been tracking the journey very closely, and I think the ag agentic opportunity has clearly arrived. We spent two years talking about ai, then we talked about generative ai we have, but some of this is basically AI needs to move with you, meaning as alternatively, otherwise, we're really back in the era of if you have to push a button that says do something, we're still kind of in what I would call the historic software era of you go in and interact with your systems, AI should be designed. And I think you made the acquisition at WalkMe. I think part of that was kind of about making AI sort of pervasive. Talk a little bit about how SAP's thinking about making AI more contextually aware and more pervasive to drive user and productivity growth and efficiencies that people maybe don't know how to get out of ai.

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Brenda Bown: And I get really excited because that omnipresence of ai, it really moves us into the era of AI. We talked earlier about customers that are using and making AI real and SAP. We have 34,000, over 34,000 of our customers that are using some form of generative AI already in their system. So we know that they're being used. Those use cases that we talk about, we're going to get to 400 use cases by the end of the year across all of our applications. They're real. Now, what we want to make sure is that the barrier to entry for the usage of AI and for the adoption of AI for our customers is really low. And one of the ways that we do that is with that omni process across all the applications, across any system that you work in. And that's what we're doing with Juul.

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So if we think about JUUL as the new user interface for AI, it gives you access in a very natural way with natural language for you to be able to ask Juul any question. And then all those agents or those billions of agents were in the background to process the answer. Now with the acquisition of WalkMe, what we did that is really cool is that we launched something called the dual action bar. So that dual action bar literally travels with you, it travels with you. It doesn't matter if you're in another system, if you're interacting in ServiceNow, for example, that dual action bar is there and it doesn't wait for you to prompt the action bar and ask a question. What it does is that it's looking at all the behavioral data, looking at all the actions that you're taking, and it's prompting suggestions based on what you're doing already with your system. So we talk about that dual action bar enabling to you to be everywhere and to manage everything, and it's truly what it's doing. And then in the background, you have all of the agents working for you, which is the agent AI component that we talk about.

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Daniel Newman: And WalkMe had a very significant evolution since the acquisition by SAP originally, it was sort of trying to help people use the technology it's invested in, which it still is, but it was before trying to use say, a SaaS or an application. Now it's basically an enabler of helping people use consume and proactively implement AI across your entire business journey, which is fascinating because I do think adoption is a gap, and there's a reason that many of us became successful in taking something like a chat GPT tool and using because it's like, Hey, this is kind of search. I know how to do this. I've been doing this a long time. I asked the question and now I give more context and kind of an answer, and it can do it differently. I don't just get a link. But for enterprise, a lot of the challenge has always been about adoption. People have always kind of said, I don't know that I feel I'm getting the value of all these apps that I'm investing in. AI really does seem like a great opportunity to tear that wall down and make this everything more usable. 

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But one thing that I do think that enterprises are challenged with, and I'd love to get your take on this Brenda is they're challenged by right now everyone's bringing AI at them. You have been a consumer of products as a CMO for a long time, meaning that people sell you stuff, businesses, people probably try to sell you a software to run things, right? Long story short is as you're sort of buying this stuff, you're trying to figure out how to optimize it and how to utilize it. In Agent World, it's like, oh, I want to sell you an HR agent. I want to sell you a CRM agent. I want to sell you an ERP agent. I want to sell you a supply chain optimization tool, an agent, oh, I want you to run you an agent in your productivity suite. I know that in your Sapphire keynote in the Sapphire keynote, there was a great sort of flywheel narrative about why start and build with SAP. I'd love to get your As agents will consolidate. I don't think you're going to buy an agent from every software app that you have. How is SAP sort of driving a narrative and helping the market understand why maybe SAP is the right place to start build and orchestrate a lot of their agentic solutions?

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Brenda Bown: And we talked about it at Sapphire, like you mentioned, but one of the things that when we think about agentic AI and about agents, I always first start with what do we consider an agent? So many definitions of AI agents, Albertan that people sometimes get confused and you talk about billions of agents, so people sometimes get a little bit, it's daunting, right? To think about, oh, do I need to use billions of agents? And if I'm not using all of them, then I'm behind. And the reality is that SAP, what we consider an AI agent is an agent that can help solve a complex business process and why a complex business process? Because we can do that right with all the data and state that we have with all the breadth and depth of applications that we have. And we know that there's going to be smaller tasks that are going to be done in the background like sending an email, some vendors out there called that task an agent.

