Goldman Sachs says current levels of artificial intelligence investment remain manageable and well below past major technology cycles, even as expectations for long-term productivity gains continue to build.
In a note to clients, the bank said AI-related capital expenditure accounts for less than 1% of U.S. GDP — far smaller than the 2–5% seen during earlier transformative tech booms such as the dot-com era or electrification.
Goldman estimates AI-driven productivity could generate an $8 trillion present-discounted value in additional capital revenue for the U.S. economy, with potential outcomes ranging from $5 trillion to as high as $19 trillion. Those gains, the bank argues, would far exceed cumulative AI investment forecasts, even before considering cross-border profits, new profit pools, or breakthroughs toward artificial general intelligence (AGI).
The analysis comes amid market debate over whether soaring AI spending could overheat capex cycles or lead to a future bubble. Goldman’s view suggests that while valuations in the sector are elevated, the scale of investment remains proportionate to the long-term economic upside.
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Goldman’s analysis supports a bullish long-term outlook for AI-related equities, suggesting current spending levels pose little macro risk. The bank’s trillion-dollar productivity forecast could reinforce optimism in semiconductor, cloud, and infrastructure sectors.
Contrarian stuff from GS?
