AI boosted US economy by basically zero in 2025, Goldman Sachs chief economist reveals

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Goldman Sachs chief economist Jan Hatzius says AI contributed basically zero to US GDP growth in 2025, despite hundreds of billions in investments. The reason: most AI infrastructure spending goes to imported components from Taiwan and Asia, with roughly 75% of data center costs spent overseas. This challenges narratives that AI investment is driving American economic expansion.

Goldman Sachs Chief Economist Challenges AI Investment Narrative

Despite massive corporate spending on AI, the technology contributed basically zero to US economy growth in 2025, according to Jan Hatzius, Goldman Sachs chief economist. Speaking with the Atlantic Council, Hatzius stated bluntly that "we don't actually view AI investment as strongly growth positive" and noted "there's been a lot of misreporting of the impact that AI investment had on GDP growth in 2025."

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The assessment directly contradicts earlier estimates suggesting AI accounted for anywhere from 35 percent to 92 percent of economic expansion last year.

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Source: TechSpot

Source: TechSpot

The reality stands in stark contrast to the narrative that AI investment is propping up America's economic performance. While the U.S. economy recorded 2.2 percent GDP growth in 2025, analyst Joseph Politano calculates that only 0.2 percent of that growth stemmed from AI investment.

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This minimal contribution reveals a significant gap between investor enthusiasm and measurable economic impact.

Imported AI Components Drive Spending Overseas

The core issue lies in where AI infrastructure spending actually flows. Roughly three-quarters of the investment in building an AI data center goes toward computing components, and the majority of that spending happens overseas.

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Hatzius explained that "a lot of the AI investment that we're seeing in the U.S. adds to Taiwanese GDP, and it adds to Korean GDP but not really that much to U.S. GDP."

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Source: Tom's Hardware

Source: Tom's Hardware

The five top U.S. tech companies are collectively expected to spend as much as $700 billion on AI infrastructure in 2026.

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Yet this massive capital expenditure primarily benefits manufacturing economies in Asia, particularly Taiwan, where companies like Nvidia source their semiconductors from TSMC. Federal Reserve Bank of Chicago President Austan Goolsbee reinforced this view, noting that AI "is buying imported goods, so we need to subtract that to get the overall GDP effect."

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AI Infrastructure Spending Accelerates Despite Profitability Concerns

The AI investment impact raises questions about sustainability when companies aren't generating returns. OpenAI, despite being the biggest capital-burning company in history, generated less than $20 billion in revenue for 2025.

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Meanwhile, estimates suggest capital expenditure on AI infrastructure could reach $600 billion by 2030 and up to $1.4 trillion by 2033.

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IDC research predicts AI infrastructure spending could hit $758 billion by 2029, up from $82 billion in the last full calendar quarter.

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J.P. Morgan claimed in November that AI needed to generate over $600 billion in revenue annually just to achieve a 10% return on the enormous expenditures.

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This mismatch between spending and returns fuels growing concerns about an AI market bubble.

Source: Inc.

Source: Inc.

Long-Term Productivity Gains Remain Uncertain

While current economic impact appears minimal, Goldman Sachs Research forecasted in 2023 that AI could begin having measurable impact on GDP growth and labor productivity in 2027.

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The bank estimates AI could increase U.S. productivity growth by 1.5 percentage points annually, assuming widespread adoption over a 10-year period.

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However, the path to those productivity gains remains unclear. Analysts at Morgan Stanley, JPMorgan Chase, and other major financial institutions have expressed similar skepticism about AI's near-term economic contribution.

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Tax advisor Joe Brusuelas noted that economic effects of AI are difficult to estimate, with everyone "trying to peer through the fog to understand what is driving growth."

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The gap between AI's long-term potential and its near-term economic impact highlights the need for businesses to balance AI investment with investments in workers and training that help employees use the technology effectively.

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