A few weeks ago on This Week in Tech, Stacey Higginbotham, policy fellow at Consumer Reports, was discussing the wave of mega-investments flooding the AI space. Google's forty billion into Anthropic. Microsoft's thirteen billion into OpenAI. Anthropic's hundred billion commitment to Amazon Web Services. And she observed something that's been nagging at me: the money moves between companies but it doesn't really move. It circles. Microsoft invests in OpenAI, OpenAI commits to spending that money back on Microsoft Azure. Google puts forty billion into Anthropic, and Anthropic pre-commits to buying Google Cloud compute for years to come. The cash flows out and flows right back in. It's customer acquisition dressed as equity. But here's what I can't figure out: where's the scrutiny? Why isn't this pattern front and center in how we talk about AI funding? Why are we treating these announcements as straightforward investments when the money's essentially looping back to where it came from?
How the loop works
Microsoft's relationship with OpenAI is the prototype. In 2019, Microsoft made its first investment: a billion dollars. By 2023, that had grown to thirteen billion across multiple tranches. On the surface, it looks like traditional venture capital: Microsoft backs a promising company, takes a stake, hopes it pays off. But the structure reveals something different.
OpenAI didn't take that thirteen billion and diversify its infrastructure across cloud providers. Instead, it committed to spending most of that money on Microsoft Azure. When the most recent investment was announced in October 2025, OpenAI agreed to purchase two hundred and fifty billion dollars worth of Azure compute services through 2032. That's not a side deal. That's the core of the arrangement.
Microsoft invests billions. OpenAI commits to spending those billions, and then some, buying Microsoft's cloud services. The money Microsoft put in doesn't sit in OpenAI's bank account as capital. It flows directly back to Microsoft as revenue. From Microsoft's perspective, the investment secures a guaranteed customer for years. From OpenAI's perspective, the investment buys compute capacity it needs to train and run its models. But for anyone trying to evaluate whether OpenAI is actually financially healthy or just performing financial health for the market, the distinction matters enormously.
And the structure keeps shifting. On April 27, 2026, Microsoft and OpenAI announced yet another restructuring. Microsoft's license to OpenAI's intellectual property becomes non-exclusive. Revenue share payments from OpenAI to Microsoft are now subject to an undisclosed cap, though they continue through 2030. Microsoft stops paying revenue share to OpenAI altogether. The 250 billion Azure commitment stays intact. The trigger for this restructure was OpenAI's 50 billion deal with Amazon, announced in February, which expanded OpenAI's existing 38 billion AWS agreement by another 100 billion over eight years. That Amazon deal created legal peril under the original Microsoft exclusivity terms, so the contract had to be rewritten. The terms keep changing. Key numbers stay undisclosed. The compute commitments multiply.
The pattern spreads
The Microsoft-OpenAI template didn't stay isolated. By late 2025, the same structure had become the industry standard.
In November, Microsoft and Nvidia announced a combined five billion dollar investment in Anthropic. In return, Anthropic committed to purchasing thirty billion dollars in Azure compute capacity from Microsoft, plus contracting for up to one gigawatt of additional Nvidia capacity. Again: the money flows in, and flows right back out as pre-committed spending.
Then in April 2026, Google announced it would invest up to forty billion in Anthropic. The first ten billion arrives upfront at a three hundred and fifty billion dollar valuation. The remaining thirty billion is tied to performance milestones Anthropic hasn't yet hit. But simultaneously, Anthropic agreed to purchase one hundred billion dollars in compute from Amazon Web Services over ten years, and five gigawatts of compute from Google itself as part of this deal.
Amazon had made its own announcement weeks earlier: a twenty-five billion dollar investment in Anthropic, with conditional commitments up to thirty-three billion more. The numbers are staggering, but the structure is repetitive. Money announced as investment. Compute capacity pre-committed as obligation. The cash that leaves one company's treasury arrives at another's as guaranteed revenue.
Nvidia benefits from chip sales baked into these deals. Microsoft and Google and Amazon benefit from long-term cloud contracts. Anthropic and OpenAI benefit from secured compute access. Everyone wins on paper. But the question of who's actually funding whom, and at what real cost, becomes impossible to answer from the outside.
When investment announcements obscure purchasing commitments, the actual financial health of these companies becomes unknowable from the outside.
The transparency problem
What troubles me about these circular structures isn't that they're illegal or even necessarily deceptive. It's that they're opaque by design. When money moves in loops, when investment announcements obscure purchasing commitments, when valuations are tied to compute capacity that doesn't exist yet, when key terms keep getting renegotiated with critical numbers undisclosed, the actual financial health of these companies becomes unknowable from the outside. And that matters because we're building on top of these models.
Organizations everywhere are integrating Claude or ChatGPT into their infrastructure. They're making bets on which models will be available, affordable, and reliable in three years. They're staffing teams around these technologies. But they can't evaluate the stability of the companies providing them because the financial relationships are deliberately murky.
Are these companies genuinely viable, or are they performing viability for investors and the market? Will the pricing that makes their models attractive today hold in two years, or will subsidies evaporate once lock-in is complete? Can you trust that a model won't be deprioritized if a cloud provider decides it's more profitable to push its own?
These aren't paranoid questions. They're basic due diligence. And right now, I'm not sure we have good answers. That's something I want to understand better.
You can't make good strategy decisions on bad information. And right now, the information we have about AI infrastructure and funding is deliberately obscured by financial structures designed to look like one thing while functioning as another. The circular deals work. They secure compute, they lock in customers, they generate headlines that make everything look like it's thriving. But they also make it impossible to know whether we're investing in genuine breakthroughs or elaborate financial theater.
Organizations everywhere are building their content strategy, their product roadmaps, their infrastructure decisions on the assumption that these models will be here, affordable, and competitive in the years ahead. That assumption is only as good as our ability to understand the actual economics underneath. And right now, that visibility doesn't exist. So either we demand it, or we accept that we're building on foundations we don't actually understand.