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 Technology Conference here in sunny Monarch Beach, the Waldorf Astoria, 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. 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 four years ago, I was an exception in bringing my son. Many of you who have seen him and have been here all four years, you said, "Wow, he's kind of doubled in height," so now I look up to him. I see more and more families, and this has become a really special event. I should only hope that for the next two days, we make it really productive, really fun. 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. 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. There's very few companies that have not only survived but thrived over the decades. 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 kick us off. With that, welcome, Mike Sicilia. Mike, thank you so much for being here. Thanks for having me. 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 Clay Magouyrk, 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? Restaurants, 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. Clay 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 have 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 the company, and 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 one 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 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 guess we haven't gone two or three 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 to 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? Yeah. Well, I think what's most interesting, Brad, is that you've said, how has that conversation evolved over the last year? I actually think about it, say, how has it evolved over the last month? Wow. Because that's how quickly things continue to change here in the AI piece. If I went through the whole last year, we'd take up the whole 45 minutes that we have here because every month it changes, but I'll sort of summarize it in the disruption side of AI. We said this on probably a couple earnings calls ago. Perhaps the first industry to be really disrupted by AI is 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 started a long time ago as, in those days, called a programmer. It eventually changed into software engineer and things, but same function. If you would'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, "That's like 'Star Wars,' futuristic stuff. There's no way." But it's real. It is super real. It is incredibly interesting, and so I think the software industry will probably be likely disrupted in a positive way. Now, what I don't mean by that, I want to be clear, what I don't mean by that is that the SaaSpocalypse fears and all these things are that we no longer need software engineers and so on. 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. 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. 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 our customers thinking about this. What are the conversations like with CEOs of our customers? Where I think the acceptance is okay. 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? How much of a disruptive factor do I have to put into my organization? What is the change management? Where is the low-hanging fruit? Where is the mid-term return? What should I be thinking about from a longer perspective? That has become the nature of these conversations. 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 the next big thing, if you will, in AI, is that, as we have said. Look, the model is stunning, right? Codex, I mean, the ability to create source code, the ability to read and write everything on the internet, understand, have conversation, just stunning technology. Of course, from a contextual standpoint, these models do not know anything about private data, government data, and all the enterprises and governments that we serve on a daily basis. The intersection of those two things, or the union of those two things, the application of that is where I think there is just a tremendous value unlock as we go forward. Where people have stumbled early on is just not understanding what a token is, let alone how much it is 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 will just use one example. We are, despite lots of applications, but our HCM application. So our hiring and screening application. How do you screen candidates? How do you hire candidates? Because we have the heuristics and the patterns that we have for 14,000 customers that are live on our Fusion application today. We can have a conversation with a customer that says, "Okay, you today are screening and hiring 15 high-value candidates per month. Given the trajectory of your business, you would really like to get to 40 or 50." How many tokens do you need to consume, and how do we package that up into a bundle for you so that you have got predictable cost and you have got an ROI? You have got an ROI case built into that. How do you price and package that all as a service? If you are not doing all of it. If you are not closely provisioned to the, in this case, the large language model that is going to go through the resume posting, the reading, and all of these screening things. If you are not in the infrastructure business of providing the lowest price performance compute on the market, you are not in the applications business, and you do not have patterns of 14,000 live ERP customers of all sizes. It is very difficult to get into that predictable ROI discussion. I think that that has become an evolution of the customers that I am having. I could go on and on and on with a ton of other examples. No. But that was eight minutes on one question, so I'm going to stop. No, it's great context, Mike. Yeah. There's a lot of threads to pull on there, and if I think about Mr. Ellison over all those decades, the one thing that hasn't changed is price performance has always been a message around Oracle. If I think about software monetization and pricing models, they've evolved the metrics even within Oracle, from power units many years ago- Sure to processors and database to users, to named users. It had always been across the industry an ROI-based sale. Yeah. 