Oracle Corp The Six Five Summit: AI Unleashed 2026

It is nice to be here.

Let us go. I work at Oracle, so it is not too dissimilar.

Yeah. Look, I think, the overall thought process, I would say, is it's gone from how do I build an AI model to essentially how do I operationalize AI across my entire organization, right? That's the key message that I would talk about. A year ago, a lot of the customers were like, "Well, which model should I use? What GPU should I buy? How fast can I train?" They're still important questions, but not for the enterprise customer, right? Today, I think I would say CIOs are asking very different set of questions. How do I connect my AI to my enterprise data? How do I run governance on it? How do I keep my sensitive information to myself within the bounds of my data center or my boundaries? How do I scale AI across thousands of employees and business processes, right?

Actually, Oracle is going through that significant change ourselves. How do I control costs over time, right? That's actually the recent conversation a lot of the times is, great, we're using AI, but costs are ballooning. How do I control that? Is it through inferencing? Is it through building my own model? How do I think about the cost aspect of it, right? So this is why AI infrastructure has become really strategic, right? It's no longer a standard work alone, workload, so to speak. It's really embedded into, I would say, all of our applications. Especially working at Oracle, we're just not just an infrastructure company, we're an applications company as well, right? So it's embedded into ERP, HCM, supply chain, healthcare, financial services, manufacturing. So basically, every enterprise workflow that you can think of, right? Infrastructure is just much more than compute.

It's more than GPU compute anyway. It's everything from security, identity, databases, massive datasets. We're seeing the enterprises go through the motions and be a bit more pragmatic about they don't want 10 different AI platforms. They want the data to come, rather than data come into AI, they want AI to come to the data. There's lots of change going on as they really figure out, how do I embed AI into all of my business processes, people, and function? That's essentially the big change. There's no answer yet, but I think they're going through that sea change now.

I'll start with the last statement I just made, which was, most customers increasingly want the AI to come to their data, not the other way around. What that means is that, most enterprise data is not just sitting in one cloud. It's on premises, it's in an Oracle Database, maybe it's in some of the other cloud providers, maybe it's in some neo clouds. Some must actually remain inside a sovereign environment. With AI becoming critical infrastructure for a lot of governments, if you go outside the U.S., the geopolitical space, it's governed. It's regulated. AI changes all those assumptions. What customers are really telling us now is they want to keep the data where it lives. They want to apply AI consistently across all their environments, not Snowflake environments.

They want to maintain a single security model and governance framework as well at the same time. For us, from an Oracle standpoint, this is essentially what distributed cloud has become. It's really become a significant differentiator for us. We've got now probably over 50 to 70 dedicated regions and Oracle Alloys that are deployed globally, and it's actually worked out really well for us because it's the same code, it's the same set of services, but the deployment model's slightly different depending on the needs that you have whether it's public cloud, whether it's a dedicated region at customer's facility, whether it's Cloud@Customer, if you've got your data sitting on an Oracle Exadata box, as an example, right next to your AI, whether it's sovereign cloud, partner clouds with Oracle Alloy.