What's The Big Deal?
Get the view from the inside. Every week, Graham Smith (ex-Ares) and Deborah Taylor (ex-Barclays) take a look at Wall Street’s headline-grabbing deals.
From mega-mergers and hostile takeovers to complex private credit transactions, they break down the why, the how, and the who behind the numbers.
What's The Big Deal?
How AI Data Centres Are Funded — And What Happens When the Money Stops
Use Left/Right to seek, Home/End to jump to start or end. Hold shift to jump forward or backward.
OpenAI has missed a revenue target in the run-up to what is expected to be one of the largest IPOs in history. Sam Altman and the company's CFO have been publicly at odds.
And behind all of this sits close to $700 billion of committed CapEx across the major hyperscalers, much of it financed through project finance structures that were built on the assumption of hyper-aggressive AI revenue growth.
In this episode, Debs and Graham use the OpenAI revenue miss as a lens to examine how AI infrastructure financing actually works, who is exposed when things wobble, and how a shortfall at the end of the chain could propagate upward.
Debs walks through the mechanics of project finance as it has been adapted for data centre construction. SPVs are set up to construct and operate individual facilities, with construction contracts and take or pay revenue agreements signed in advance to create predictable cash flows.
That predictability is what allows the SPV to finance itself at up to 90% debt, significantly more leveraged than a typical LBO, and on 15 year lease terms.
The financing is bankruptcy remote, meaning SPV investors have no direct recourse to the hyperscalers themselves.
That structure works cleanly until one of the counterparties at the end of the chain stops performing.
Oracle, which handles two thirds of OpenAI's compute commitments and carries the weakest credit rating among the major hyperscalers, is identified as the most exposed party.
A sustained revenue miss from OpenAI puts Oracle under pressure on its own SPV contract obligations, raising the prospect of a credit downgrade from just above investment grade to junk, with potential covenant implications that would compound the problem further.
The episode closes with the broader question of whether the AI infrastructure build-out is entering its first genuine stress test, and what the next 12 months of investor reporting might finally reveal about the numbers behind the narrative.
Key Discussion Points:
> OpenAI pre-IPO: what the revenue miss and exec conflict signal about the state of the business.
> Hyperscaler CapEx commitments: the scale of spending committed for 2026 and how it is being financed across public and private markets.
> Project finance mechanics: SPV structure, construction contracts, take or pay agreements, and the debt waterfall.
> Leverage and risk: why data centre project finance operates at 90% leverage and why that is only sustainable with locked-in cash flows.
> Oracle's position: credit rating, exposure to OpenAI and the domino risk within the financing chain.
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What do you see this?
SPEAKER_00This is not what big companies that are about to list for one of the biggest ideas ever are supposed to do.
SPEAKER_02I think it's a bit of a they are investing in infrastructure.
SPEAKER_00Actually, bankruptcy isn't a huge risk. But what is a risk is they say, yeah, we spend this much contract, but we don't have the cash to pay it right now.
SPEAKER_02We're gonna talk about project finance, how this machine is funding hyperscale investments.
SPEAKER_00This is an advance of the IPO, even, right? Because they haven't even actually filed for their for their IPO yet. You've got Sam Altman and their CFO having like this public debate about an argument about missing their revenue number.
SPEAKER_02Welcome to this week's episode of What's the Big Deal, uh, where we do talk about major deals in the public and private markets and explore finance industry developments. My name is Deborah Taylor, and I'm gonna use my background for my career in investment banking to talk about things from a public markets perspective.
SPEAKER_00And I'm Graham Smith. I'm gonna use my background in private credit to talk about things from a private market perspective.
SPEAKER_02Fantastic. Right, Graham, let's dive in. What is the big deal this week that we're gonna talk about?
SPEAKER_00So no surprise, we're back to obviously we got a few big recurring themes this year with with AI. We've talked about this in the context of a few, a few different things. And actually, it's kind of it's kind of really it's obviously topical because there's a lot going on. We wanted to have kind of an educational, an educational episode today on hyperscalers and kind of perfect timing in the sense that open AI just missed a revenue forecast. They're obviously one of the big hyperscalers, really taking a lot of data center capacity. So both want to have a chat about what's going on with OpenAI, talk about the overall landscape. And if things are wobbling a little bit, then talk about just some early views on who's at risk and what might happen over the next year or so.