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. Here in the AI area, I would love to explore a little bit more AI monetization and how that maybe changes things. 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 one 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 three will enjoy popularity as we go forward. I just gave the example of outcomes-based for the HCM hiring and screening use case. We have talked about our Fusion AI 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 is going to be in the token consumption perspective, where customers are going to need to consume tokens to build their own agent. So I think the combination of the three things that you mentioned will continue to be popular choices for our customers, given that we are in each one of those businesses. We are not in any single piece of that business. I think the key element is, what is the predictability around it? We are 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 Codex in a sales function?" Actually, it was fairly compelling what they were doing. That said, we had to tamp down the token throttling a little bit here because you do not want people just running away. That is kind of been the early stumbling block, is that you have got a bunch of people out there with their credit card or the equivalent thereof, kind of buying things for a science project. I think having that governance over top of it. Having the ability to 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, I think to your point, there's not just a single monetization model here. There's still some customers that are user-by-seat. Outcomes, I think, become increasingly popular as people are looking to get that ROI from AI. Then just token bundling as well, understanding that give me a certain amount of tokens, then tell me when I'm getting close to that. 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 the 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 emphasized that making AI native to the application and workflow rather than taking a bolt-on approach is the way to be and the way to go. When customers are evaluating Fusion today, what role does embedded AI play in accelerating or even expanding a customer commitment? Yeah. It's part and parcel of every conversation we're having with customers today. We like to say that one of the quickest ways to get value from AI today is actually to move to the Fusion applications because there's nothing you have to do except to consume the application, right? It's built into the application. It's not something separate you need to think about. Frankly, you're probably going to put yourself in a, 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 onto 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. 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. If you think back to applications business in general, what's one of the things that's plagued your runaway go-lives, cost overruns? A lot of it is customizations, right? Sure. Customizations and it's done two things. Number one, they become much more expensive than thought. The go-lives take a lot longer. The second thing is you've got people that are stranded. They're stranded on-prem because there is no SaaS equivalent for what they've built. With the Oracle AI Agent Studio and the Agentic App Builder provisioned 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 can say, "Here's the package application," right? "But 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. 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 won't let you go off the rails. This is at the metadata layer, at 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 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 customizations at all. I'm just going to run this as is." 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. 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 you get. In some cases, monthly patches 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 direct AI 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? Yeah. I think they're both equally important. It's hard to say which is the bigger. Things are changing so quickly. If we look at this over a five-year horizon, it's hard to say which is the bigger market. I'm happy that we're in both markets. I'm happy that we're. Here's what I think is likely to happen, right? You've got very wide moat applications, particularly when you're in heavily regulated industries like banking, utilities, healthcare, things like that. It's unlikely to me that there's a vibe coding phenomenon that goes and replaces all of that mission-critical infrastructure that the regulators are going to say, "Sure. Go right ahead and go run after the American healthcare system, the banking system," stuff like Swift. It's unlikely, I think, that 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 their subspecialty of the industry. The fact that you can do both, you can consume the wide, the sort of heavy moat 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 of those applications. It's also not out of the question, and we see this in our healthcare applications as 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. When I say user interface, I mean user interface in the traditional clicking for- Sure things like that. AI is the new UI. Yeah, right. AI is the new UI. I think why there is a continued, and certainly even I think continued growth opportunity for applications is that all the stuff in the middle that the AI interface needs to interact with is, at least the businesses that we are in Oracle, right? These are pretty complex mission-critical, heart of the industry, heart of the business type stuff. Or for governments, a similar vein. I think that both of those things. That is why it is hard to say which one is the bigger generator. It might come down to how you classify the revenue. Sure. I think the combination of both. If you did not have both, we would not be in as good of a situation going forward, right? Where the revenue falls on either side of it is probably less interesting. What is more interesting is that we are generating differentiated outcomes for our customers from a turnkey service. Well said. 