Nvidia CEO Jensen Huang repeated his forecast that global AI infrastructure spending will hit $3 trillion to $4 trillion a year by 2030, the same call he made at the same conference a year earlier. The reaffirmation comes alongside fiscal Q2 2027 revenue of $96.2 billion and a memory chip shortage that Huang says is now the main limit on how much Nvidia can ship.
Jensen Huang has a number he likes, and he is sticking to it. At the Goldman Sachs Communacopia + Technology Conference on September 10, 2026, Nvidia's chief executive reaffirmed his forecast that global AI infrastructure spending will reach $3 trillion to $4 trillion annually by the end of the decade. He made the same call at the same conference a year earlier.
Revenue and pricing back up the call
Nvidia reported fiscal Q2 2027 revenue of $96.2 billion, up 106% year-over-year, with $89 billion of that coming from data center operations. Huang attributed part of the acceleration to the death of Moore's Law, the historical doubling of transistor density every couple of years, which has stalled and pushed companies to buy more specialized hardware rather than wait for the next generation of chips.
Supply, however, is not keeping pace with demand. Huang flagged memory chip availability as the primary bottleneck currently limiting how much product Nvidia can ship. On pricing, Hopper-generation GPUs run around $18,000 per unit, the newer Blackwell architecture costs roughly $25,000 per chip, and the forthcoming Vera Rubin platform is priced at approximately $40,000.
Hyperscalers keep raising their budgets
Hyperscalers are expected to increase combined capital expenditures from roughly $800 billion in 2026 to approximately $1.3 trillion in 2027, a jump of around 60%. Nvidia has also partnered with major financial firms to help funnel more than $500 billion into AI data center projects.
For fiscal 2028, Nvidia projects revenue growth of around 70%, versus an analyst consensus closer to 45%.
A shortage that could reshape the supply chain
The supply chain constraints Huang identified create a secondary investment thesis within semiconductors. Companies producing high-bandwidth memory and advanced packaging stand to benefit as the bottleneck attracts capital, and the shortage also gives competing chip architectures a window to gain ground with hyperscalers looking to diversify their suppliers.
Source: Crypto Briefing
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