Nvidia Corp (NASDAQ: NVDA) reported a record second-quarter performance, with revenue surging 106% to $96.2 billion and net profit more than doubling to $59.7 billion. Despite the strong operational results, market observers are raising concerns about the sustainability of the underlying financing structures supporting this growth.

Howard W. French, former New York Times Tokyo bureau chief, argues in a Foreign Policy column that the financial ecosystem forming around Nvidia increasingly mirrors corporate Japan in the late 1980s. His analysis suggests that while the technology is real, the capital allocation patterns carry significant risk.

The Financing Structure

French notes that the S&P 500 trades at approximately 23 times expected earnings, roughly one-third of the multiple seen in Tokyo in December 1989. His primary concern lies not with Nvidia’s valuation but with its deepening entanglement with customers through complex financing arrangements.

In August, Nvidia signed preliminary agreements to mobilize more than $500 billion in third-party financing for AI infrastructure. Additionally, the company agreed to guarantee up to $105 billion in lease and power payments for OpenAI’s 4.25-gigawatt data-center project in Ohio.

Separately, Nvidia has committed $36 billion under cloud-service agreements with AI providers. The company warned it may be required to purchase capacity that these providers cannot sell, effectively placing Nvidia on both sides of the boom: selling hardware while simultaneously financing the demand for it.

Parallels With 1980s Japan

French draws parallels to Japan’s late-1980s corporate system, where major industrial groups owned stakes in one another and financed each other’s expansion. Capital flowed based on relationships rather than cash flow, often continuing even as markets weakened.

He observes that Nvidia is entering a similar web by supplying AI companies while investing in them and financing their expansion. This occurs even as profits from AI services have yet to match the enormous infrastructure spending.

Japan’s technological dominance was substantial; its companies controlled about 80% of global DRAM production in the 1980s. However, the bubble still burst, and the Nikkei did not regain its 1989 peak until February 2024, more than 34 years later.

What the Numbers Show

The divergence between Nvidia’s operational profitability and its balance sheet exposure highlights a structural shift. While net profit doubled to $59.7 billion on $96.2 billion in revenue, the company’s commitment to guarantee up to $105 billion for a single customer’s power and lease obligations represents nearly 18% of its annualized revenue run rate. This concentration of off-balance-sheet risk alongside direct cloud commitments of $36 billion indicates that Nvidia’s future earnings stability is increasingly tied to the creditworthiness and monetization success of its clients, rather than solely its own sales execution.

French also points to cheaper Chinese open models as a potential threat to AI service economics, which could drive down returns just as Nvidia finances ever more expensive infrastructure.

Market Sentiment

Despite these warnings, prediction markets remain bullish. Polymarket traders assign Nvidia a 76% chance of ending 2026 as the world’s largest company. Apple Inc (NASDAQ: AAPL) holds a 14% probability, while Alphabet Inc (NASDAQ: GOOGL) stands at 9%.

French concedes his analogy is imperfect but maintains that Japan’s experience demonstrates that technological dominance and excessive capital spending are not mutually exclusive. The core risk remains that as Nvidia helps finance demand for its own chips, it becomes more exposed if customers struggle to generate returns on that spending.

Nvidia Corp (NASDAQ: NVDA) CEO Jensen Huang defended the expansion of artificial intelligence data centers in the United States, arguing that the infrastructure boom is reviving domestic manufacturing and strengthening the power grid.

Huang made the comments over the weekend, pushing back against growing criticism regarding the environmental and economic impact of these facilities. He aligned his view with investor Gavin Baker, stating that modern data centers increasingly utilize closed-loop water systems and generate significant tax revenue.

AI as an Industrial Driver

Huang characterized the sector's growth as a catalyst for broader economic transformation. He noted that $400 billion has been invested in AI startups in the past six months alone. According to Huang, this demand is driving investment in sustainable energy infrastructure and is "powered by market forces, not subsidies."

He emphasized that builders must partner with local communities to earn trust and create tangible local benefits. Huang framed the initiative as an opportunity for America to lead the next industrial revolution after decades of offshoring.

Regulatory Pushback Intensifies

Despite these claims, regulatory resistance has grown in several states. A July study from Georgia Tech highlighted that while data centers generate economic benefits, those gains are not evenly distributed across communities.

Recent state-level actions include:

• New York: Governor Kathy Hochul imposed a pause of up to one year on new hyperscale data centers requiring at least 50 megawatts of power, citing grid strain.
• Texas: Governor Greg Abbott ordered a statewide audit of data centers amid concerns over power bills and water use.
• Michigan: Local officials in Saline Township initially rejected a proposed $16 billion OpenAI-Oracle Corp facility, though the project eventually moved forward.

President Donald Trump criticized New York's moratorium as a "terrible decision," warning that jobs and investment could shift to more welcoming states. He suggested the industry needs public relations assistance to balance community costs and benefits.

Market Reaction

Nvidia shares closed at $217.55, down 4.57%. In Monday's premarket trading, the stock was up 0.55% at $218.75. Benzinga Edge Rankings place Nvidia in the 98th percentile for Growth, with positive price-trend ratings across short, medium, and long-term horizons.