Nvidia Forecasts AI Infrastructure Spending to Reach $4 Trillion
Nvidia CEO Jensen Huang expects global AI capital expenditures to reach between $3 trillion and $4 trillion by the end of the decade. CFO Colette Kress asserts that AI has transitioned from a "nice-to-have" to a necessity, noting that latest systems are reducing costs and increasing value for customers as AI tokens become more profitable. This growth comes amid significant infrastructure bottlenecks, with Nvidia demanding 20x more supply for critical components. The company is now pivoting toward "AI factories" that prioritize performance per watt and cost per token to support the scaling of agentic AI and autonomous enterprise agents.
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Nvidia’s rise from chipmaker to AI infrastructure powerhouse has transformed it into one of the world’s most valuable companies. Leading the financial operation behind that ascent is CFO Colette Kress, No. 49 on the 2026 Fortune Most Powerful Women list. Kress joined Nvidia in 2013.
AI spending expected to top $1 trillion in 2 years. That estimate's way too low if Jensen Huang's right
During Wednesday evening's earnings ... thought AI capital expenditures could get up to $4 trillion. "The capex is at a trillion dollars, and it's growing toward the three to four [trillion-dollar mark]," he said, speaking only of capex for hyperscalers like Alphabet and Amazon, which excludes other segments of the supercomputing market such as neoclouds. Nvidia's chief financial officer Colette Kress was even more ...
According to Huang, however, AI has advanced and is now more efficient. Image source: Getty Images. Not only are tokens more efficient, but Nvidia's chips are also proving to be more valuable than previously expected, with the company's CFO, Colette Kress, saying that "customers are generating ...
Nvidia CEO: AI Crosses Critical Threshold, Tokens Now Profitable - NVIDIA (NASDAQ:NVDA) - Benzinga
For years, the concern was that serving AI models would remain too expensive, limiting adoption and weighing on profitability. Nvidia argues the opposite is happening. Earlier in the call, Nvidia CFO Colette Kress highlighted how the company’s latest systems continue to reduce the cost of ...
AI factories are token factories, converting power into intelligence in real time. And as agentic AI scales and autonomous, always-on special agents are deployed in the enterprise, performance per watt and cost per token become the economics that matter.
The AI boom has already burned through one shortage after another. First it was GPUs. Then high-bandwidth memory. Then power infrastructure, transformers, cooling systems, and even land near major electric grids. Yet as hyperscalers continue pouring hundreds of billions into AI data centers, ...
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