SPEAKER_02Absolutely. So uh we've got you starting off on the numbers this week. You'll talk about why a single missed record revenue number is actually affecting the public markets. I know we've had a big sell-off on some stocks uh over just the last couple of days. We're going to talk about project finance, how this machine is funding hyperscaler investments, and who's funding this and how. Um, and then finally, we'll have a little discussion uh about why data center investments are looking maybe a bit more risky today than they were even a few weeks ago. And whose risk is that? That's really the big question, isn't it? Graham, the news on OpenAI's revenues, why does this matter?
SPEAKER_00Well, this is, I mean, this this actually follows on from some of the discussion we were having on the open A anthropic IPOs that are that are coming down the track this year. And if anyone has listened to that episode, one of the things we talked about was just some of the hyper-aggressive revenue recognition policies that look, we don't, we don't know for sure that they're using, but you can you can kind of you can kind of venture an estimated or an educated guess here and and really say that one, you kind of know a lot of these high-growth tech companies in the run-up to IPO are going to recognize revenue as aggressively as they possibly can. Look, I don't know what your view is on OpenAI, Sam Altman, just the whole the whole cast of characters involved in this overall landscape, but just knowing what you know about them as individuals, like do you think they are being conservative with their revenue recognition policies or perhaps a little bit aggressive or slightly too aggressive? So I think when we when we see some news that the the revenue and this is a this is in advance of the the IPO, even, right? Because they haven't even actually filed for their for their IPO yet. They've missed a revenue target and they've missed it based on these super aggressive revenue recognition policies that I think we all assume they're using. And you also look at the you look at the the other stuff that's happening with OpenAI in particular, and you've got you've got Sam Altman and their CFO having like this public debate about an argument about missing their revenue number. And I think that's just made a lot of people say, like, what's going on? This is this is just crazy. This isn't what companies are supposed to do. This is not what big companies that are about to list for one of the biggest IPOs ever are supposed to do. And I think you put that in the context of you've got all this committed capex spend across all these all these hyperscalers, and people are saying, all right, if we're already missing revenue targets, what is gonna come of all this data center capacity that's already been committed and is both built already, coming online, all the committed capex that has been uh that's been made in this space. I think everyone's just taking a step back and saying, wait a minute, what's going on?
SPEAKER_02Yeah, because it it does sound incredibly chaotic from their side. And definitely we've seen examples of this before where where you see this tension between sort of execs, it's usually a reflection of what's how pressured things are behind the scenes. So that in itself for me is a very, very poor signal. Um, but you mentioned around the commitments because we're talking here about revenue, misses, but they are committed to huge amounts of spending off the back of quite aggressive growth targets, aren't they? Whereas you know, we're normally thinking about opex, you know, against current revenue numbers. But because the growth of revenue was so expected to be so aggressive, they've signed up to big future spend that they can't easily walk away from, can they?
SPEAKER_00No, and I think the other thing is you have you have these big, when we say hyperscalers, we're talking, we're really talking the huge tech providers like the AWSs and Microsoft's and Metas and OpenAI. And I think everyone, and we'll talk a little bit about project finance and everyone who is actually building and financing these data centers. When you have a contract signed by one of these big hyperscalers, you kind of think of that as pretty bulletproof. And you secure equity financing, you secure debt financing against these long-term contracts. And then when you have one of these really big guys say, Oh, I don't know if I've made my revenue target, I think that makes everyone freak out a little bit. Because to your point, they've committed just a ton of capex spend off expectations of hyper growth. And if that growth doesn't come, then then the question is what happens and who's exposed.
SPEAKER_02Yes, it's a big question. What happens and who's exposed? We'll definitely we'll get onto that. Um, should we talk a little bit about the financing of uh well, the capex spend and sort of how that's being financed? Because these are big numbers that we're hearing.
