Oracle's ability to prove AI demand exists is established; future success depends on efficient conversion of backlog to revenue and managing debt.

Oracle moving higher this morning after an earnings beat and guidance that exceeded estimates. The company still expects CapEx between 90 and 95 billion for fiscal 2027.

So, Oracle, they reported earnings buck 92 per share on an adjusted basis. Revenue up almost 30% to 19.3 such more than 19.3 billion.

But listen, the standout was cloud. Cloud more than doubling cloud infrastructure revenue, 7.4 billion. So, you know, it's the numbers are really showing that Oracle is beginning to convert its enormous AI backlog into deployed infrastructure and actual revenue.

The key shift is from proving AI demand exists to proving that Oracle can deliver the capacity required to serve it. So, really, I know Oracle showed that it can sell AI infrastructure.

Great news. Now it needs to show how much of the enterprise AI stack they can capture around it.

I wonder if that's why it feels like investors don't know what to make of this, right? Because earlier we were higher than where we sit. Right now we're just up about a half a percent on shares right now.

And listen, they spent 28.5 billion on CapEx this quarter. Is that I mean, some may say this is simply the price of competing on this front.

Okay, let's talk about the backlog. They have a massive backlog, $664 billion. How much confidence should investors have in Oracle being able to deliver on that?

So, I I think that it remains to be to be seen. I I think that there is definitely some confidence there. Um the bigger question is how efficiently it can convert that contracted demand into capacity, revenue, margins, and ultimately cash flow.

Signing these massive AI contracts is the first step. Delivering the infrastructure behind them is much harder, and remember AI and um infrastructure is just the first part of this.

What we ultimately want to see are the applications and the business outcomes that will be running and using the infrastructure. Right. So, so if you think about it, Oracle is not only renting AI compute.

So, we're we're we're we're seeing the interest there.

Um what makes Oracle different, or I think there's a real opportunity, and what we should be watching, is it already sits close to enterprise databases. I mean, it is the enterprise database applications, valuable business data.

So, its opportunity is really to connect AI infrastructure with the data and applications enterprises already run. So, if that happens, OCI growth could drive higher value database and application consumption for Oracle.

And And you also say in terms of the competitive landscape, you say Oracle does not need to be AWS, Microsoft, or Google at their own game.

Well, it goes back to their combination of OCI, databases, enterprise applications, and their multi-cloud deployment. So, So, Oracle software can be deployed across multiple hyperscalers, and that gives it a differentiated position in the AI stack.

So, as enterprises increasingly operate across these multiple cloud models on prem, Oracle can capture these AI workloads without requiring customers necessarily standardize their entirely their entire technology environment on Oracle.

So, that's definitely a differentiator for Oracle. And Stephanie, I got to ask you about the debt load. That's obviously one of the challenges that or one of the issues that investors are challenged by here. They're carrying roughly 125 billion in debt.

How much of a challenge is that for investors who are looking at Oracle? I I mean, it's a challenge. I mean, the question is whether Oracle can add capacity quickly enough while maintaining the economics of the business.

As customer concentration, funding, long-term margins remain open questions. But, this quarter did provide stronger evidence that the demand is becoming revenue.