Oracle Corporation (ORCL) Earnings Call Transcript & Summary

I think we're live. Good morning, everybody. I'm Brad Zelnick, Head of Software Equity Research here at Deutsche Bank. And on behalf of myself and all my colleagues, extremely delighted to welcome you all to the 20th Annual Deutsche Bank TMT Conference here in Sunny Monarch Beach, the Waldorf Storia in Southern California. I got to say that this is an exciting time for tech, extremely dynamic, a lot of things happening, but I feel like event-wise this is something really special that we've carved out. And I know that because I heard from all of you, many of you that were at the welcome event yesterday. I can see over the years, it's now the fourth year that we're here in this location. And I can tell you 4 years ago, I was an exception in bringing my son. And many of you who have seen him and have been here all 4 years, you said, wow, he's kind of like doubled in height. So now I look up to him. But I see more and more families, and this has become a really special event. So I should only hope that -- for the next 2 days, we make it really productive, really fun. And in the next year, if you didn't bring your family or if you're listening on the webcast, you're going to come and join us as well. But -- as I think about technology and I think about paradigm shifts, which seem to occur every decade or so, there's a lot of change going on. And there's very, very few companies that have not only survived, but thrived over the decades. And when I think about Oracle that's been around in a leadership position, nearly the last half century, I couldn't think of a more fitting company to ticket is off. So with that, Welcome, Mike Cecilia, Mike, thank you so much for being here.

Thanks for having us. .

So Mike, for everybody in the room, can you maybe just give us a quick overview. Mike is the CEO of Oracle Corporation along with Klamer, who is your Co-CEO. Can you just give us a sense of where you spend your time most across apps, infrastructure and the broader Oracle portfolio. .

Events like this. And basically running and operating our go-to-market functions, our marketing functions, all the things that we need to do to put our best foot forward with our customers and lake place spends a lot of time on the infrastructure side, particularly the large infrastructure build-out that we have right now. Although it's not that we exclusively split our time that way. clay and I've been working together for a very long period of time here, long before we took these roles. So we collaborate on many things, including investment decisions, operating things like that. So it's a partnership that's been well formed over the years, working together with Larry for quite a long period of time, and it's 11 that works quite well for us. I sort of came up or grew up, I guess, you would say, at Oracle in the applications business and spent a lot of time, a lot of time there, particularly in our mission-critical industries application. But -- it's part of what we do at Oracle. It's not all of what we do.

Very good. Maybe getting right into it, AI. I mean, we I guess we haven't gone 2 or 3 minutes without getting straight into AI because it's so topical. Just at a high level, it's creating both massive opportunity yet at the same time, disruption across the industry. Can you just help us understand your dialogue with CEOs, CIOs, corporate boards, how that dialogue around AI has evolved over the past year? And how having a full stack offering positions you in those conversations today?