SPEAKER_00Yeah, yeah, yeah. And so, I mean, the numbers, so I'll I'll kind of run through just the high-level numbers and then you've got more of a project finance background. So I'm actually really keen to get your take on just how, like just how all this stuff comes together. All right. So I'm just looking for, I think this is just for for this year. We're looking at a total committed capex spend of 700, 725 billion across some of the main players. So Amazon, Microsoft, Google, Meta, Amazon 200 billion, Microsoft 190 billion, Google 190 billion, meta 145 billion. I think literally as we've been looking this up, we've seen some press releases. Uh I think it's Meta in particular, even upping, upping their CapEx target. So everyone, everyone is just going all in on data center build, compute capacity. Um, and it's really, it's really driven by these big hyperscalers. The other one that's kind of interesting, and I think you know more, you know a bit more about this than I do, is just how Oracle fits into all this. Because it's actually kind of interesting. Like Oracle has been around forever. I feel like until a few years ago, people probably forgot about them a little bit. I mean, started as a database business and ERP software, which I don't know, is not particularly exciting. And then they really jumped in on the AI bandwagon and to date have been real, real winners. Uh, but also sounds like they're potentially they're potentially on that list of parties who's pretty exposed here. Um so that's that that's literally just for 2026, the better part, like the better part of a trillion dollars of committed capex spend on data center compute capacity. And admittedly, when we say when we say spend, that's not that's not just on the physical buildings, that's on the servers, the GPUs. Obviously, the GPU is like a massively, a massively expensive component of this CapEx. Absolutely. And I don't have the the details of how all this breaks down necessarily, but the numbers here are big.
SPEAKER_02Yeah, because I think everybody wants to be on that bandwagon. There have been big numbers thrown around. Everyone's talking about AI investment, but without specifying what they mean by that investment, is it data centers, is it chips? And you know, and also it's not always clear how all the pieces of the jigsaw fit together. You mentioned Oracle, OpenAI, um, there are you know other you know, people who are sort of involved in this AI investment, but sort of how does it all kind of connect together? So I think we could we should talk about that a little bit because that kind of I think gets the nub of why this open AI news is so important because potentially it kind of is the first link in a whole chain of things that could potentially unravel if you know worst comes for worst. Um but let's talk about the financing for a lot of this spend. So, in terms of the financing for all of this huge CapEx spend, it is coming from the debt markets, and roughly half of that is coming from the public markets, that's like bonds, and half is coming from the private markets. Now, I think on the public market side, what's happening in you know with bonds is really well talked about. A lot of us have heard about, you know, uh all the bonds that have been issued by the hyperscalers, Meta, Alphabet with that hundred-year bond. Um, I mean, there's been huge amounts. $1.2 trillion of bonds have been issued over the last, you know, I think up to now in terms of funding AI spent. Um, and that's you know, spend that's coming from the hyperscalers that's on their balance sheet. Um, now a lot of this is being deployed in purchasing chips, those are the GPUs, which you explained so beautifully in a recent episode. Um, I think Oracle is a bit of an outlier because they are investing in AI infrastructure. They have a much weaker credit rating than the other hyperscalers. So they can't tap into the bond markets quite to the same extent as the others. So they've actually arranged some uh structured financing. I think it was led by PIMCO recently. They issue, they basically arranged some financing with uh led by them. So um we have got some spend which is actually on the corporate balance sheets, but I think what's maybe less well understood um is the element that's being provided by the private markets through project finance. And project finance isn't a new thing, that is a decades-old form of financing infrastructure projects. And you know, for example, the Channel Tunnel, power stations, all of those are funded through project finance, but now it's being repurposed for data center financing. Um and the way that that works is I think quite interesting um in kind of peeling back the layers of how you know different funders are involved. So, well, how does project finance work? Um, so first of all, a special company is set up, what we refer to as a special purpose company or an SPV, uh, to construct and operate the data center. Um and you might have heard of SPVs after Enron, you know, they've got a bit of a bad rap, but they're widely used for kind of arranging kind of uh these kind of structured finance uh arrangements. Now, what that SPV needs is really predictable cash flows. It needs to be really low risk in terms of you know what the cash flows are going to be for the construction and then the cash flows that will come in once that data center is operational. Okay. So what the SPV does is just signs loads of contracts to take the risk outside the vehicle. So that would be like construction contracts and a fixed fee contract for constructing the data center, and then revenue contracts for when it becomes operational. Now, those could be leases or what we refer to as take or pay contracts, where the sort of the customer, if you like, for the data center agrees to take and has to pay for that the compute uh power from the from the data center. Um, even if they don't use it, they're locked into that contract. And that is actually really important in terms of when we're thinking about the open AI effects. Okay. Now, once you've done that, once those contracts have been signed, you've now got really predictable cash flows. And that means you can now let use loads of debt financing to fund the construction side of things. And when we talk when I talk about lots of leverage, we're talking more leverage even than you know, you were referencing last week in last week's episodes around leverage buyouts. We're talking about 90% debt financing, 10% equity financing. So this is extremely leveraged, but on the basis the cash flows are going to be very, very predictable. Okay.