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. Yeah as they face pressure, whether it be in rising component costs and taking care of prioritizing their hardware needs or dealing with runaway token spend for the moment. Yeah. 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 where there's been slower sales cycles or even maybe a couple quarters of freezing sales cycles, which is now unlocked, it's really more been at the SMB side of this thing. On the SaaS side of things, when you looked at the most acute part, the most acute peak of the kind of the 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 to midsize businesses than it does on large enterprises, again, particularly those in regulatory environments. We said that on our last earnings call. If you look at our NetSuite business as one example of that, Sure you had some slowdown in sales cycles. But now I think with our new AI-enabled NetSuite applications, we actually feel good about the fact that AI actually helps those businesses too and actually gets to a faster go-live time. 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. Actually, quite the opposite. I think 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 forward-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 install base has moved from on-prem to cloud in the application infrastructure. That means there's half to go, right, at a 4x to 5x conversion rate. And there's half to go in big meaty industries like banking, right, and utilities and healthcare. So there's still the tried and true kind of on-prem to cloud business. We're not through that transition. There's still room to go there, quite a bit of room to go. On the CPU side of things, I think the reason we've continued to accelerate is that our cost performance is superior, right? As you said, that's always been a bellwether 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. If you can spend X with one hyperscaler, and you can get twice as much done with Oracle for the same X, I mean, you're- Paying half the price. You're going to make that choice. So, look, I don't have any secret sauce for you except to say it's all about innovation. It's about innovation in every single layer of the stack. That has been our differentiator at Oracle, that we've been in what we think to be all layers of the stack. We continue to innovate in 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 where you're running that on our OCI infrastructure, whether natively or you're running it in our multi-cloud infrastructure throughout the world. So that's another piece that we've unlocked. I could go on and on. Yeah. This is fantastic. Yeah. I want to maybe touch on another subject, the importance of having an industry focus, which if I remember, 20 + years ago, Oracle had the IBUs, the industry business units. Yep. There was a period where the company made a number of acquisitions Yep to get to the heart of mission-critical business processes in each industry, including Primavera, by the way. Oh, sure. which I remember very well. Yep. 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? How does that inform the ongoing investment you will make in industry solutions and industry go to market? Well, I think it is absolutely more important than it has ever been for us for the simple reason that outcomes matter, right? Outcomes matter, and outcomes are going to matter to the business. With our industry approach, we have always been in a situation where we sold to both the IT function of a business, but also to the business itself because we are in the heart of what the business does. We are providing the core banking systems. We are providing the merchandising supply chain management systems. We are supplying the meter data management and grid sharing systems for utilities, the property management systems, reservation systems for hotels. These are all businesses that we have been in. You don't see the Oracle logo on them because they're private labeled by the business itself, but we are the guts of what matters in healthcare, electronic health, which we all have been publicized very well. Largest custodian of electronic healthcare records on the planet. Now, when you want to talk about how do you get value from AI, it's both an IT conversation, of course, but also increasingly a business conversation, and it's one that CEOs are increasingly involved in our customer situations. We've always been selling to the CEO in that industry perspective, and we've been able to recruit people in. People matter here in a big way, Brad. We've been able to recruit people in who are domain experts now in these, both for acquisition, but also organically. If I look at the people that are running our industries today, these are people that we've recruited in from the industry. Unlike me, most of them didn't come from an acquisition, but they actually like the center of gravity that we have in the industry, and they were recruited into Oracle, as a result. It's always been a competitive differentiator for us. Probably more important than ever. In terms of our go-to-market function, we reorganized our sales team to be completely industry-focused across the globe. That's even true in our infrastructure business as well. Even in our infrastructure business, we have people that call on the same industry because it's unlikely that in our IaaS business, unlikely that's the only thing we're selling to our customer is infrastructure. We're also selling database. We're