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NewsMaterial3 min readDisconfirmAI Editorial

IMF Scenario Analysis: The Greatest Risk of AI Is Not Just Technical Failure, but Markets Running Out of Patience

At its October 2026 annual meeting, the International Monetary Fund (IMF) outlined three scenarios for AI investment, warning that in a pessimistic case, global growth could decline by 1.3 percentage points. The core mechanism is supply chain transmission risk driven by highly concentrated investment: cuts in capital expenditure by U.S. tech giants would impact Asian manufacturing exports. The article distinguishes between hyperscale cloud providers investing with their own cash and data center companies relying on external financing, citing IMF Managing Director Kristalina Georgieva’s assessment that the real danger lies in financial markets lacking the patience to match the actual timeline of technology diffusion.

2026-10-19 09:19 GMT+8

In October 2026, the International Monetary Fund (IMF) and the World Bank held their annual meetings in Bangkok, Thailand. The primary concern for finance ministers and central bank governors from around the world was artificial intelligence (AI) investment. The IMF warned that if the AI investment boom were to cool abruptly, the shock would not be limited to stock market investors; the real economies of both developed and developing countries would be affected.

The starting point of this warning is the high concentration of AI investment. According to estimates by economist Stijn Van Nieuwerburgh, the United States will invest more than $10 trillion in data centers and related infrastructure over the next seven years leading up to 2032, averaging about 3.6% of U.S. Gross Domestic Product (GDP) annually. If realized, this scale would exceed historical investments in railway networks, power grids, and internet infrastructure. The construction of AI data centers requires semiconductors, power equipment, cooling systems, building materials, land, and labor; therefore, AI investment has spread from specific technology companies to the manufacturing, construction, and energy sectors.

Concentration implies vulnerability. The IMF's pessimistic scenario shows that if AI companies' profitability falls short of expectations or technological progress is slower than anticipated, investor confidence could collapse, causing U.S. AI capital expenditure to plummet, Asian exports to slow down, and stock prices and the U.S. dollar to fall simultaneously—a chain reaction that could suppress global economic growth rates by as much as 1.3 percentage points in 2028. The transmission path is clear: when large U.S. tech companies cut back on data center investment, orders for semiconductors and servers decrease, hitting economies like South Korea and Taiwan, which rely heavily on AI-related exports, first. According to CEIC data, in September 2026, South Korea's exports grew by over 80% year-on-year, Taiwan's by over 60%, China's by over 30%, and Japan's by about 20%, all driven by demand for AI-related products.

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However, not all AI investment companies face equal risks. Archie Scheske, Chief Credit Officer at Moody's Ratings, pointed out that large cloud service providers like Google and Microsoft are expanding their AI investments while holding ample cash and strong cash flows. What is truly vulnerable are infrastructure companies that rely heavily on external borrowing. Signals have already appeared in the market this week: bonds related to AI cloud infrastructure company CoreWeave came under pressure, and two Australian data center companies postponed their initial public offering (IPO) plans citing market volatility. Distinguishing between expansion funded by own cash versus reliance on external financing is a boundary that must not be confused when assessing AI investment risks.

IMF Managing Director Kristalina Georgieva offered a deeper judgment: the greatest risk in the AI era may not be the failure of the technology itself, but rather financial markets failing to wait for the technology's success. When new technologies emerge, people tend to overestimate short-term effects and underestimate long-term ones. It takes considerable time for AI to diffuse from laboratories to full industrial application and truly boost productivity, yet investors expect rapid profitability. When the time gap between expectations and reality becomes intolerable to the market, investment contraction and stock price declines will arrive before productivity improvements, potentially dragging down the real economy.

It is important to emphasize that the 1.3 percentage point figure is a hypothetical scenario within the IMF model, not a baseline forecast. The IMF's basic outlook still considers AI investment to have a positive contribution to global growth. The value of this scenario lies in identifying the transmission mechanisms and vulnerable links: this path may only shift from a scenario to reality if AI companies' profits remain consistently below expectations, financing conditions tighten, or the pace of technology diffusion is significantly slower than the assumptions implied by market pricing.

Sources

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