SPEAKER_00So basically, basically what you do just just for my own benefit and for everyone else, you you set up this SPV, you go out and you arrange everything before you before you start with breaking ground on the actual data center. So arrange the construction, the contracts, right? And then and then once everything is kind of signed, signed and delivered, then you go out to the financing market and say, okay, I've got this just insanely robust set of lease payments that's signed up for what I I don't I don't want a typical lease term is on a data center like this.
SPEAKER_02Like 15 years or something. Yeah.
SPEAKER_00So I and I assume that goes that extends beyond whatever whatever kind of credit facility is is extended or offered to these to these SPVs.
SPEAKER_02Yes, I'd assume so, yeah. But the idea is that the the revenues, if you like, for the SPV, they are going to basically be used to pay down that debt in a similar cash flow waterfall to the you know those that we see with leverage buyouts. So as soon as the revenues start coming in, you start paying the debt that was raised to fund the construction. So that's the way that some things are set up, basically.
SPEAKER_00Is is there any element of because when we talk about you know 10% equity, it reads it reads a bit CLO and structure. Are there are are these the kind of things that have different, like different tiers of of debt in essence, or is it just kind of one one big facility and whoever participates takes the same return?
SPEAKER_02Yeah, I mean I don't know the layers of financing in as much detail um as I do for leverage buyouts, but yeah, there are different chances within there. I just I don't know how sort of what a typical structure would look like. Um yeah, I mean it's it is you know that it is very, very leveraged, and you know, ultimately it's done on the basis that you have very predictable cash flows. What makes it really interesting is that from a tech company's perspective, they're signing these contracts with the SPVs and it doesn't actually go on their balance sheet. It's effectively off balance sheet until the data center becomes operational. So it's attractive from their perspective, it's attractive for those investing in it because they're basically um in sort of lending to or providing equity finance to a vehicle with very predictable but stable cash flows, or that's what you anticipate. Now, a key part of the SPV is that it is a bankruptcy remote vehicle. That means that those that invest in that vehicle have no recourse from the hyperscalers. So if things go wrong, the lenders can't tap into the hyperscalers unless there's some kind of additional guarantee that's being provided. Okay. And this becomes important if things do start to go wrong. However, we also know that the hyperscalers, you know, if they have lease commitments or even take or pay contracts, they can't walk away from those either. So we really then need to explore how this chain unravels if the per you know, the the party at the end of the chain, that's OpenAI effectively, if they can't afford their commitments, how does that affect Oracle, who basically rely on them for their revenues, for the compute? How does that then affect the SPV that's basically got the contract for the take or pay contract or the lease? And then how does that affect those providing the finance to the SPV? We've now got a weak link in the chain. How do things unravel?
SPEAKER_00There's there's a lot, there's a lot of stuff in this chain to get your to get your head around. I mean, so let's let's just kind of play out a quick scenario and say okay, it's it's probably it's probably unlikely that any of these big hyperscalers is going bankrupt. You never, I guess you never know with a company like like OpenAI, right? Never never say never, but let's assume for a second that actual bankruptcy isn't isn't a huge risk. But what is a risk is they say, yeah, we signed this long-term contract, but we just don't have the cash to, we don't have the cash to pay it right now. Like we missed our revenue targets. We're already burning literally all the cash in the world. So sorry. What what happens in that in that scenario?