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So we don't do that. We call an AI agent that we ship out of the box like an agent that solves a complex business task that sometimes presents all of those business processes. Sometimes it goes beyond the finance function and it speaks to a supply chain agent and it speaks to a customer service agent. And then that is the agent that we ship out of the box. We know that customers are dealing with that complex business process. So we have over 40 agents that we have out the door that we talked about Sapphire, and I can give you an example. We have an agent that Standard Charter Bank is using specifically for goal setting in hr. So what they do is they rolled out that agent to 84,000 of their employees globally. So that's truly at scale. And that agent is helping the employees build goals specifically based on their performance, based on their business goals, based on the conversations that they've had with their managers.

It helps them build goals that they can then enter into the system. All that is automatically done. So before what it used to take two hours for an employee to do, and now it's taking them 10 minutes. So it is dramatically improving the productivity of that person within a business process. 

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We also have out of the box like a customer experience agent, right? Bosch Power Tools is using the customer experience agent is not only replying to emails, it's actually reasoning all the inquiries that are coming in is redirecting some of those increase, but it's also drafting responses already and triggering other actions. So it's the act of reasoning and then acting right, and then triggering another action that is going to always have an oversight from a human right, but it's already doing that action for you. In addition to that, we have the capacity to build your own agent. So those are agents that we ship out of the box, but then we have the ability for you to build your own agent with Juull Studio. And that is we have customers like Cirque de Sole that we have had great partnership over the years with they are building their own agent to be able to manage accounts payable across all of their shows. So each show that Cirque de Sole has is specifically a P&L, and they create an agent for them to deal with accounts payable for each one of those shows. And the agent deals with all the translation across because those shows travel across the world, deals with all the translation of languages, deals with the action of paying to the suppliers, et cetera. So that's the variety of the agents and the agent AI system that we're building for customers to use.

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 And in addition to that, like you said, there's so many vendors throwing AI agents out there that we want to make sure not only that you have a strong foundation to use out of the box agents with your SAP system, build your own agents that we know that you're going to have to use because you have unique business processes that you're running, but also the ability for you to work with other agents. So we have joint interoperability protocol of agent to agent collaboration with Google and with Microsoft. And we're also building very strong integrations with, for example, Microsoft Copilot, that they have a strong productivity angle of course, because you can use, we know that our customers are using copilot in productivity with the office suite with teams. So that integration that we're building with juul, you can use JuuL within Microsoft copilot or you can use copilot within Juul. So you don't have to do that kind of toggling between your system depending on where you are. You can actually get all that goodness from copilot as well if you're in your SAP system. So we're very mindful of all that heterogeneous landscape that is out there, and we want to make sure that we can integrate with that. But at the same time, we know that the core of mission critical business process is it's run in SAP. So we want to make sure that we have that very well established for our customers.

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Daniel Newman: First of all, really appreciate you bringing some of these customer examples because so often, I think right now it starts with the hype and making it real. We sort of hear that, oh, they're doing it and they like, oh, it's a POC and it's being done in some very small vacuum in a very small number of times. Part of the reason we're building out this massive AI infrastructure is because when this gets done at scale. When you have companies like the ones that you mentioned, large banks and large manufacturers that have many of these agents all working, by the way, 24 7, they can work all day. You will have trillions, these tokens everyone talks about. But I like that you brought those examples. I also like though that you sort of explained agent because I do think there's kind of, well, what is a generative AI tool? What is a bot? What is an agent? Because I think some people are kind of conflating a bot, which have been around a long time answering an FAQ. It kind of could maybe be in somewhat of an agent sometimes. 

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But what you're saying about a complex business process, in my mind, it's all about when it can kind of orchestrate and coordinate. Meaning if it's just going back to a knowledge graph and saying, oh, we're open nine to 6:00 PM that's a bot. But when it can actually say it's open, give you express directions, maybe coordinate a meeting for you when all those things can happen, now we are actually experiencing what is ag agentic. And so you mentioned Juul Studio, and I just want to ask this question because right now I think a lot of businesses are going to probably go with a lot of off the shelf, even some of the examples. These are huge companies that are taking what you've built off the shelf, but how hard, from what you're hearing from your customers, is it for them? Because every company has a few custom processes and SAP knows this, it's built on these massive custom deployments, which you've moved away a little bit from as you've gone to cloud and ai, but you're trying to deliver more out of the box. But when a customer does need to go custom JuuL studio, are they finding it something they can really work with?