selling ERP. We're selling some operating technology as well. We've actually gone through a major restructuring of our go-to-market function so that we have two things. We have complete industry alignment, and number two, we have less sellers calling higher on our customers and speaking more at the executive level. Because we need less sellers per customer, it's allowed us to expand our reach and pick up some uncovered territory today that was previously uncovered. Helpful. Mike, you already touched on the advantage of having the full stack, and I think you've said in the past, customers increasingly think about the applications and database layers together rather than as separate decisions. For those less familiar in the room, can you just remind us what differentiates Oracle AI Database and how the layers come together to create additional value? Yep for customers? So just in general, the Oracle AI Database is probably a quite popular custodian of the world's mission-critical data and has been incredibly sticky in that regard. That mission-critical data is the key for inferencing, the key for retrieval augmented generation. I'll say contextual AI, contextual applied AI. So we built into the database things like vector search, where we are automatically vectorizing all of that data for customers as a service, just as an upgrade that's built into the database. Just one example of innovation. The other piece is that we're doing that on top of our blockchain tables as well, which for certain vertical industries is incredibly— Having something that's completely immutable is incredibly important for certain vertical industries. Then you put on top of it the way that we encrypt data. So I'll use our healthcare example, our healthcare database, for example. Well, let me put it a different way. How did the healthcare business make our database features stronger? Because we are the largest custodian of electronic health records on the planet, we have to think about encryption keys. We have to think about what's called longitudinal records, which means your entire patient record. So the way the database works for healthcare is that we have an encryption key per patient. So most databases on the market today are encrypted at rest, encrypted in transit. We actually have an encryption key for patients. So if you were to steal the database, you'd have to steal however many patients' worth of encryption keys or decode however many patients' worth of encryption keys you also had in the database at the same time. Now, how do you do all that and also not impact performance? Because encryption is one of the things that can make databases operate more slowly. Well, that's just decades and decades of innovation that we've put into the Oracle Database. Then you put all that together and say, "How do I make it highly secure?" How do I make it immutable for our mission-critical and government and enterprises? And how do I make it applicable for AI? So again, it's not any one of those features that gives us an advantage. It's the fact that we can do all of them as a service. It's just a service that you built in. You don't have to go buy a third-party application or a third-party pack or have somebody come in and custom-build this. It's a service that's built into the Oracle Database. The reason that I think we're able to get to that level of innovation is, again, because we're in the entirety of the business. Our testing cycles start in healthcare, for example, in a patient exam room, right? They're not just starting with unit testing with the database team. It's a different perspective on the market and a different philosophy on the market. It's clearly distinct, and it's clearly driving your success. If I take a lot of what you said and I align that with what were the financial targets that were put out at the last financial analyst meeting, fiscal 2027 this year marks an important inflection point for cloud database growth. The environment's clearly supportive, right? You've got data migrations accelerating, coding agents that are, in part, reducing the associated friction of that, multi-cloud reaching global regional availability. Beyond these factors, what else underpins your confidence in hitting these targets over the next few years, specifically in cloud database? Well, so we just announced that we have 22 regions live now with Amazon in multi-cloud database. If you look back at our last earnings, we had already gone live with Azure. It was our first partnership with Microsoft, then with Google, and now with Amazon. In Q4, we announced over 400% growth in our multi-cloud database business. The good news is that that's largely concentrated in the earlier partnerships and not in the Amazon partnership because we're now just delivering those regions, and now you have 22 of them live, which is pretty quick growth here as we go across the board. We feel good about our position in that business. I think the other thing that gives us confidence in database and cloud growth around database is that more than ever, data matters. More than ever, as we think about, again, not to repeat what I said, but get back into this idea of applied AI, differentiated AI, outcome-based AI. Without the database, you can't do it, right? You just can't do it. So whether the customer is running AI infrastructure on Amazon, on Google, on Microsoft, we're agnostic. Even running on OCI, we're agnostic. We're model-agnostic, right? We arbitrage open source models. We open source OpenAI inside of our own applications. But all against the Oracle Database, right? So we can take the Oracle Database. We've made the Oracle Database very portable. We've made our infrastructure very portable. The same reason that we're able to take the Oracle Database and make it available in all of our competitors' infrastructure is the same reason that we, I think, have a unique competitive advantage in the infrastructure business in general. The good old CPU business. Long