SPEAKER_02A key issue here is that two-thirds of open AI's compute commitments are to Oracle. So Oracle has a big exposure to open AI. And that I think really means that we should focus in on you know Oracle's kind of position or sort of role within this chain. Yeah.
SPEAKER_01Right.
SPEAKER_02So let's say OpenAI, they you know, they disappoint on revenues. Again, it's, you know, they're now in the position where they're going to miss payments to Oracle, let's say. I guess the question, the first question, uh Graham, you probably have more experience of this than I do, but can they can things be reneged renegotiated? Could they even raise additional equity? I mean, those are the first steps, aren't they, when you're kind of thinking about restructuring.
SPEAKER_00100%. I mean, think think the the answer is things can always get renegotiated, right? When when things start getting into trouble as a as a lender, you're generally not just hitting the button on your your full-on enforcement and taking the keys to the business goodbye kind of process.
SPEAKER_01Yeah.
SPEAKER_00There's a discussion to be had around some kind of compromise. So you're right. I think that's that's probably what happens.
SPEAKER_01Yeah.
SPEAKER_00It's up, but does feel like Oracle, perhaps right now, is the most exposed in this in this chain. Is that fair to say?
SPEAKER_02Yeah, I think, I mean, it's a big if, but if OpenAI genuinely can't pay, can't renegotiate, Oracle does become the next focus because they are locked into those SPV contracts. They either lease contracts or take or pay contracts, they can't walk away from them. And as I mentioned earlier, they are the only one of the five big hyperscalers that don't have a high or a really good investment grade rating. They're just above the junk status. And I think their credit rating would be the next domino to fall. Um, and unfortunately, that would mean them being downgraded to junk status, which isn't just a change of label, it can be a covenant breach, for example. So for them, it puts them under a lot of pressure sort of within the lengths of the chain. I think in reality, if then they can't pay, then the SPV is left, of course, exposed. And those that have invested in the SPV are also exposed. But I mean, in theory, you would then expect that they could find a new tenant. I think they refer to them as anchor tenants, the the hyperscaler that's kind of going to be using the data center. So it could be repurposed, presumably, to a new anchor tenant.
SPEAKER_00And presumably, presumably, so when we talk about, and we don't have the split, right? But when we talk about this six, seven hundred billion of committed capex spend that is both the data center build and all the stuff that goes inside. Presumably the SPV is not really on the hook for the stuff necessarily if the if the cash, if the cash doesn't come in and the data center build doesn't finish. Or are we in this world where you finish the data center build, you get the client in, they stop paying, then I I guess there's there's a bunch of other financing for the stuff as well. Is that all the same SPV? Is that different financing parties? We've been hearing about you know ABLs on GPUs. Like there's there, I feel like the the number of counterparties here is almost like too big to keep track of.
SPEAKER_02Yeah. So I think yeah, definitely there's kind of a parceling up of the different assets within the data center. There's, you know, as you say, there's the GPUs, it's it has its own separate financing. But the actual physical building, um, the kind of all the equipment within there, um, I think is all covered by these contracts, which the SP which are so important to how the SPB functions. So once that's been signed, you're kind of locked into that construction. And therefore you're then locked into, you know, operating that data center. And I think that's the big issue for the SPBs is you know, can they find a new tenant? Uh you know, there is a small chance that you end up with, you know, what we refer to as stranded asset risk, where you have an asset which actually doesn't have really Much economic value, maybe because you know, technology has moved on in the few years, you know, since whilst the asset was being constructed. And you know, it's fine if you've got a tenant who's locked into the contract, but if you're then trying to find a new tenant, but that that asset's now aged in terms of technology, could it become a stranded asset? And I think that is the scenario where the investors in the SPV would be exposed. So there's a I think a lot of ifs, um, but maybe fewer ifs around Oracle's exposure.
