Asia faces significantly higher risks from an AI correction compared to other regions, according to the Asean+3 Macroeconomic Research Office's 2026 Financial Stability Report. The region is 'particularly exposed' because it's at the center of global AI supply chains and 'increasingly integrated into AI-related financial markets', as reported by the Asean+3 Macroeconomic Research Office. Southeast Asia plus China, Japan and South Korea are more at risk than most economies to any potential collapse in the artificial-intelligence boom. A disorderly correction could propagate through multiple channels, including lower technology exports, portfolio losses, capital outflows, refinancing pressure on leveraged technology and infrastructure firms, and weaker investor confidence. The region accounted for two-thirds of the growth in global AI-related trade, with much of the physical production taking place in Asia from memory chips in South Korea to semiconductor assembly in Malaysia.
Despite massive infrastructure investments, the AI economy faces a severe profitability crisis. As of September 2026, 3.7 trillion dollars have been spent on investments into America's major artificial intelligence companies, representing nearly 12 percent of the U.S. GDP. However, the entire industry is only projected to produce 75 billion dollars in revenue this year, with major companies posting recent net losses of tens of billions of dollars. OpenAI posted a net loss of 38.5 billion dollars last year alone, while the company announced plans to spend 750 billion dollars on AI infrastructure through 2030. According to JP Morgan, AI companies need to produce 650 billion dollars in revenue for investors to earn a 10 percent return on current AI investments, yet Google, Anthropic, and OpenAI are only projected to generate 95 to 100 billion dollars in revenue while spending nearly 725 billion dollars on infrastructure.
The Financial Services Agency (FSA) established the "On-Chain Finance Forum for the AI Era" in Summer 2026, with its inaugural session held on September 30, 2026. According to the FSA, this forum represents a critical response to the global economy's transition toward "Agentic Commerce," where autonomous artificial intelligence agents conduct 24/7/365 cross-border economic transactions across languages and time zones without manual human intervention. The FSA's primary mandate is to deliver an interim summary and a joint public-private roadmap by early 2027 during its second session, as reported by the agency.
Nvidia announced a $500 billion financing initiative in August with financial partners including Blackstone, Apollo and KKR, aiming to use its GPUs as collateral for AI developers to access computing capacity. However, Wall Street remains cautious about whether Nvidia's AI chips can act as long-term collateral, with some banks underwriting the chips over just three to four years rather than Nvidia's claimed decade-long revenue generation potential. "Wall Street is much more conservative," said Tony Trzcinka, a senior portfolio manager at Impax Asset Management, as reported by Reuters. The concern stems from the rapid evolution of GPUs and lack of historical data, making it difficult for lenders to determine future chip values. Recent deals like CoreWeave's $8.5 billion loan and Broadcom's $35 billion Anthropic financing structure have relied heavily on strong customer revenues to reduce lender risk.
Some regional equity markets are heavily concentrated on AI, such as South Korea, exposing them to a sharp correction in prices. Other markets like Japan and Hong Kong have come to move closely in line with US AI and technology firms, meaning shocks could also be transmitted even absent a domestic trigger, according to AMRO. As hyperscalers increasingly turn to borrowings to fund costly data center buildouts, higher leverage could amplify shocks if AI returns disappoint. Opaque private credit markets and circular financing deals could worsen the instability. Central bankers around the world, from the Bank of England to the Monetary Authority of Singapore, have increasingly raised concerns about whether massive AI investments can be sustainable. The technology has developed at breakneck speed, but stiff competition among developers, higher borrowing costs and growing pushback against data centers and AI's security threats have raised concerns about sustainability.
