🤖 AI Summary
Harvard economist Jason Furman calculated that U.S. GDP growth in H1 2025 was almost entirely driven by investment in data centers and information-processing technology—without those categories, annualized growth would have been only 0.1%. Technically, information‑processing equipment and software made up about 4% of GDP but accounted for roughly 92% of GDP growth over the period. Analysts echoing Furman note an unprecedented hyperscaler buildout: capex on data center and related items has risen roughly fourfold and is approaching $400 billion annually, with the top 10 spenders making up nearly a third of that outlay. Renaissance Macro even estimated that AI data‑center buildout had contributed more to GDP than U.S. consumer spending so far in 2025.
For the AI/ML community this underlines two big implications: first, demand for massive compute, storage and networking is now a macroeconomic growth engine—fueling investment in hardware, software, and power infrastructure—and second, it concentrates economic risk. The surge bolsters chipmakers, cloud providers and data‑center ecosystems (Microsoft, Google, Amazon, Meta, Nvidia), but raises questions about sustainability, regional power grids, and market distortions if spending slows. Furman and others also note offsetting effects (lower rates, cheaper electricity) could recapture some growth, but the broader picture is clear: AI compute investment is reshaping macro outcomes and policy debates.
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