Yes. Well, I think what's most interesting, Brad, is that you've said, how has that evolved? That conversation evolved over the last year. I actually think about it and say, how it evolved over the last month. because that's how quickly things continue to change here in the. So if I went through the whole last year, we take up the whole 45 minutes that we have there because every month, it changes. But I'll sort of summarize it is the disruption the disruption side of AI. We said this on probably a couple of earnings calls ago. Perhaps the first industry to be really disrupted by AI is actually our own our own industry. It's the industry that sort of created, if you will, the AI, but the disruption factor, the positive disruption factor that we're seeing is really stunning. I mean I started a long time ago, in those days called a program or eventually change it to a software engineer and things same function. If you would have told me today, you've told me then that the productivity that we could get from a single software engineer was what we're getting and the dramatic output that, that person could have in production grade, I'm talking mission-critical, I'll use the application space here, but it's not exclusive to applications. would be what it is today. I'd say there's just -- that's like Star Wars feature is stuff, there's no way, but it's real. I mean it is super real. It is incredibly interesting. And -- so I think the software industry will probably be a likely disrupted in a positive way. Now what I don't mean to be -- what I don't mean by that is that the SaaS papules fears and all these things are -- I mean that we need software engineers. And so the fact that we're able to disrupt ourselves and become so productive is because we have decades of experience with building delivering mission-critical applications, mission-critical infrastructure like Oracle Database. And we understand the domain, we understand the regulatory constraints. We understand all the things you need to do to be able to deliver that as a turnkey service to customers. And when you have that domain expertise, you can just get a lot more done more quickly with a lot of the tooling. So that's the first piece on disruption. Now come into your question about how our customers thinking about this, what are the conversations like with CEOs of our customers. Well, I think the -- the acceptance is, okay, I mean, yes, there's something to this AI stuff. This is pretty real. How do I get value from it? How do I understand the cost around it and how much of a disruptive factor do I have to put it in my organization? What's the change management? Where is the low-hanging fruit? Where is the midterm return? What should I be thinking about from a longer perspective. So that's become the nature of these conversations. And I think what that leads to is that it really opens up what we largely refer to as the inferencing market, which I think is sort of the next big the next big thing, if you will, in AI is that as we've said, look, the model is stunning, right? Codes, I mean, the ability to create source code, the ability to read and write everything on the Internet and understand, have conversation just stunning technology. Of course, from a contextual standpoint, these models don't know anything about private data, government data and all the enterprises and governments that we serve on a daily basis. The intersection of those 2 things or the union of those 2 things, the application of that is where I think there's just tremendous value unlock as we go forward. What's -- where people have stumbled early on is just not understanding like what a token is, let alone how much it's going to cost them and how do you get value from this? Where we have I think a compelling differentiated conversation with our customers is like I'll just use 1 example. Yes, we're split lots of applications, but our HCM application, right? So our hiring and screening application. How do you hire candidate -- how do you screen candidates, how you hire candidates? Because we have the heuristics and the patterns that we have for 14,000 customers that are live on our Fusion applications today. We can have a conversation with the customer that says, okay, you are today are screening 15 high-value and hiring 15 high-value candidates per month. You'd really like to get given the trajectory of your business, you'd really like to get to 40 or 50 -- how much does that -- how many tokens do you need to consume and how do we package that up into a bundle for you so that you've got predictable cost and you've got an ROI. You've got an ROI case built into that? And how do you price and package that all as a service? And if you're not doing all of it, right, if you're not closely provision to the -- in this case, a large language model that's going to go through the resume posting and reading and all these screening things. If you're not in the infrastructure business, providing the lowest price performance compute on the market. You're not in the applications business, you don't have patterns of 14,000 live ERP customers of all sizes. It's very difficult to get into that predictable ROI discussion. And I think that, that is -- that's become an evolution of the customers that I'm having. I could go on a ton of examples, but that was 8 minutes on 1 question.

It's great context. -- right. And there's a lot of threads to pull on there. And if I think about Mr. Ellison over all those decades, the 1 thing that hasn't changed is price performance has always been a message around Oracle. And if I think about software monetization and pricing models, they've evolved the metrics even within Oracle from power units many go to processors and database to users, to named users. But it had always been across the industry an ROI-based sale. And as we move forward, though, over those decades, it feels like the risk has shifted from the customer onto the vendor as we went from decades ago, big ERP implementations, nearly bankrupting some customers. But here in the AI area, I'd love to explore a little bit more AI monetization and how that maybe changes things. So Oracle today offers a number of options, token bundles, usage-based pricing for agents, agent studio, more recently even outcome-based pricing. Is there any 1 of those that you see becoming more popular or in your view, becomes more prevalent over time?

Well, I think since we offer a really diverse and yet complete stack that all 3 will enjoy popularity as we go forward. From now, I just gave the example of outcomes based for the HCM hiring and screening use case. We've talked about our Fusion agent studio in which customers or partners can create their own AI agents on top of our Fusion platform, not on a custom platform, not on a different platform, but right on top of that platform, that's going to be in a token consumption perspective where customers are going to need to consume tokens to build their own agent. So I think the combination of the 3 things that you mentioned will continue to be popular choices for our customers, given that we're in each 1 of those businesses. We're not in any single piece of that business. But I think the key element is what's the predictability around it. I mean you've seen -- we've all seen -- look, I mean, we had -- I had -- we're leveraging AI internally at Oracle. And I had some salespeople run up some token bills and I said, what -- what are you actually doing with Kodak in a sales function. And actually, it was fairly compelling what they were doing. That said, we had a tamp down the tampon the tokens to a little bit here because you don't want people just running that's kind of been the early summing block is day. You've got a bunch of people out there with their credit card or the equivalent thereof, kind of buying things for a science project. And I think having that governance over top of it and having the ability to sort of marshal all these different consumption models and outcome models, is going to be the key differentiator that enterprise, particularly enterprises and governments as well are looking for. But the monetization is, to your point, right, there's not just a single monetization model here. It's -- there's still some customers that are used or by seed. Outcomes, I think, become increasingly popular as people are looking to get that ROI from and then just a token bundling as well, understanding give me a certain amount of tokens and then tell me when I'm getting close to that. But by the same token, help me measure the ROI for what's been consumed? How do I measure the ROI for what's been consumed for the consumption of those tokens. Well, we can easily do that because we're delivering the platform that is the orchestrator of the token being consumed together with a large language model, we can actually see and demonstrate the ROI .