SPEAKER_00Interesting. I mean, are we a world in which the in a world in which the uh Paramount Skydance Warner Brothers deal is now off because all of a sudden Larry's like, sorry, David, I don't have enough cash anymore. I got I gotta make good on all my data.
SPEAKER_02The chain keeps unraveling. Wow, where does it stop?
SPEAKER_00Seriously. I mean that the thing, the thing I I kind of take your point on the stranded asset thing, though, because if you I guess if you believe that we're in a world where open AI, as an example, can't can't make its data center payment, then who else gobbles that up? If the hyperscalers aren't aren't able to satisfy the demands, then like who is?
SPEAKER_02Yeah. Yeah. And I think so far a lot of the risk has been about whether there was a risk of oversupply in the m in the market. There's been so much investment in the infrastructure. And I think it was just talks about in very hypothetical terms. And now we're actually, you know, really starting to see that this is a genuine concern. And having to understand the difference.
SPEAKER_00It didn't take long for that, did it?
SPEAKER_02Well, I think we're two years in, but yeah, I think uh we're now it's we're now we now have hard numbers, or at least, well, it sounds like they're quite soft numbers to be honest, in open AI, but we have some data to work with because a lot of this has been on the private side, um, with you know, no real numbers being released until recently. Um but I think it is interesting because you know, we've talked about this as being open AI's issue, but it's not really just an open AI story. It's about how the financing of AI infrastructure has kind of grown and assembled itself over the last couple of years and it's now effectively being stress tested. You know, can it cope with the risk that you have maybe one you know company at the end of the chain not performing as expected? You know, and you know, ideally, if thing you know, if you know the people structuring it have done their jobs well, you know, and the risks of being well managed, it shouldn't unwind too, you know, in too chaotic a fashion, but you know, who knows? Yeah. And it's definitely a story. Go on, yeah, definitely a story where you know we had so much upside. It's all been positive, hasn't it? All the messaging. Invest in AI. You know, anyone who was you know mentioning AI investment in their press release, it's seen as a big positive, you know, is a is the tide turning, I guess.
SPEAKER_00Maybe. And we'll we'll see what happens in coming months and and coming years. I mean, because the one thing that is true in this space is things change so, so quickly. And, you know, if there's let's say, let's say we get to a point six, twelve months down the line where because the new compute capacity comes online, we see AI models that are just so much better even than the ones we know now, then are we in a position where all of a sudden revenue is growing again, and then we get into bigger discussions about you know everyone's losing their job because AI is taking their job because it's so good and all the things. So there's there's just a lot to a lot to unpick here. Um and no doubt we're gonna we're gonna keep talking about this just because it's I mean, I think it's it's interesting, it's topical, it's moving, it's moving quickly. And in some ways, uh we've been talking about the financing today, but also it impacts everyone to some extent. So it's uh it's a highly interesting topic.
SPEAKER_02It is interesting. I I don't know about you, but I feel like every day I'm learning more about how all of the different pieces work. You know, I you know, uh I think a lot of us have used AI without really questioning how, you know, how the companies operate, how the financing works. And so it is a good opportunity to learn a little bit more and you know, open your eyes to, you know, what the future is you know potentially going to hold.
SPEAKER_00100%. 100%. Because it's both bright and also quite dark at the same time, depending on what view you take and where you think it might go. So lots of stuff to think about.
SPEAKER_02So I think we've covered quite a lot of ground there in this week's episode. We'll take a pause now for uh for this week. Um but thanks ever so much for those of you that have been listening. And uh if you're listening on uh YouTube, if you're watching on YouTube, please do like and subscribe and leave us a comment. And if you're listening on Spotify or Apple, please do like and leave us a rating. So thanks very much from me and over to Graham.
SPEAKER_00And thanks for me as well. No doubt, lots more to come on this topic. It's gonna be a busy year. We still have the the big IPOs to come. I think the interesting thing for me is that we're gonna get a lot more actual data and have some numbers to really talk about once we see once we see some investor reporting come out. So watch this space because there's gonna be a lot, a lot more to talk about. So it's been it's been fun as always. Thanks, Debs, and we'll see everyone same time next week.