ago, we remember that business like last year. The good old infrastructure business is that our form factor is very differentiated. Our form factor is smaller. It would be not as easy. If you were to say, "Well, we're going to go build Oracle Cloud Database inside Amazon for 22 sites." If we needed hundreds of racks per site to do that wouldn't be such a good value prop for us, right? But the fact that we can do this with such a small number of racks, and then it's that same technology that allows us to create fully sovereign infrastructure with 12 racks. I don't mean like an edge solution here. I'm talking about full-featured OCI, all of Fusion, all of our applications, everything that you want in 12 racks. You can imagine that that becomes a price point that's very attractive for countries and enterprises throughout the world. Again, I'm sorry it's the same boring story, but the fact that we're in every one of these businesses gets us to more of a turnkey solution at the best price point for the money. Why am I also continuing to be confident in our cloud database growth? Well, look, there are a lot of Amazon customers, AWS customers, that are also Oracle Database customers, right? Early days of that infrastructure build-out, 22 sites live. I feel good about it. 12 racks and can scale horizontally too. By the way, 12 racks is probably high. We're getting down to six. Even smaller. Yeah, we are getting down to six. Well, this becomes a really interesting kind of infrastructure question because, look, the big giga sale stuff gets all the headlines today, right? It gets all the headlines, and rightfully so, right? There is a lot going on in the industry there. But think about how many banks, utilities, even large healthcare systems, how many of them have their own existing data centers today? Lots, right? How many legacy data centers are there out there? As you see banks modernize from COBOL, there is a lot of space that is going to free up on the floor. Pretty easy to think about getting 12 racks or six racks into that from an infrastructure standpoint and having a turnkey cloud solution. By the way, that is not a very capital-intensive business. These data centers are already energized. You might do a little retrofit. You might put some different chillers in there and things like that. But it is not like you need to go build something brand new or go acquire the land or figure out how you are going to get the power for it, right? That same form factor that allows us to take the Oracle Database and make it completely portable to any of our competitors' database also gives us full scale advantage to be able to deliver a much smaller form factor cloud for existing database infrastructure. I think, the other thing that I like about that business is because asset-intensive industries or heavily regulated industries have been slow to move their mission-critical stuff, if you will, to the cloud, whether it is database or applications. Now kind of getting on board in this mythos moment to say, "We actually might want to think about at least ring-fencing our mission-critical stuff in the cloud, if not thinking about a SaaS or database cloud transition," that starts to unlock this value proposition conversation around this saying, "Well, how about we have a best of both worlds conversation for you? We can bring it to you in private cloud. We will bring it to you in private cloud in your data center, with a number of racks that is very palatable, and we will deliver the racks, we will deliver OCI, we will deliver the applications, we will deliver the database, we will deliver the analytics." That I think is an interesting. It's a really interesting point in a world where power is the constraint to all this explosive growth that we're seeing. Thanks for pointing that out. While we're on the topic of infrastructure, and you touched on this a little bit, there's a lot of focus today on OpenAI models and their implications. Oracle has taken more of a Switzerland approach of not competing at the model layer, and instead wanting to be a compute provider to everyone. Can we just get your thoughts on the emergence of open models becoming one of the primary ways of serving inferencing in the enterprise? Yeah. Look, I think there's a place for open models. In fact, in some of those, if you use the examples that I gave earlier with HCM, we're arbitraging both, in this case, OpenAI and open models, right? We're using ChatOS and some of these things on the back end. If there's a good enough result from the model that results in a high-quality answer for customers, we're by no means opposed to leveraging that and, again, keeping our costs low as a result. I think there will be a place for both, just like open source infrastructure, in that you tend to see on the mission-critical side that the key mission-critical infrastructure is largely running on enterprise-grade or enterprise-provided infrastructure, more of the ancillary pieces on open source. I think when you think about the way that AI intersects with data, there's going to be lots of questions around safety and security from customers around how that whole thing works. So, we're in a good position to have that conversation with customers because we are arbitraging models. We're not locked into any particular model. I think there will be multiple winners in the space. I think there will be open source winners as well. I do. I think customers are going to make the choice as to which one they'd like to consume, and I think in certain regulated industries, it's probably going to tend more to the enterprise-provided models than it does to the open source. Do I think there's a place for open source? Absolutely. Just like Linux. We're in the Linux business, right? It's not unfamiliar territory for Oracle. We understand, and we've supported open source for decades. For sure, and I remember I was there at OpenWorld many years ago when Unbreakable was announced. I'm