Capital expenditures on artificial intelligence infrastructure are cementing their role as the primary macroeconomic engine of the United States. On November 12, 2026, Goldman Sachs analysts projected that annual spending on AI hardware and intellectual property will surpass $900 billion by the end of 2026 and climb to roughly $1.4 trillion by late 2027.
According to the investment bank’s estimates, this capital outlay will correspond to nearly 4% of the entire US economy. The bulk of liquidity is flowing into semiconductors, compute clusters, and data center power grids. While sustaining massive hardware demand, this scale introduces systemic macro risk: if enterprise software monetization fails to generate commensurate ROI, the market faces a severe valuation correction.
Sources: Reuters | The Independent
4% of US Economy: Goldman Sachs Projects AI Spending to Hit $1.4 Trillion by Late 2027
