# Commodification of Intelligence: Good, Bad, and Ugly Circular AI Deals

> Source: <https://www.emergingtrajectories.com/lh/commodification-and-circularity/>
> Published: 2026-07-29 18:57:10+00:00

Every few months, and especially this week, the AI space gets criticized for circular financing and customer relationships. OpenAI raises money from Microsoft, spending it on Microsoft servers; Nvidia backstops CoreWeave debt, and CoreWeave buys Nvidia GPUs. “The bubble is about to burst!” analysts scream.

Analysts point to dot-com deals with circular investments in 1999, arguing that this is all bound to
happen again[[1]](#ref-1) [2]. They are wrong.

Circular deals are more interesting than “good” or “bad.” They show the AI industry isn't just maturing, but modifying the idea of “AI” to something that is less a technology product, and more a commodity. Imagine that—intelligence available like electricity, and the underlying financial system structured accordingly.

The evolution of circular deals points to the *commodification* of AI, where
compute capacity is moving from a business model where you buy a product (e.g., the hardware, or
space in a data center) to something so fungible that you buy it the way you buy electricity,
copper, natural gas, or other commodities.

We'll explore why circular deals are particularly important in commodity industries and
what this implies for understanding the trajectory of AI. First we'll cover how major investments in *traditional* commodities
markets work to ground our analogy more clearly. Next, we'll cover the investments that
mimic this process in AI, showing how such investments can be healthy. Finally, we'll
explore a few examples where circular deals do *not* abide by this analogy and how these
deals are introducing risks that could one day turn into awful surprises for the companies
themselves, their investors, or the entire sector.

Complex commodity infrastructure like mines, refineries, and ports comes with such large development costs that a bank lending a development company money can potentially risk its own solvency in doing so. Circular deals with multiple customers or beneficiaries, and potentially even governments, are often the only solution that gets shovels in dirt or ships in the water.

Let's look at a simplified example of such a deal. Imagine you want to develop your region's economy with several wells and a pipeline, and you can't afford it. You partner with a commodity trading firm who agrees to make your company attractive to banks or bond buyers by guaranteeing they will buy all your oil at a certain price. This means you are guaranteed revenue for the foreseeable future, and the banks know they can trust you'll repay their loans. The trading firm might even take an equity stake in your company for good measure—potentially to encourage better governance or oversight.

With such a relationship between you and the oil trader, you've got oil, a large bank loan, and a guaranteed customer… you've got yourself a circular commodities deal!

This is not a contrived example; it's a common strategy developed and evolved since the
1960s. Japanese commodities traders and development banks financed infrastructure to enable
commodity development, committing to future purchases and equity deals [3]. Jamaica did so in the 1980s

More recently, the US government began facilitating circular deal making to stimulate the critical
minerals sector in its bid for supply chain resilience. Last year, MP Materials, a relative
newcomer to magnet manufacturing and critical minerals, announced a 10-year relationship with the
Department of War, where the latter committed to buying all neodymium-praseodymium (i.e., magnets)
from the company for at least $110/kg [5]. Since then,
such off-take agreements have been announced between MP Materials and General Motors

Fungible commodities with large global markets are particularly well suited to such deals because the counterparty guaranteeing to be a customer (i.e., the oil trading firm in our example above) knows there is a large market they can tap into. They likely have a history of successfully making such sales, otherwise they wouldn't have billions of dollars and a pristine reputation they can leverage.

The frontier generative AI industry—be it model development or inference—is very much dependent on Nvidia. GPUs are effectively a fungible commodity thanks to Nvidia's development of the underlying infrastructure and standardization across all firms in the space. Three forces are enabling AI chips and associated data centers to act like a fungible commodity:

As a result, GPUs, electricity, and data centers are all effectively fungible, with large order backlogs and pent-up demand. If you build a data center and can't leverage it for your own business, there's a good chance you can sell it to someone who can—they might even pay a premium for availability in the short term.

