
Fink warned that AI is creating shortages in compute power, chips, memory, and electricity as companies race to build larger AI systems, driving U.S. infrastructure spending on semiconductor manufacturing, power generation, and data-center construction.
Instead of renting cloud capacity, companies may buy contracts guaranteeing future access to AI compute resources — such as GPU-hours, AI inference capacity, data center power allocations, or reserved cloud processing capacity — similar to how airlines lock in oil futures prices.
Goldman Sachs estimates global AI-related infrastructure spending could approach $1 trillion over the next several years, with Microsoft, Amazon, Alphabet, and Meta Platforms expected to spend $710 billion or more in combined capital expenditures this year alone on AI infrastructure.
The U.S. Energy Information Administration projects electricity demand from data centers could more than double by 2030, with Goldman Sachs estimating AI-related data centers may consume as much as 8% of total U.S. electricity demand by the end of the decade versus roughly 3% today.
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