Nvidia's CEO Jensen Huang delivered a bombshell forecast that caught Wall Street off guard: the company expects 70% revenue growth in fiscal 2028, wildly exceeding the 44% analyst consensus. The projection, announced during the company's second-quarter earnings call, sent Nvidia's stock rallying more than 4% in after-hours trading and signals that the artificial intelligence infrastructure buildout is accelerating far faster than most investors anticipated.

The 70% guidance is particularly remarkable because Nvidia rarely provides forecasts more than one quarter ahead. "We've never forecasted, never guided to a year in advance," Huang explained on the call. The company broke its own precedent because Huang has visibility into next year's computing needs now, and he wanted to ensure all partners in the AI infrastructure ecosystem had consistent information.

Based on current analyst projections for fiscal 2027 revenue of roughly $396 billion to $570 billion, the 70% growth rate would push Nvidia's fiscal 2028 revenue to somewhere between $673 billion and $700 billion. That trajectory would position Nvidia as the second-largest U.S. technology company by revenue, behind only Amazon and ahead of Apple and Alphabet.

What's Driving This Explosive Growth?

The surge in demand reflects a fundamental shift in how artificial intelligence systems consume computing power. Huang explained that agentic AI, which refers to autonomous AI systems that can perform tasks independently, requires dramatically more compute than traditional AI interactions with human users. "The amount of compute an AI agent gobbles up versus a human user is about 15 to 100 times greater, depending on the type of task or problem being solved," Huang said.

Huang

This shift matters because businesses are planning to deploy far more AI agents in the future. Huang used Nvidia itself as an example: "We have 40,000 employees, roughly. In the future, we'll have 400,000 agents, 4 million agents, and those agents are running continuously." As companies across industries adopt this model, the demand for Nvidia's chips will continue to multiply.

Equally important, demand is no longer concentrated among a handful of hyperscale cloud providers like OpenAI, Google, and Meta. A year ago, Huang noted, "one lab alone was driving the buildout." Today, the customer base has diversified dramatically. Nvidia now serves what it calls ACIE customers, which includes regional AI companies, neo-clouds, AI startups, and enterprises. This segment represents about half of Nvidia's business and is growing at 100% annually.

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How Nvidia Is Addressing Supply Constraints and Financing Challenges

Despite the bullish demand picture, Nvidia faces real constraints that are preventing even faster growth. The company's entire supply chain is stretched thin, particularly for memory chips, which face a global shortage due to widespread AI infrastructure buildouts across the industry. "Our entire supply chain is challenged, and it's everybody; everybody is really running flat out," Huang said.

Huang emphasized that demand actually exceeds the company's 70% growth forecast. "Even though our demand is much greater than 70%, our supply allows us to confidently deliver 70%," he explained. Without these supply constraints, Nvidia's growth trajectory would be even steeper.

Huang

To manage these challenges and support customers who lack the financial track record to secure traditional loans for expensive AI infrastructure, Nvidia has implemented several strategies:

• Financing Partnerships: Nvidia partnered with six major financial firms, including Apollo, BlackRock, Blackstone, Goldman Sachs, and KKR, to mobilize over $500 billion in third-party capital for AI infrastructure buildouts over time.
• Guarantee Structures: For smaller AI-native cloud providers called neo-clouds, Nvidia guarantees it will pay for a minimum portion of a data center's capacity, which helps satisfy banks and enables financing. In exchange, Nvidia takes a cut of the provider's rental revenue above that threshold.
• Strategic Investments: Nvidia has invested nearly $50 billion in frontier AI labs and other partners, creating what some critics call "circular financing" because Nvidia's investments in these companies ultimately drive demand for Nvidia's chips.

Is Nvidia's "Circular Financing" Strategy Risky?

Nvidia's involvement in financing and investing in its own customers has drawn scrutiny from skeptics who worry about interdependencies and financial risk. The company disclosed maximum gross guarantee exposure of $108.5 billion, mostly stemming from credit support for SB Energy's Ohio tech campus, which will host Nvidia compute leased to OpenAI.

"We recognize the scale of this support, and we know some will call this circular financing. We see it differently," said Colette Kress, Nvidia's chief financial officer.

Colette Kress, Chief Financial Officer at Nvidia

Kress defended the strategy by arguing that Nvidia's investments in frontier AI labs are low-risk, high-reward bets. She noted that these labs have proven technology, strong customer traction, and "skyrocketing" usage. "We expect them to become the largest technology companies in history," Kress said. Their growth "isn't limited by their technology or customer demand. It's limited by compute".

She added that demand from AI labs will contribute to about a quarter of Nvidia's business next year, and that Nvidia's platform is "fungible and durable," meaning it can be repurposed for other customers if a partner's needs change. The company also emphasized that independent capital still underwrites every deal on its own merits, and that Nvidia gets paid twice: once on hardware sales and again through revenue sharing.

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However, markets have shown some skepticism. When reports surfaced in July that Nvidia was in talks to guarantee as much as $250 billion in capacity for OpenAI, credit markets repriced Nvidia's five-year risk significantly higher, and the stock shed $250 billion in value. Even though the final number came in lower at $105 billion, the market interpreted the news as a sign of increased financial risk rather than reduced demand.

What Do the Latest Earnings Numbers Show?

Nvidia's second-quarter results provided the foundation for the company's bullish forward guidance. The company reported revenue of $96.2 billion, up 106% from a year earlier and sailing past analyst expectations of $92.2 billion. Earnings per share came in at $2.22 on a non-GAAP basis, above the $2.06 to $2.09 expected.

Data center revenue, which represents the vast majority of Nvidia's business, reached $89 billion, up 117% year-over-year. The company guided for third-quarter revenue of $108 billion, plus or minus 2%, matching the so-called "buyside whisper range" that sophisticated investors had been anticipating.

Gross margins remained resilient at 75%, though the company guided for a slight decline to 74% in the third quarter. This is actually better than the 72.6% that analysts had been modeling, suggesting Nvidia's pricing power remains strong despite rising memory costs.

"AI has reached its inflection point. It's doing useful work. Its tokens are productive and profitable. Now, compute is revenue. And demand is accelerating," said Jensen Huang, founder and CEO of Nvidia.

Jensen Huang, Founder and CEO at Nvidia

Huang's statement captures the fundamental shift underway in the AI industry. For years, artificial intelligence was viewed as a research project or a long-term bet. Today, AI systems are generating measurable business value, and companies are willing to spend billions on the computing infrastructure needed to power them. Nvidia, as the dominant supplier of the chips that make this possible, sits at the center of this transformation.

The company also announced the Vera Rubin platform, which is ramping into full production with racks running at partners including CoreWeave, Google Cloud, Microsoft Azure, Oracle Cloud Infrastructure, and Nebius. This new platform is designed specifically for the moment Huang described, where AI infrastructure buildouts are at "full steam".

Nvidia returned approximately $26 billion to shareholders in the second quarter through stock buybacks and dividends, and the company has $99 billion remaining under its share repurchase authorization. This capital return program underscores management's confidence in the company's ability to generate enormous cash flows even as it invests heavily in partnerships and infrastructure.

The 70% growth forecast represents a watershed moment for Nvidia and the broader AI industry. It signals that the infrastructure buildout is not a temporary phenomenon driven by a handful of companies, but rather a multi-year transformation that will touch virtually every sector of the economy. For investors and industry observers, the question is no longer whether AI will drive massive computing demand, but how quickly companies can scale to meet it.