SpaceX and Meta, despite trying to build top-tier foundation models, are profitably leasing their
own data centers to others—these data centers are working today and ready for frontier lab
workloads. Well-capitalized labs are willing to pay a huge premium for the privilege. SpaceX
leases its Colossus 1 and 2 data centers for over $2 billion per month [8], at a significant markup over other smaller clouds and data
centers

Let's now return to the aspiring startup or neocloud. You are starting up and, like our oil example earlier, have proven yourself on a small scale but now need your own data center or access to thousands of GPUs. What can you do?

Enter Nvidia and the circular deal—much like the oil deal.

Nvidia provides the capital and product access to your startup, prioritizing your access to its GPUs
so you can get the hardware you need. Nvidia has a $1 trillion order backlog [10] and knows it can resell your hardware or make better use of
it if you fail, so it goes a step further: it becomes the guaranteed buyer of your compute if you
can't take advantage of it… much like SpaceX and Meta above. This is not
theoretical—SemiAnalysis provides estimates for Nvidia compute off-take agreements and
pricing

This is, of course, one type of circular deal, and a relatively simple one at that. It's been
used in CoreWeave's $6.3 billion deal with Nvidia [12], alongside smaller data center operators like Firmus ($505
million

This helps explain why we see so many interconnecting and circular
relationships—OpenAI cancels its deal with Oracle, so Meta swoops in [14]; SpaceX leases servers to Google, Google invests in
Anthropic; and so on.

Wall Street gets circular deals, and humanity gets artificial general intelligence… purportedly.

Nvidia argues it is supporting a global AI ecosystem. Unfortunately, this doesn't preclude it
from overextending itself. A $6.3 billion deal with CoreWeave is one thing, but committing up to
$750 billion [2] is another.

The success of this approach for startups and neoclouds also assumes that AI and data centers continue to be fungible and “resellable”. Should standards or chipsets change, or should technologies make it easier to run local models or models on small clusters, then the business models might fail and the off-take agreements Nvidia has might not help the ecosystem much.

Circularity becomes particularly nefarious when it is used to hide the effects of the investments, debts, or other obligations from investors.

[Figure 1](#fig-google-backstop) shows the FT's [15] breakdown of a recent TeraWulf bond deal. In this case,
TeraWulf can obtain financing given Google's backstop of any lease failures, should Fluidstack
not be able to pay TeraWulf, or Anthropic unable to pay Fluidstack

Similarly, Meta's $27.3 billion Hyperion data center bond sale is an off-balance sheet one [17], as is its more recent $12.3 billion deal marketed
by BlackRock

Many finance professionals argue that these bonds are ultimately guaranteed by the impressive and continually growing revenues and profits from the hyperscalers, so there is nothing to worry about. The reason these bonds find so many customers, despite the circularity label, is that the final guarantors (i.e., the hyperscalers) generate billions of dollars of profit every year and can easily cover these costs, should it come down to that.

… but this is *today*, and it's with the current bond deals. Will
tomorrow's bond deals be supported by the hyperscalers in the same way? And what happens if
hyperscaler revenue trends change? What if the banks begin expanding the backstop agreements from
hyperscalers to “generally pretty decent” companies? What if the backstop fails to be
enforced? Will we see hyperscaler-backstop-backed-bonds grouped together, collateralized, and
resold the way Mortgage Backed Securities were in 2007?[[19]](#ref-19)

Circular deals are not bad. In fact, they are critical in the development of the AI ecosystem much like such deals are used in critical minerals, oil, electric vehicles, and other capital intensive industries with incredibly high startup costs.

The circularity helps illustrate the commodification of AI today, and how the technology might one day be more like electricity or an internet connection, rather than a product one buys or subscribes to.

When circular deals are supported by overextended lenders, or when overextended lenders try to move
such deals off their balance sheets, they become ugly and bad—in other words,
incredibly risky. This industry is likely to grow much more in the coming years, so it is important to watch for the lowering of standards or aggregation of risk. As SemiAnalysis
writes [11]:

AI Debt Financing will become a multi-trillion-dollar credit market, with over $7T of debt outstanding by 2029 driven both by AI IT Capex and AI Datacenter Capex needs [...] This will make it the second largest asset backed debt market after the US mortgage-backed financing market at just over $13T.

In this evolution, there might be a few bad deals along the way. It's important to keep your eyes open.

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