NVIDIA—the "central bank" of the AI industry
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In the AI era, Nvidia is no longer just a chip-selling company, but is transforming into a "central bank-like" presence that controls capital flows, influences technological directions, and stabilizes the industry ecosystem.
On September 27, tech media The Information published an in-depth report that analyzed in detail the unique role Nvidia and its CEO Jensen Huang play in the AI economy, revealing how Nvidia, through large-scale investments and strategic planning, is gradually becoming a "government-like" entity in the AI field.
Through in-depth research and interviews with numerous industry insiders, including Nvidia executives and informed sources, the article shows how this chip giant uses its massive cash flow to shape the entire AI ecosystem. The report points out that Nvidia’s investment strategy has already gone beyond the scope of traditional business cooperation and has begun to take on characteristics similar to government regulation of the economy.
The article believes that Nvidia's investment scale and coverage have reached unprecedented levels. From data center construction to AI model development, from incubating startups to large-scale project financing, Nvidia’s reach extends to almost every corner of the AI industry. This all-encompassing participation gives it a "central bank"-like status and influence in the AI economy.
The article particularly emphasizes the driving factor behind Nvidia's investment frenzy—the deep fear that future technological breakthroughs might bypass its chips. This concern has led the company to adopt a more aggressive investment strategy, attempting to use capital power to consolidate its core position in the AI ecosystem.
The "Government" Role in the AI Economy
At the start, the article mentions Jensen Huang’s dazzling investments, such as Nvidia’s commitment to invest up to $100 billion in OpenAI in the past few months, acquiring the technology and talent of several startups, and even extending an olive branch to competitor Intel. All these actions point to a key idea: Nvidia is becoming the "de facto government" of the artificial intelligence sector.
According to the article, in September alone, Nvidia completed several major investments: it agreed to purchase all unsold GPUs from cloud service provider CoreWeave over the next seven years, a deal that may cost about $6.3 billion.
In addition, Nvidia invested $700 million in UK data center startup Nscale, spent over $900 million to hire the CEO and engineers of networking startup Enfabrica and secure its technology licensing, and purchased a 4% stake in struggling chipmaker Intel, worth $5 billion.
Most notably this week, Nvidia expressed an intent to invest up to $100 billion in OpenAI over the next few years.
As part of the cooperation between the two companies, the AI startup will use this investment to build an AI data center consuming at least 10 gigawatts of power, equivalent to 4 to 5 million Nvidia GPUs—about Nvidia's total planned GPU shipments for all of 2025. As Jensen Huang said this week on CNBC: "This is a huge project."
Nvidia’s investments have become so huge and extensive, covering data centers, model development, and many other categories and companies, that it is starting to play the role of a “government” in the AI field. This metaphor is not an exaggeration, but a true portrayal of its influence in the AI ecosystem.
The amount of money Nvidia injects into AI companies such as OpenAI is already close to the scale of a government stimulus program.
As the biggest beneficiary, Nvidia gains enormous returns from the booming AI economy because its GPUs are core to training and running the most advanced large language models. Nvidia's funding of AI startups helps them pay for GPUs, which effectively brings part of the cash flow back to the company in the form of chip sales.
Harvard Business School professor David Yoffie commented:
"They are working hard to stimulate demand for their products, which is a completely valid strategic direction. On the other hand, the scale of this investment, and the fact that it targets just one customer, raises a question—are they stimulating artificial demand, which cannot be sustained in the long term and could produce severe negative returns in the future?"
A New Role as the “Central Bank” of AI
Meanwhile, these investment behaviors have also brought Nvidia massive "soft power".
For example, Jensen Huang maintains excellent relationships with senior government officials in multiple countries. When Nvidia announced a series of investments in the UK, the British Prime Minister publicly endorsed the company, which undoubtedly helped ease previously tense regulatory relations caused by the failed Arm acquisition. This sort of influence has gone beyond the business realm and has taken on a quasi-political flavor.
The report, citing two insiders, uncovered a behind-the-scenes story:
Recently, some large data center builders encountered difficulties in project financing, as traditional financial institutions became more cautious. At this critical moment, Nvidia stepped in.
The article directly quotes the source’s perspective: "Nvidia is willing to step in and provide financing support for data center companies, which helps attract other project backers to join." In other words, Nvidia’s intervention is like a central bank injecting liquidity into the market, taking on the role of "lender of last resort".
Its credit endorsement and financial support greatly reduce the risk for other investors and activates the entire financing chain.
Although this behavior is to secure future GPU sales for itself, it objectively plays a role in stabilizing market confidence and ensuring AI infrastructure construction does not stall. This is exactly the key role that a central bank plays in the financial system—to prevent systemic risk.
The Frenzied Spending: Fear and Huge Cash Reserves
What drives Nvidia to invest on such a massive, cost-ignoring scale? The article believes there are two main driving forces: huge cash reserves and deep existential fear.
First, Nvidia is simply "too rich".
According to estimates from S&P Global Market Intelligence, Nvidia’s free cash flow will reach $97 billion in fiscal year 2026 and $148 billion in fiscal year 2027. Just two years ago, in fiscal year 2024, Nvidia’s free cash flow was only $26.9 billion.
Due to regulatory restrictions, spending this money on large-scale acquisitions has become unusually difficult, making strategic investment the most logical way to use its massive cash reserves.
But a deeper reason is a persistent fear among the company’s upper management.
The article cites the views of two Nvidia executives, revealing a lingering “nightmare scenario” at the company: “What happens if a major breakthrough in AI emerges that doesn’t rely on Nvidia chips?”
In the view of some executives, that would mark the beginning of the end for the company. They are especially worried that industry leaders like OpenAI might one day reach the milestone of “de-Nvidia-ification.”
The article points out that this fear drives Nvidia to do whatever it takes to tightly bind all key players in the ecosystem to its own wagon.
Artificially Manufactured Prosperity?
At the same time, the article also presents concerns and doubts about Nvidia’s strategy. Harvard Business School Professor David Yoffie raises a pointed question:
By investing on such a large scale in a single customer (such as OpenAI), is Nvidia stimulating real demand, or “artificial demand”?
He worries that this seller-driven boom may not be sustainable and could lead to serious negative returns in the future.
Yoffie further analyzes that Nvidia’s aggressive moves may force cloud giants such as Amazon and Google to accelerate their own chip development in order to break away from dependence on a single supplier.
"It’s like an ally that’s too powerful, making the king uneasy. Especially if OpenAI does provide cloud computing power to the outside world in the future using these resources, it will compete directly with Amazon and Google, making the relationship between Nvidia and its major customers more delicate."
To illustrate this, Yoffie cites the historical lesson of Intel’s decline. He notes that almost no one took Apple’s early self-developed chips seriously, but the company eventually displaced Intel’s position in Mac computers. This history is deeply imprinted in the tech industry’s memory.
He believes that Jensen Huang must abide by a saying from former Intel CEO Andy Grove—"Only the paranoid survive." This vigilance against potential disruptors is at the core of Nvidia’s strategy.
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