IMF Warns Surge in U.S., China Debt Could Have ‘Profound’ Impact on Global Economy

The U.S. and Chinese governments should take action to lower future borrowing, as a surge in their debts threatens to have “profound” effects on the global economy and the interest rates paid by other countries, the International Monetary Fund said Wednesday.

In its twice-yearly report on government borrowing, the Fund said many rich countries have adopted measures that will lead to a reduction in their debts relative to the size of their economies, although not to the levels seen before the Covid-19 pandemic.

However, that is not true of the U.S. and China, which will continue to see a surge in borrowing if current policies remain in place. The Fund projected that U.S. government debt relative to economic output will rise by 70% by 2053, while Chinese debt will more than double by the same year.

The Fund said both countries will lead a rise in global government debt to 98.8% of economic output in 2029 from 93.2% in 2023. The U.K. and Italy are among the other big contributors to that increase.

“The increase will be led by some large economies, for example, China, Italy, the United Kingdom, and the United States, which critically need to take policy action to address fundamental imbalances between spending and revenues,” the IMF said.

The IMF expects U.S. government debt to be 133.9% of annual gross domestic product in 2029, up from 122.1% in 2023. And it expects China’s debt to rise to 110.1% of GDP by the same year from 83.6%.

The Fund said there had been “large fiscal slippages” in the U.S. during 2023, with government spending exceeding revenues by 8.8% of GDP, up from 4.1% in the previous year. It expects the budget deficit to exceed 6% over the medium term.

That level of borrowing is slowing progress toward reducing inflation, the Fund said, and may also increase the interest rates paid by other governments.

“Loose US fiscal policy could make the last mile of disinflation harder to achieve while exacerbating the debt burden,” the Fund said. “Further, global interest rate spillovers could contribute to tighter financial conditions, increasing risks elsewhere.”

A series of weak auctions for U.S. Treasurys are stoking investors’ concerns that markets will struggle to absorb an incoming rush of government debt. The government is poised to sell another $386 billion or so of bonds in May—an onslaught that Wall Street expects to continue no matter who wins November’s presidential election.

While analysts don’t expect those sales to fail, a sharp rise in U.S. bond yields would likely have consequences for borrowers around the world. The IMF estimated that a rise of one percentage point in U.S. yields leads to a matching rise for developing economies and an increase of 90 basis points in other rich countries.

“Long-term government bond yields in the United States remain elevated and sensitive to inflation developments and monetary policy decisions,” the Fund said. “This could lead to volatile financing conditions in other economies.”

China’s budget deficit fell to 7.1% of GDP in 2023 from 7.5% the previous year, but the IMF projects a steady pickup from this year to 7.9% in 2029. It warned that a slowdown in the world’s second largest economy “exacerbated by unintended fiscal tightening” would likely weaken growth elsewhere, and reduce aid flows that have become a significant source of funding for governments in Africa and Latin America.

An unusually large number of elections is likely to push government borrowing higher this year, the Fund said. It estimates that 88 economies or economic areas are set for significant votes, and that budget deficits tend to be 0.3% of GDP higher in election years than in other years.

“What makes this year different is not only the confluence of elections, but the fact that they will happen amid higher demand for public spending,” the Fund said. “The bias toward higher spending is shared across the political spectrum, indicating substantial challenges in gathering support for consolidation in the years ahead, and particularly in a key election year like 2024.”

A sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.

The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.

The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.

The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.

This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.

The debt behind the AI build-out

Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.

Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.

JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.

The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.

That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.

A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.

When interest rates rise, those assumptions become less forgiving.

Inflation changes the calculation

September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.

The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.

CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.

Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.

Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.

The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.

China adds another source of pressure

Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.

Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.

The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.

That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.

A reset rather than the end of the boom

The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.

What has changed is the market’s willingness to overlook the price and financing structure of that growth.

The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.

More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.

For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.

Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.

The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.

Fact box

Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026

Philadelphia Semiconductor Index: Down approximately 11.4 per cent

Micron Technology: Down approximately 14.6 per cent

Samsung Electronics: Down approximately 18 per cent

SK Hynix: Down approximately 24 per cent

US September inflation: 3.7 per cent annually

Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion