A key red flag in the AI sector is circular financing, where a company like NVIDIA invests in a startup that then uses the funds to purchase NVIDIA's products. This creates a closed loop that can artificially inflate revenue and demand metrics, a tactic reminiscent of the dot-com bubble.

AI companies are selling large, seat-based contracts based on hype and experimental budgets, inflating current ARR. Investors are skeptical because, like early SaaS, customers will eventually demand usage-based or outcome-based pricing, challenging the long-term revenue stability of these startups.

The AI ecosystem appears to have circular cash flows. For example, Microsoft invests billions in OpenAI, which then uses that money to pay Microsoft for compute services. This creates revenue for Microsoft while funding OpenAI, but it raises investor concerns about how much organic, external demand truly exists for these costly services.

Analysts distinguish between initial revenue from training large language models (LLMs) and more sustainable, long-term revenue from 'inference'—the actual use of AI applications by end-market companies. The latter, like a bank using an AI chatbot, signals true market adoption and is considered the more valuable, 'sticky' revenue base.

Hedge fund manager David Einhorn highlights the unstable economics of the AI supply chain, where money flows circularly with diminishing returns. For every $1 a consumer pays OpenAI, OpenAI spends $2 on Microsoft, which spends $0.60 on CoreWeave, which then spends $2.40 on NVIDIA. This questions the long-term profitability and sustainability of the entire ecosystem as currently structured.

Profits from AI infrastructure (e.g., NVIDIA chips) can be misleading. The customer's purchase may be funded by a venture investment from the seller itself, making the revenue less recurring than it appears and complicating traditional valuation methods.

Revenue figures for AI companies can be misleading. The same dollar is often counted multiple times as it moves from the end customer through a SaaS provider and a cloud platform before reaching the model provider, creating a "margin stacking" effect that obscures the true net revenue.

Large tech firms invest in AI startups who then agree to spend that money on the investor's services. This creates a "circular" flow of cash that boosts the startup's perceived revenue and the tech giant's AI-related sales, creating questionable accounting.

Unlike sham transactions that invent revenue, investments like Nvidia's into its GPU customers are economically sound. The deciding factor is the massive, verifiable downstream demand for the AI tokens these GPUs produce. This makes the deals a form of strategic credit extension, not fraudulent accounting.