At Goldman Sachs’ Communicopia + Technology conference on September 10, 2026, Nvidia CEO Jensen Huang laid out why he anticipates the company will grow revenue by a staggering 70% in the coming fiscal year.
What’s Driving the Upswing
Huang emphasized that Nvidia is deeply embedded across the AI ecosystem. He said the company isn’t just a chipmaker—but a foundational platform for AI, used by hyperscalers like Amazon, Microsoft, and Google, AI labs like OpenAI and Anthropic, open-weight models, and a growing number of cloud and AI-native startups. All of these organizations, according to Huang, depend on Nvidia’s hardware and software stack. Meanwhile, competition—from major cloud providers to startup chipmakers—hasn’t slowed Nvidia’s momentum.
A key product fueling this momentum: a system that integrates 36 Nvidia “Grace” CPUs with 72 “Blackwell” GPUs. Huang revealed that sales of this system are rising 27% month over month. He also noted the company is tracking everything from data center shell construction to power capacity globally—placing Nvidia in a unique position to see demand trends before they fully play out.
70% Growth, $400 to $680 Billion
When Nvidia reported its recent record-breaking revenue, it issued guidance to grow about 70% year-over-year. The base figure is expected to hit roughly $400 billion this fiscal year—if the guidance holds, next year’s revenue could reach approximately $680 billion.
To support that projection, Nvidia points to its broad footprint: it claims to be connected with all parts of the AI value chain, from memory chip suppliers to cloud providers to AI-native firms. Huang also defended the company’s investment strategy—particularly investments in companies that end up purchasing Nvidia’s products. He asserted that any investment is tied to revenue commitments. One example he gave: Nvidia has committed around $100 billion in such contracts, ensuring returns and lowering risk.
Nvidia seems to know where everything is before it happens. The company is said to monitor data center shell construction globally—tracking land, power, and shell—and receives feedback from “neoclouds,” OEMs, and native AI firms. This gives it early visibility into infrastructure trends that support its dominant position.
Risks and Reality Checks
Still, Huang acknowledged that much of AI’s expansion is powered by resource-heavy startups burning through capital to run large models. As those models proliferate, efficiency pressures on compute infrastructure are likely to increase. Over time, firms will seek ways to reduce token usage and optimize infrastructure—as has happened with previous waves of technology scaling.
The company’s outlook hinges on continued demand across AI workloads, growing spending power among AI labs and data-intensive firms, and Nvidia maintaining its lead in both hardware and software integration. If any of those shift, the risk grows that competitors could catch up or that costs could squeeze margins.
What’s clear: Nvidia feels confident. Its current roadmap—and its presence from processors to AI labs to data centers—lays out a bold frame for what might become one of tech’s biggest revenue surges ever.
Why this matters: Nvidia’s projected growth underscores how central AI infrastructure has become to global tech strategies. It’s not just about chips—it’s about a company synchronizing its supply chain, customers, and investments to surf the AI wave. What to watch next: how competitors respond, whether margins hold under scale, and whether worldwide infrastructure investment keeps pace with Huang’s bullish vision.