showing my age, but Mike, I've always been interested in looking at adoption patterns of enterprise technology and enterprise software. People talk about classic S-curve adoption. I often think of it as a value prop just becoming so compelling that from CFO to CFO on the golf course or CEO to CEO, you see that your peers are doing it, you feel that you have to do something. I'd be curious your perspective. Is there a specific customer profile or maybe set of workloads that you see acting with a greater sense of urgency to migrate today and to become AI-infused, or has anything surprised you about which customers are moving first? Yeah. Well, it's a really interesting time for that question, again, because of the cyber concerns in the world, right? I think you're seeing a little bit, Brad, of a paradigm shift in that. Think about the general move to the cloud, right? One of the things that made it sometimes go slower for folks than they would like, or it made it more expensive, is because they try to move and transform at the same time, right? How do you move this workload, and how do I transform it into a modern application stack? Whether it's SaaS, whether it's PaaS, whatever layer it's at, and how do I modernize it at the same time? That added cycles, that added change management, that added unforeseen circumstances. I think this idea of ring-fencing everything that somebody has, ring-fencing it into at least being able to defend, having a perimeter around this because of the impact, the potential downside impact of a cyber trade-off with AI, is probably becoming a more popular conversation than the transform at the same time conversation, which is obviously going to lend itself to our CPU infrastructure business as well. On the heels of that, where I think there's another big opportunity for AI is the time to go live. Is reducing the time to go live. Particularly when you have big ERP transformations, which as you mentioned before, sometimes have been plagued with cost overruns, time overruns, and expectations not being met. These models, and we're leveraging with our own services team, have become very good at understanding customers' environments, understanding, for example, an E-Business Suite implementation, understanding all the customizations that have been made, and figuring out what's the best path for you to get to a more vanilla Fusion application, and then what are the agents that you should create to go replace those customizations. You're seeing compression from years to months. I'll give you an example. We spoke about this. We're a large provider to the US Department of Veterans Affairs for electronic health records. Yeah. We saw the time to go live because of the AI tooling that we. Healthcare is probably the most complicated industry from a go-live perspective, just because of all the regulatory, patient safety, and all the things, all the boxes that you need to tick, very important boxes you need to tick as you go live. We saw that come from 18 months down to eight months. Same set of people, same consultants, same implementation people, but with AI tooling, understanding the before and the after is dramatic. That one does involve a transformation. That does involve new clinical processes. That does involve new workflows and new configurations. Now, if you just wanted to say, how do I get from here to here, get the same functionality without doing any transformation, I think you are going to see that curve continue to bend. Good news is that, as we talk about our deferred position being greater than our in-quarter position is, one of the things that would be to our advantage is to decrease the ramp, decrease the go-live times, because you have got so much of that revenue sitting at deferred at this point, and the more quickly that you can bring it in, obviously, the better off you are. Very good point. I think we are almost about out of time, but I am going to ask you one final question. If I look out a year from now, what do you expect will have changed most meaningfully in how investors view Oracle's growth profile and competitive position? Well, a year is a long time in the age of AI, but I think, look, as you mentioned, we are approaching the sort of peak of our scaled-out infrastructure delivery. In the short term, short term being, let us use your year as a short-term horizon. We are probably in a position to deliver an industry-leading amount of compute to the market, of scale compute to the market. So I think proof points around that delivery are going to be important to the market. I think innovations, and I think the other thing that will be interesting over the next year is that I feel good about the fact that we are in a very good position to deliver meaningful AI proof points that are going to do two things. Number one, they are going to help enterprises and governments get more comfortable with the application of AI. But I also think they're going to be particularly acute in businesses like healthcare. I think those things are going to be good for the world. I think what the world really wants to hear is some very positive proof points around this. If you look at some of the backlash and some of the sentiment around AI in the market today, there's one shining star. That is, if you look at all the polls, people largely believe that AI can have a dramatic impact on healthcare, on better outcomes for patients. I don't think the world is that far away from actually delivering some of that stuff. That makes me very excited. It's good for the world, good for the country. It's also good for business. So I think that we put all those things together, and I would hope that in the next year, that those are the things we talk about next year in terms of accomplishments. Awesome. Well, Mike, it's always great to see you, even better here- Thank you at the Deutsche Bank Technology Conference. Thanks for having me, and thanks, everyone, for your attention and participation. Thank you