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Brenda Bown: Yes. I think that the beauty of Juul Studio is that you can define the skills that you wanted to use. You can also define the models that you want to build from. You can also define the other agents that you want that agent to work with. And not only you can build your own agent, but you can also customize. So what we ship out of the box, you can take it and say, Hey, I want to tweak a few things here. And you have all those variables there, and then you can create the own agent. I think that because of the custom business process, but also because the complexity of our customers sometimes globally, I mean we talked about Cirque de Sole, it's like mind blowing. It's like the amount of shows that they have and the amount of countries and the scale that they go with. So they have is the same function of the agent, but they have to do it in different context, right? Because they have different suppliers and deploying it is super seamless. They said we build it once and then we deploy it for each one of the shows, and it's beautiful. It adopts the same language that the same language of the show. It recognizes the suppliers that we're using. And sometimes those suppliers are big ones, sometimes are mom and pop shops that are in the city and they're like, it's super seamless. So that speaks to the scalability, the adaptability of those custom agents depending on the process that you want to build. But they based it off something that we had already talked with them about and that we had already built. So it's that beauty of you can extend, you can customize, but it's depending on what you need. And it's a really neat way of doing it if you go into Juul studio, the really neat way of doing it because it outlines all the variables that you can do.

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Daniel Newman: Yeah, it seems like there's going to be a really significant opportunity for companies like SAP to have the data and insights of so many enterprises and that mission critical data to be able to build a lot of out of the box. I think that's going to be part of this whole going fast and scaling. But we just know history has proven that there's infinitely more variables and options that different companies could end up having. So being able to build is going to be really important as well. So as we sort of pull this all together, we started the conversation talking about bringing enterprise AI to life, that taking away the hype, making it all work SAP, in order to build a future where it's going to continue to be as successful and growing and grow at the rate it has and even faster. You have to be the enabler. All these companies are going to have to evolve and they're going to have to evolve with you. Just kind of in a more simple sort of contextual way, how do you think SAP is going to be most influential in driving and helping companies be successful in the era of enterprise AI?

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Brenda Bown: I think that there's a few ways that we're doing it right now with our customers. We talked about, depending on where customers are in the journey, and I think that that's very important. We talked about tens of thousands of our customers using AI that is going to just accelerate, right? I mean once they start using, once they start finding those use cases, it's going to accelerate even more. AI goes very fast, like you said, Daniel. So we are shipping innovation on a monthly basis. So I think being with those customers on their journey and helping them make it real and deriving value from it, that is very critical and that is how we're going to continue to evolve into this era of enterprise AI. The other thing is with we're making a seamless experience. We talk about low barrier to entry. I mean, these are mission critical processes, so risk aversion is common and we want to make sure that we lower that barrier to entry. So really establishing a strong AI foundation, which we have with our AI foundation, which we talked about Sapphire, that it gives you the reliability, the security, making sure that your data is state that we have built with business data cloud is secure, is reliable and is trusted, and having that foundation with our customers, it's going to be really important because that's from where they build. 

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The other thing that I would say is we continue to build very, very strong partnerships in the ecosystem. I mean, we talked about partnerships that we built with other vendors like Microsoft and Google, et cetera. We also build partnerships with pure AI companies. With Mistral, for example, we started building a finance agent specifically that we can ship out of the box. We build a partnership with Nut Diamond, we build a prompt optimizer. And when you hear the expression like prompt engineering is instead, because we know the developers are spending so much time building this prompts and with this prompt optimizer with not Diamond, really the developer is going to outline the outcome that they want to have and all that optimization is going to be done in the background. So those are just two examples of AI companies that we partner with. And we are going to build the future of enterprise AI with those partnerships as well. But we know that all the gravitas of your mission critical data, your mission critical process starts with SAP, and we want to make sure that you continue to feel confident and that the trust that we have built with our customers continues as we build the future with them.

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Daniel Newman: And of course, you mentioned Perplexity as well, another quickly rising ai, pure AI play that is now part of the SAP ecosystem. It's always been part of the S-A-P-D-N-A to have partnerships. So that's not surprising at all to me. I'm also really glad that you did mention trust and security. We didn't talk about it a lot, but I think part of the reason enterprise has also gone a little bit slower is because there is a meticulousness that's required to make sure that enterprise data stays in the right place. And you'll be in a company with European descent too. Sovereign is going to be another big opportunity to expect SAP to be able to capitalize on as well. Alright, so final just where can the audience go and learn a little bit more about what you're doing in enterprise AI?

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Brenda Bown: We just had Sapphire done. So it's our biggest customer event. It's our flagship event. We had it just in May in Orlando, and then in Madrid. We have many more announcements coming. So definitely stay tuned. We have Veeva Tech coming up. We have SAP Connect coming up in October as well, but I think customers can go and watch our Sapphire keynote. It was a very, very popular keynote. We have a lot of announcements there, our innovation guide as well. But if you watch the keynote, you'll hear all the momentum that we're building, all the things that we have available today, which is we're making it real with customers. And then obviously we're going to continue to deliver the rest of the year.

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Daniel Newman: Brenda, so great to sit down with you.

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Brenda Bown: Great to see you, Dan. Thank you. 

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Daniel Newman: Thank you everybody for being here with us at the Six Five Summit AI Unleashed. That was a great conversation with SAP. I'm going to kick it back to the studio, more from us soon.

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