Story perspectives

U.S. AI Spending Could Hit $1.1 T, But Build-Out Faces Shortages

6/12/2026

Summary

Story summary

U.S. AI capital expenditures could reach $1.1 trillion in 2027, or $1.4 trillion in a bullish view.
Goldman Sachs says Q1 backlog for Google Cloud and AWS rose to $832 billion from $358 billion six months earlier.
Delayed data-center projects and shortages of memory, power and labor may limit the AI infrastructure build-out.
AI-infrastructure stock valuations have surged, creating volatility as the Nasdaq 100 fell 2 % and the S&P 500 dropped 1.6 % in the AI sell-off.

History

Historical Context

In March 2000 the Nasdaq Composite hit its all-time high of 5,048.62, marking the peak of the dot-com bubble that saw companies like Cisco Systems and Amazon.com lose up to 80-90 % of their market value. Today AI-infrastructure spending by Google Cloud, Amazon Web Services and Intel-backed projects is echoing that capital-intensive surge, prompting concerns of a similar correction.

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Story summary

U.S. AI capital expenditures could reach $1.1 trillion in 2027, or $1.4 trillion in a bullish view.
Goldman Sachs says Q1 backlog for Google Cloud and AWS rose to $832 billion from $358 billion six months earlier.
Delayed data-center projects and shortages of memory, power and labor may limit the AI infrastructure build-out.
AI-infrastructure stock valuations have surged, creating volatility as the Nasdaq 100 fell 2 % and the S&P 500 dropped 1.6 % in the AI sell-off.

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