That makes a lot of sense. Maybe as we think about AI native applications, I think Oracle has had a point of view and emphasize that making AI native to the application work flow rather than taking a bolt-on approach is the way to be and the way to go. Would customers are evaluating Fusion today what role does embedded AI play in accelerating or even expanding a customer commitment? .

Yes. I mean, it's part and press of every conversation we're having with customers today. We like to say that 1 of the quickest ways to get value from AI today is actually is to move to use applications because there's nothing you have to do except to consume some the application, right? It's built into the application. It's not something separate you need to think about. And frankly, you're probably going to put yourself in a -- well, not probably, but I think, going to put yourself in a much better cyber defense perspective rather than taking bolt-ons from third parties and bolting it on to your existing on-prem infrastructure and potentially creating a bunch of Internet-facing stuff that wasn't Internet-facing before accidentally or in some cases, maybe on purpose as a result of the feature. So -- the fact that we built it in is huge. The fact that we also say to customers, hey, you can build your own as well is another big differentiator. And if you think back to like applications business in general. That's 1 of the things that what's 1 of the things that's league you run away, go lives, cost overruns, A lot of it is customizations, right? Customizations and -- it's done 2 things. Number one, they become much more expensive than thought. The go-lives take a lot longer. And the second thing is you've got people that are stranded. There's branded on-prem because there is no SaaS equivalent for what they've built. With the AI agent studio and the AI agent builder provision together with and running on the same database, running on the same infrastructure, running on the same platform services together with Fusion, you really get the best of both worlds. So that you could say here's the package application, right? But he's here is a token bundle. Here's a studio builder. By the way, you don't need to be an engineer or a coder to build these agents. And you can do what you'd like to your heart's content. But here's the good news. You can't go off the rails. We will let you go off the rails. This is an embedded data layer, an API level that we guarantee not to deprecate interface with all the applications, not just Fusion, but vertical applications as well so that you can do both because there is -- look, the industry in general has always said, don't customize. It's a bad idea, right? But there are always some things that you have to sympathize and empathize with customers and that they're pretty specific to their business. it's really hard to sometimes do that to say, I'm not going to have any customization at all. I'm just going to run this as is. And we absolutely still want that to be the North Star. But -- now I think AI really kind of brings that conversation back to the forefront where you've got a configuration, not a customization. And by the way, all of those agents and all that studio, we upgrade, we patch that just like we do our Fusion applications on a quarterly basis. Every quarter, in some cases, monthly passes if there are security things that we're thinking deserve attention, all that's just built in as a service.

Makes sense. Just following that, should we think about the larger opportunity being AI direct monetization or in using a rich AI native feature set to drive greater adoption of applications, expand seats and consolidate more workflows onto Oracle Fusion?

Yes. I think they're both equally important. It's hard to say which is the bigger -- I mean, things are changing so quickly. If we look at this over a 5-year horizon, it's hard to say that which is the bigger market. I'm happy that we're in both markets. I'm happy that we're -- I mean there's -- here's what I think is likely to happen, right? You've got very wide node applications or particularly when you're in heavily regulated industries like banking, utilities, health care like that. It's unlikely to me that there's a bibcoding phenomenon that goes and replaces all of that mission-critical infrastructure that the regulators are going to say, "Sure, right ahead and go run that for the American health care system. -- banking system, stuff like Swift, it's unlikely, I think that's going to happen. . What is likely is that people will want to continue to tailor and continue to make things germane to either their specialty or the subspecialty in the industry. And the fact that you can do both, you assume the light -- the sort of heavy mode stuff as is, you can create something in parallel, I think, is certainly compelling. The other thing I think that's interesting is that if you think about this from a security standpoint, from a business rule standpoint, everything that we're doing in our application stack is all API-driven. So it's not even out of the question that you could consider that the applications really run headless if you will. And the agent becomes the agents -- the customer-generated agents, Oracle generated agents or partner-generated agents become the face to face of those applications. It's also not out of the question. And we see this in -- look at our health care applications some of the recent AI agents that we've released and that the user interface itself almost entirely disappears, right? User interface is really almost gone. And it's voice-activated or it's just -- what would I say user interface, I mean, user interface in the traditional clicking for and things like that.

