AI to ROI: Big Story - Will the Angst, Agony, and Adversity of AI be Worth It?

**Ray Rike** (0:08)
Welcome back to the AI to ROI, the Big Story edition podcast. I'm Ray Rike, Founder, CEO of Benchmarkit, and joining me as always is my co-host, Peter Buchanan.

**Peter Buchanan** (0:19)
Yes, I'm Peter Buchanan. I'm the founder of NewPlan, and Ray, it's great to be here. This week, we're going to talk about a topic that really captures the moment we're living through. And that topic is, with all the anxiety and angst, all the massive investment, there's a big question. And that big question is, is AI actually going to pay off?

**Ray Rike** (0:44)
That's exactly right. Comes from our Monday, March 9th, Big Story. Will angst, agony and adversity of AI be worth it? And I'm really excited because the spoiler alert, though, is it will be worth it. It's just going to be how difficult is the journey going to be, and how long is it going to take. So let's break down both sides of this story, Peter.

**Peter Buchanan** (1:10)
You bet.

**Ray Rike** (1:11)
One of my questions is, let's start with the reality. The infrastructure spending is staggering. Can you put some more numbers behind that for the audience?

**Peter Buchanan** (1:21)
I can. So let's start with the number that makes everyone's jaw drop. So just for this year, the five largest hyperscalers, that's Amazon, Microsoft, Alphabet, Meta and that newcomer Oracle, they're on track to spend over $600 billion on CapEx to support the delivery of AI. So 75 percent of that $600 plus billion goes directly to AI infrastructure, that's GPUs, servers, data centers, HVAC, electricity, labor. To put that in perspective, Ray, that level of spending nearly matches the combined scale of the Apollo program, the Interstate Highway system and the national build out of electricity all at once in a single year.

**Ray Rike** (2:15)
Well, tells me that things are getting a hell of a lot more expensive, Peter, or this is just that much bigger. And by the way, when we talk about bigger, I think that's where it gets really uncomfortable, because if you look at, you know, 23, 24, 25, the major hyperscalers, those companies you talked about, they funded the majority of that build out entirely from their own cash flows. And that air is over because the aggregate cap ex for 2026 actually is exceeding their combined free cash flow. So they're tapping into the debt market. An example, Oracle is spending 75% of its annual revenue on cap ex.

**Peter Buchanan** (2:55)
Well, 57, Ray. Don't give them too much. 57, not 75

**Ray Rike** (3:00)
And Microsoft's at 45

**Peter Buchanan** (3:02)
Yeah, yeah.

**Ray Rike** (3:03)
But those are ratios more typical of heavy industrial enterprises than software companies. Software has never been cap ex intensive. So is this partially what's behind all the talk we hear about credit risk for our $3 trillion private credit economy in the United States alone?

**Peter Buchanan** (3:22)
It is. And the bond markets are really paying attention. So Oracle's five-year credit default swap spread has more than tripled since September of 2025 So that's six months. Investors are genuinely concerned about their concentrated bet on OpenAI as an anchor customer.

**Ray Rike** (3:43)
Oh, Peter, we've talked about this multiple times in the newsletter, and that's the circular nature. In fact, was OpenAI just raised $110 billion last week? And that came from people like Amazon, who then committed, OpenAI then committed to actually purchase compute capacity from them. So very circular, right?

**Peter Buchanan** (4:09)
Amazon, NVIDIA, both of them. And those investments were actually, it was almost more like a supply chain deal than raising $110 billion and their milestones attached to them. So the $110 billion isn't going in the bank immediately.

**Ray Rike** (4:26)
You know, there is a little bit of some gray clouds out there. And one of them is that data center construction just can't keep up. So, even if you have all this capital, supply is not unlimited. You can't just snap your fingers and build out. An example, the world currently has around 12,000 data centers in operation, with 3,000 more being planned. And by 2030, that infrastructure spending is on track to reach $1 trillion. But here is the, I think the silver lining, and this is gonna be a thread I'm gonna pull through the rest of today's conversation, I don't think we're gonna see AI build out happening nearly as quickly, so it's not gonna be impacting jobs nearly as quickly, because almost every one of those data center construction projects is behind schedule, and I don't see it speeding up in the next 12, 24, 36 months. What do you think?

**Peter Buchanan** (5:23)