On Friday, market commentator The Kobeissi Letter shared an estimate stating AI services could account for 8.8% of U.S. gross domestic product by 2032, potentially generating $3.5 trillion in annual revenue for AI companies.
AI Spending Could Rival Food Spending
In a post on X, The Kobeissi Letter compared the projected spending with other major categories of the U.S. economy, including food, energy, construction and healthcare.
The estimate puts AI services spending close to U.S. consumer spending on food, which accounts for 9.1% of GDP. Energy spending represents 5.1%, while construction and computers and software each account for 4.4%, according to the post.
The commentator also compared the projected AI spending share with defense at 2.8% of GDP and communications and internet at 1.2%. Healthcare remains the largest category in the comparison, accounting for 18% of GDP.
AI Infrastructure Spending Also Expands
U.S. hyperscalers could spend $916 billion on capital expenditures over the next 12 months, with spending projected to rise to nearly $1.2 trillion in the following year, according to estimates compiled by Apollo Global Management chief economist Torsten Slok.
Data-center capital expenditure could reach roughly 3.1% of U.S. GDP in 2027, compared with a peak of 1.2% for telecom investment during the dot-com boom.
Separately, estimates from UBP put five major hyperscalers’ capital expenditure at roughly $820 billion in 2026, compared with about $750 billion in operating cash flow. Their projected 2027 spending ranges from $1 trillion to $1.3 trillion, potentially creating a financing gap.
Last month, Matt Garman, CEO of Amazon.com Inc.‘s (NASDAQ: AMZN) AWS said customers are seeing positive business returns from AI at current capabilities and costs, adding that he felt good about the company’s spending.
During the same time, investor Ray Dalio warned that rising AI-related borrowing and interest rates could increase the risk of a market downturn.
Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors.
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