Tesla and SpaceX CEO Elon Musk said artificial intelligence could nearly double US economic growth next year, taking GDP growth from around 2% to 4%. Musk shared the prediction on X on September 18, adding that growth could be even higher.
“My guess is that AI roughly doubles US GDP growth next year from ~2% to ~4%. Maybe even more,” Musk wrote.
Musk did not disclose the assumptions behind his estimate or explain how he measured the projected growth. His forecast comes as businesses and investors examine whether heavy spending on AI infrastructure can translate into broader productivity gains.
Musk’s 4% estimate sits above the latest US Federal Reserve projection. Fed officials expect real GDP to grow at a median rate of 2.4% in 2027, with individual forecasts ranging from 2% to 2.9%. The Federal Reserve expects growth of 2.3% in 2026.
The US economy expanded at an annualized rate of 1.5% in the second quarter of 2026, down from 2.1% in the first quarter, according to the Bureau of Economic Analysis.
Musk previously projected a much larger economic impact from AI and automation. Earlier in September, he estimated that AI could expand the global economy by 20% to 30%, equivalent to USD 20 trillion to USD 30 trillion in additional annual output.
Musk’s latest forecast comes as the AI investment cycle faces higher borrowing costs and questions over how quickly companies can generate returns from large infrastructure spending.
A recent report from brokerage firm Dolat Capital said major cloud companies are moving from relatively asset-light business models towards large-scale capital expenditure on AI infrastructure. Companies are financing this spending through internal cash flows, debt and equity.
“The AI capex cycle is therefore entering its first meaningful macro test, with a more hawkish central-bank stance raising the funding hurdle for an investment cycle already demanding substantial capital,” the brokerage said.
The brokerage also identified AI monetization as a key unresolved issue. Falling token costs, improving model efficiency and rapid advances in technology could affect the pace at which companies recover their AI investments.
“The key risk is not demand for AI, but whether incremental investment continues to generate sufficient returns to sustain the current pace of spending,” Dolat Capital said.
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The AI infrastructure buildout also faces pressure from higher borrowing costs. Dolat Capital pointed to rising bond yields, US government borrowing, monetary policy normalization in Japan and increased infrastructure and defense spending as factors affecting the global cost of capital.
The brokerage also cited about USD 8 trillion in US Treasury securities requiring refinancing. The next phase of the AI investment cycle could therefore depend on the pace of AI monetization, hyperscaler spending, and the direction of interest rates.