Nvidia CEO Jensen Huang has rejected claims that the chipmaker's investments in AI and cloud firms amount to circular financing of its own chip demand. He argues the sums involved are immaterial next to the business they generate, even as regulators flag rising debt and private-credit use across the AI buildout.
Jensen Huang told the Goldman Sachs Communacopia and Technology Conference that Nvidia's investments are too small relative to the revenue they generate to support the circular financing theory. Critics argue Nvidia invests in an AI company or cloud provider, that company then buys Nvidia hardware, and the revenue flows back to Nvidia, blurring the line between an investment and a sale.
The deals fueling the debate
OpenAI and CoreWeave sit at the center of the discussion. In January, Nvidia put $2 billion into CoreWeave Class A shares at $87.20 each, alongside a plan to build more than five gigawatts of AI data center capacity with CoreWeave by 2030. OpenAI then announced a $110 billion funding round at a $730 billion pre-money valuation, with $30 billion coming from Nvidia, $30 billion from SoftBank and $50 billion from Amazon. On August 10, Nvidia joined Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR on a platform aiming to mobilize more than $500 billion in third-party AI infrastructure capital, a fundraising target rather than a direct Nvidia commitment.
Huang frames a GPU as a productive, revenue-generating asset rather than a one-time hardware sale. According to InvestingLive: "In AI, compute is revenue," he said, arguing that framing changes how the investment relationships should be read.
Customer concentration adds statistical weight
Nvidia's own SEC filings give the concern some grounding. Three direct customers accounted for 16%, 15% and 13% of the company's first-half fiscal 2027 revenue. In February, addressing earlier talk of a possible $100 billion OpenAI investment, Huang said it was never a commitment and that Nvidia would invest one step at a time.
The scrutiny extends beyond Nvidia. The IMF said in April that AI-related investments could face strain in a downturn, noting rising circular financing across the value chain, though it judged the financial-stability impact minor for now. The Bank for International Settlements warned on September 10 that growing reliance on debt and private credit to fund AI spending could contribute to a larger shock if returns disappoint.
S&P Global estimates the five largest hyperscalers could spend a combined $5.3 trillion in capital expenditure through 2030, and Stanford's 2026 AI Index puts Nvidia's share of global AI compute capacity above 60%.
What Nvidia's own cash returns show
The company returned $26 billion to shareholders in its fiscal second quarter alone, split between $20 billion in buybacks and $6 billion in dividends, the largest dividend payout in the company's history. Nvidia still has roughly $99 billion in remaining buyback authorization.
For now, the debate looks more reputational than financial for Nvidia specifically. But any sign that hyperscaler capital spending plans are slowing would likely reignite scrutiny of the exact financing structure Huang is defending.
Sources: InvestingLive, The Motley Fool
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