Circular AI Investment Schemes: The “Round-Trip” Revenue Controversy
The New Mechanics of Silicon Valley
In the high-stakes race for Artificial Intelligence dominance, a controversial financial pattern has emerged. It is known as circular AI investment, or “round-tripping.” The mechanism is surprisingly simple yet ethically complex: A massive tech hyperscaler (like Microsoft, Amazon, or Google) invests billions into a promising AI startup. In return, that startup commits to spending a significant portion of that capital renting cloud servers exclusively from the investor.
On paper, this looks like a strategic partnership. However, financial regulators and antitrust watchdogs are beginning to ask a critical question: Is this genuine growth, or is it accounting gymnastics designed to inflate cloud revenue?
This guide dissects the mechanics of these deals, the specific antitrust concerns raised by the FTC and SEC, and the potential long-term risks for the broader tech economy.
How Circular Investment Schemes Work
To understand the controversy, one must follow the money. In a traditional venture capital deal, money is invested for equity to fund product development, hiring, and operations across various vendors. In a circular scheme, the capital flow is more restrictive.
- Step 1: The Investment. A Cloud Hyperscaler (e.g., Cloud Corp) invests $4 billion into an AI Startup.
- Step 2: The Stipulation. The deal includes a “cloud credits” or exclusivity clause, requiring the startup to use Cloud Corp’s infrastructure for training their LLMs (Large Language Models).
- Step 3: The Return (Round-Trip). The startup pays the invested cash back to Cloud Corp as “cloud service fees.”
- Step 4: The Revenue Boost. Cloud Corp records these fees as top-line revenue growth for their cloud division, impressing shareholders and boosting stock prices.
This creates a closed loop where the same dollar is counted as an asset (investment) and subsequently as income (revenue), potentially distorting the true market demand for cloud services.
Major Players and High-Profile Deals
The consolidation of AI power is currently concentrated among three major cloud providers. Below is a breakdown of recent partnerships that have drawn scrutiny regarding vendor lock-in and circular funding dynamics.
| Hyperscaler (Investor) | AI Startup (Recipient) | Investment Scale | The “Cloud-Back” Dynamic |
|---|---|---|---|
| Microsoft | OpenAI | ~$13 Billion | Majority of funds act as credits for Azure cloud compute usage. |
| Amazon (AWS) | Anthropic | ~$4 Billion | Anthropic commits to using AWS as its primary cloud provider. |
| Anthropic | ~$2 Billion | Includes heavy usage of Google Cloud and TPU infrastructure. | |
| Microsoft | Inflection AI | $650 Million (Licensing) | Unique “acqui-hire” structure avoiding direct merger scrutiny while absorbing talent. |
Regulatory Oversight: The Antitrust Crackdown
The Federal Trade Commission (FTC), led by Lina Khan, alongside the UK’s Competition and Markets Authority (CMA) and the European Commission, have launched inquiries into these investments. The concerns fall into three primary buckets:
1. Revenue Inflation (The “Enron” Fear)
While nowhere near the fraud levels of Enron, the concept of round-tripping revenue is a red flag for the SEC. If a company invests money solely to convert it into revenue immediately, it paints a misleading picture of organic growth. This artificial inflation can mislead investors regarding the actual demand for cloud infrastructure.
2. Vendor Lock-In & Market Foreclosure
By forcing startups to use their cloud infrastructure exclusively, hyperscalers may be foreclosing the market to smaller cloud competitors or independent data centers. This stifles innovation in the infrastructure layer, as startups cannot shop around for cheaper or more efficient compute power.
3. The “Pseudo-Merger”
Regulators are concerned that these massive investments give Big Tech controlling stakes in startups without going through standard merger reviews. The Microsoft-Inflection deal, for example, involved hiring the staff and licensing the software without buying the company entity, a move widely seen as a strategy to bypass antitrust blocks.
The Economic Risk: An AI Bubble?
The circular nature of these investments creates a valuation echo chamber. If the revenue of AI startups is primarily derived from funding provided by their service providers, the ecosystem lacks outside liquidity.
If the AI models do not eventually generate massive profits from enterprise customers (outside of the hyperscalers), the cash flow stops. The startups won’t be able to pay their cloud bills, and the hyperscalers will face a sudden contraction in cloud revenue—a “correction” that could ripple through the entire tech sector.