In recent weeks, you’ve probably come across a meme on social media that simulates several identical superheroes pointing at each other in bewilderment. Superimposed on their faces, company names like OpenAI, Nvidia, Oracle, Microsoft or AMD. However, the reason for this comical image should give us reason to reflect, if not to worry.
The current awakening of generative artificial intelligence is based on losses and numbers that don’t add up. After all, it is normal for investments in technology that are not yet mature to take time to turn into benefits. Up to this point it may even seem logical to us that companies like OpenAI is valued at $500 billion with just $13 billion in annualized revenue and estimated losses for 2026 at US$14 billion.
We are talking about OpenAI currently having a price-to-sales ratio of 38x, something unheard of for companies in any sector other than technology. So much so that, to justify this assessment, Sam Altman’s brand would need to reach $225 billion in revenue by 2030, with a free cash flow margin of 27%. Something that, except for a surprise in the form of the advent of general AI that seems quite unlikely with current models, seems unlikely to happen.
But let’s assume, for the purposes of this reflection, that these feet of clay do not exist and that the future of OpenAI is based on solid foundations. The real problem, and therefore the meme that gives rise to this column, lies in the unprecedented circular financing structure that exists in the artificial intelligence market.
Let’s be clear: the AI funding ecosystem is characterized by a pattern in which Suppliers invest in their own customers, who then use this capital to purchase products and services from those same suppliers..
I am not the first, far from it, to notice this dissonance from the manuals: analysts are increasingly concerned about this phenomenon. The Bank of England warned last month of “risks of sharp corrections in AI”. Morgan Stanley directly alludes to the fact that “providers are financing customers and sharing revenue; there is mutual ownership and increasing concentration. Increasingly complex transactions make it difficult to assess real demand for AI and increase the risks associated with the success of this technology.”
The clearest, and one that offers us a historical perspective of this paradigm, is Jeremy Grantham, from GMO. He compares the current situation with the 2008 financial crisis and the bubble dotcom. He also warns that this is similar to what happened with Cisco in the late 90s, when the company lent money to startups to buy its routersrecording these sales as revenue. When the bubble burst, Cisco lost 78% of its value.
The dangerous circularity
OpenAI is the epicenter of this interdependent financial scheme. At the moment, maintains infrastructure purchase commitments exceeding one billion dollars (trillion Anglo-Saxons), distributed among Oracle (300 billion), Microsoft Azure (250 thousand), Nvidia (100 thousand), AMD (90 thousand), AWS (38 thousand) and CoreWeave (22.4 thousand).
First example of dangerous circularity: Nvidia agreed to invest up to 100 billion in OpenAI to finance the construction of data centers. Sam Altman, in turn, promised to use this capital to buy millions of Nvidia chips and deploy at least 10 gigawatts of infrastructure based on Nvidia technology.
In turn, Oracle signed a 300 billion contract with OpenAI to provide cloud computing services for five years, starting in 2027. If we take into account that the outstanding obligations of Larry Ellison’s multinational amount to 455 billion, this means that 66% of your future order book depends on the good performance of ChatGPT. At the same time, Oracle uses this revenue to purchase Nvidia chips, which in turn power the infrastructure used by OpenAI.
Microsoft’s situation is even clearer: Satya Nadella’s team invested 13 billion in OpenAI (holds 27% of the company, valued at 135 billion). On the way back, OpenAI committed to buying 250 billion in Azure services from Microsoft.
AMD, Nvidia’s great rival, also knows this steering wheel. The chip giant granted OpenAI the option to acquire up to 160 million shares (about 10% of the company) in exchange for OpenAI commits to deploying 6 gigawatts of AMD GPUs. We are talking about approximately 90 billion potential revenues. The deal is as circular as all the previous ones: AMD provides funding to OpenAI, which then uses those funds to buy its silicon.
And, closing the most immediate circle, CoreWeave. This AI infrastructure provider is more than 5% owned by Nvidia, but at the same time holds contracts worth $22.4 billion with OpenAI. Supported by this demand, it is purchasing 6.3 billion chips from Nvidia, which has also committed to purchasing any remaining residual capacity from this supplier. The scheme is harmless: the money comes in and goes out through the same pocket.
But don’t think that this financial practice is exclusive to Altman and his acolytes. Anthropic -one of OpenAI’s biggest rivals- received an investment of US$3 billion from Google and another US$8 billion from Amazon in exchange for a commitment to use one million TPU chips from the search giant and another million Trainium chips from AWS. Call it a coincidence, call it whatever you prefer.
Elon MuskOf course, I had to attend this party. Its despised OpenAI alternative, xAI, raised $20 billion in a funding round in which Nvidia contributed a tenth. And the compensation, what a surprise!, is the purchase of Nvidia chips worth 18 billion.
Debts and more debts
It’s clear at this point that the money never leaves the pockets of the technology providers who fund the AI players who, in turn, buy their infrastructure to train and run their models. But any avid reader will be wondering where all that money comes from.
The answer is as obvious as it is alarming due to its systemic risk: debt.
Meta, Google, Microsoft, and Amazon alone spent about $200 billion on AI infrastructure in 2025. As if that seemed like a small amount, Google revised its capital spending forecast for 2025 from $75 billion to $93 billion. Microsoft expects its investment in this plot to increase 74%, to 34.9 billion this year. And Meta adjusted its spending forecast to a minimum of 70 billion by the end of the year.
Bank of America immediately warned that 75,000 million in debt of US investment grade tied to AI-focused technology companies occurred in just two months, September and October 2025, more than double the annual industry average of 32 billion between 2015 and 2024. This includes debt issues of 30,000 million by Meta and another 18,000 million by Oracle.
It is not the only bank to show signs that something is not right. UBS estimates that the AI-related private credit loans may have nearly doubled in the last twelve months. Meanwhile, Morgan Stanley predicts that debt markets could account for more than half of the $1.5 trillion needed for data center expansion by 2028.
The essential question is not whether AI is disruptive – it is, and at an excellent level – but whether the way we finance its implementation is sustainable. Companies that incorporate the latest in artificial intelligence They are simultaneously erecting their own pedestal and the trap that hides beneath it.. Circularity has become the new structural obstacle: I invest in you so that you buy from me, and thus, like a financial palimpsest that rewrites itself without completely erasing what came before, capital is recycled in a closed cycle that does not always create new value, but rather redistributes the existing one, like an accounting twist worthy of a financial engineering compendium.
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