Monologue: Concentration Risk

**Ed Zitron** (0:02)
Causo Media Today in sentences that are not in the Bible, YouTuber Mark Plyer bought a major stake in camera maker GoPro, and then GoPro turned into an AI data center NeoCloud. I'm sick and tired of the goddamn AI bubble, I swear to Christ!
This is Better Offline, and I'm your host Ed Zitron. So today we're going to talk through a term you may or may not have heard before, Concentration Risk. It's a term that refers to having all your eggs in one or a few baskets, becoming overly reliant on a few investments, customers or particular business lines to the point that without them, your business or portfolio would suffer massive harms or just explode. In banking specifically, to quote the National Credit Union Administration, it refers to any single exposure or group of exposures with the potential to produce losses large enough relative to capital, total assets or overall risk level, to threaten a financial institution's health or ability to maintain its core operations.
I bring this all up because you're going to hear this term or variations of this term a lot in the next few months and years as the AI bubble unravels because just about every part of the industry involves its own flavor of concentration risk. Let's start at the top. Per data from fintech firm Ramp, 80% of open AI and Anthropics enterprise revenues come from 1% of their customers, a number that hasn't improved over the last three years. Ramp's lead economist Ara Karazian notes that the top 1% skews heavily towards the tech sector and AI products and services, and that this was a level of concentration risk unseen in any other software category they tracked. The data set, which includes big companies like Visa and Cursor, as well as a great deal of startups and regular sized companies, is very indicative of the overall spend of the AI industry, with the caveat that it doesn't include massive players like Microsoft or major banks. To be clear, I'm guessing about Visa and Cursor, any customer on Ramp can opt out of research, I have no idea, but I'm going to assume that there are big companies in there. I also want to be specific, that when Ramp says AI products and services, that includes AI startups that sell subscriptions with subsidized token spend, meaning that users can burn far more than their subscription price and tokens. So on a 20 buck a month subscription, you can burn 30, 40, 100 This means that the money made by Anthropica Open AI from an AI startup in that 1% spend is contingent on their continued ability to raise venture capital dollars. To similar all this down, it means that the vast majority of enterprises, which is where the real money is in software and the real growth is, just don't spend that much money on AI. Those that do spend the most on it are heavily concentrated in either AI companies that either use a lot of tokens internally because they're bankrolled by venture capital, AI companies that allow their users to blow unsustainable amounts of money on tokens, bankrolled by venture capital, tech companies that are currently under heavy pressure to spend money on AI tokens, and I assume a few whale customers of some sort. This means that 80% of OpenAI and Anthropics Enterprise revenues, which make up the vast majority of their total revenues, are dependent on what are likely hundreds of customers spending outsized amounts of money on AI tokens, with an indeterminately large chunk of them being AI startups that can only do so as long as venture capital allows them to. I also, and this is a gut feeling, wouldn't be surprised if the AI startup spend way more on tokens for writing LLM code internally considering how every time I see somebody going nuts on AI, on Twitter, it's usually a VC-backed startup. It also means, as I've hinted, that outside of the tech and AI world, very few companies are willing to pay very much for AI, which is catastrophic on just about every level, with no clear sign as to how you reverse that trend. AI has been in every media outlet and discussed in every boardroom and company for the last three years. Every single company has on some level dabbled in using AI. Most businesses have been given the green light to spend a bunch of money on AI, and in the end, it seems that the only people the tech industry can get to spend money on AI is the tech industry itself. This is open AI and Anthropic's underlying exposure, because these customers are also prime targets to move to either cheaper models that they train themselves because they're open source or eventually on device models. Even if these customers choose to stay with Anthropic and open AI, a chunk of this spend is contingent on venture capital funding, like I've said, and the rest is contingent on whether tech firms continue to be willing to spend money at scale. 80% of the revenue concentration depends on spending and capital that varies from unreliable to actively unstable. Meanwhile, these two AI labs represent a massive concentration risk for Microsoft, Google, Amazon, Oracle, CoreWeave, and anyone else that sells compute to them, with Anthropic and open AI sounding over $1.1 trillion worth of compute commitments based on demand that's mostly coming from a very small subset of customers. These are, from what I can tell, take or pay agreements where they agree to buy that compute capacity, regardless of how much capacity they actually end up using and how much revenue they actually bring in. As a reminder, both Anthropic and open AI are woefully unprofitable to lose tens of billions of dollars a year. To give you an idea of the concentration risk, open AI's compute spend and revenue share represent about 70 percent of Microsoft's AI revenues in fiscal year 26, which just ended in June, or a little over 70 percent of Microsoft's entire fiscal year revenue that year. And UBS estimates that open AI and Anthrobics compute spend will account for 48 percent of Google Cloud's entire revenues next year, or somewhere between 84 billion and 100 billion dollars in 2027 That's on top of, per Barclays, open AI and Anthrobics estimated 40 billion dollars spend on Amazon Web Services and at least 50 billion dollars that both of them will spend on Microsoft Azure in calendar year 2027, which I note because of Microsoft's odd fiscal year system. On the low end, that means that Anthropic and open AI account for over 174 billion dollars worth of expected revenues from Microsoft, Google and Amazon in 2027, which is contingent on their ability to raise venture capital or debt, which is contingent on the continued growth of their businesses, which is contingent on growing AI spend from a small subset of customers, many of whom are funded by venture capital.