AI is the new UI.

But I think what's the -- why there's a continued and certainly I think, continued growth opportunity for applications is that all the stuff in the middle that need that it needs to -- the AI interface needs to interact with is it's pretty -- at least the businesses that we're in an Oracle, right? These are pretty complex mission-critical heart of the industry, heart of the business type stuff. So -- or for governments a similar vein. So I think that both of those things. That's why it's hard to say the -- which 1 is the bigger generator. It might come down to how you classify the revenue. But I think the combination of -- if you didn't have both, we wouldn't be as good of a situation going forward. And where the revenue falls on either side of it, is probably less interesting what's more -- the rest thing is that we're generating differentiated outcomes for our customers for a turnkey service.

Very well said. Just as we contemplate this moment elsewhere in the industry, we have seen some moderation in SaaS growth rates, longer deal cycles as customers figure this all out as they face pressure, whether it be in rising component costs taking care of prioritizing their hardware needs or dealing with runaway token spend for the moment. That all said, the last few quarters, Oracle's deferred revenue has continued to grow in excess of in-period revenue growth that you've put up -- can you just unpack that for us? What in your view is driving this divergence? .

Well, I think if you segment the market a little bit and you look at whether there's been slower sales cycles or maybe a couple of quarters of freezing sales cycles, which is now unlocked. It's really more been at the SMB side of this thing. When you look at the kind of the most acute -- on the SaaS side of things, when you look at the sort of the most acute part the most acute peak of the kind of doom and gloom that the SaaS business was gone forever, and never coming back, and it was all going to go into a garage somewhere and be reinvented. That definitely has an impact, particularly probably more outsized on small and midsized businesses than it does on large enterprises, again, particularly those in regulatory environment. So -- and we said that in our last earnings call, you look at our Dambusiness. If you look at our NetSuite business is 1 example that you had some slowdown in sales cycles. But now I think we're -- with our new AI-enabled NetSuite applications, we actually feel good about the fact that AI actually helps the businesses too and actually gets to a faster go lifetime. In the enterprise market, both government and large enterprise market, we did not see a slowdown in our growth. In fact, as our deferred position continues to grow more quickly than our in-quarter revenue, which is a sign of booking strength in the future. We actually saw an acceleration because of the built-in AI to our fusion applications and our industry applications. So actually quite the opposite. I think the kind of next the piece that we've spoken about is that the next unlock on that is the ramp, which is how do you leverage AI with 4 deployed engineers in our services business and actually providing toolkits to our customers to get to live even more quickly because the opportunity is still big. And we've said publicly about half of our installed base has moved from on-prem to cloud in the application ifs. That means there's have to go. -- right, at a 4 to 5 at a 4 to 5x conversion rig. And there's have to go in big media industries like banking, right, and utilities and health care. So there's still -- they tried and true kind of on-prem to cloud business. We're not through that transition. There's still room to go there, it quite a bit of room to go. On the more -- on the CPU side of things, I think the reason we've continued to accelerate is that our cost performance is right? And as you said, there's always been a gold weather for Larry and for Oracle in general. We've always thought about -- we want to be the most efficient provider of technology to our customers. And if you can spend with 1 hyperscaler and you can get twice as much done with Oracle for the same X, I mean you're going to make that choice. So look, it -- I don't have any secret sauce for you except to say it's all about innovation. It's about innovation at every single layer of the stack. And that has been our differentiator at Oracle that we've been in multiple -- we've been in what we think to be all layers of the stack. We continue to innovate every layer of the stack. Just as important to our acceleration is what we're doing in database. I mean what we're doing in database with blockchain tables and encryption keys and vector search and all of those things, that helps our application business be stronger. It's a differentiated situation when you're running that on our OCI infrastructure, rather natively or you're running it in our multicloud infrastructure throughout the world. So that's another piece that we've unlocked. I can go on and on and on. This is fantastic.

I want to maybe touch on another subject, the importance of having an industry focus, which I remember, 20-plus years ago, Oracle had the IBUs the industry business units, and then there was a period where the company made a number of acquisitions to get to the heart of mission-critical business processes in each industry, including Primavera, by the way, which I me where you had come from. I guess before taking on your current role as CEO, you had a prominent role leading Oracle industries. Why is a vertical approach to the market more or less relevant in the age of AI. And how does that inform the ongoing investment you'll make in industry solutions and industry go-to-market? .