Hotter-Than-Expected Inflation Clouds Rate-Cut Outlook

US: Inflation eased again in January but came in above Wall Street’s expectations, clouding the Federal Reserve’s path to rate cuts and potentially giving the central bank breathing space to wait until the middle of the year.

The Labor Department reported Tuesday that consumer prices rose 3.1% in January from a year earlier, versus a December gain of 3.4%. That marked the lowest reading since June.

Still, the consumer-price index was higher than the predicted 2.9%, a disappointment for investors who hope the Fed will cut rates sooner rather than later. Rate cuts tend to help stock prices by boosting economic activity and reducing competition from bonds for investor dollars.

The release gave a nasty jolt to markets. Stocks fell sharply and bond yields rose. The Dow Jones Industrial Average slid more than 500 points, or about 1.4%, its worst one-day decline since March. For all three major U.S. stock indexes, it was their worst performance on a CPI release day since September 2022 , according to Dow Jones Market Data.

The yield on the 10-year Treasury note rose to 4.315%, bringing it to its highest level since the end of November.

Interest-rate futures, which before Tuesday’s report implied the central bank would probably begin cutting rates by its May meeting, now suggest a June start date is more likely.

Where the Fed could go from here

Investors’ belief that Fed cuts were imminent has helped fuel the rally in stocks. The Dow on Monday had hit its 12th record close of 2024.

But Tuesday’s inflation report underscores why Fed officials have been dismissive of such expectations. Some Fed officials have suggested that the pace of improvement over the past six months might overstate underlying progress in containing price pressures.

Officials have said they aren’t ready to entertain rate cuts at their next meeting, March 19-20, because they want to see more evidence that inflation is returning to their 2% target.

Fed Chair Jerome Powell has said officials want to see more evidence that inflation is returning to its 2% goal, which is measured against a separate gauge to be released later this month by the Commerce Department.

“It’s not that the data aren’t good enough. It’s that there’s really six months of data,” Powell said in an interview on “60 Minutes” earlier this month. “It doesn’t need to be better than what we’ve seen, or even as good. It just needs to be good.”

Core prices, which exclude food and energy items in an effort to better track inflation’s underlying trend, were up 3.9% in January. That was equal to December’s gain, which was the lowest since mid-2021.

From a month earlier, overall prices were up a seasonally adjusted 0.3%, and core prices were up 0.4%—larger gains than economists expected.

Two measures of inflation

The Fed’s preferred measure of inflation has been running cooler than the Labor Department’s, and analysts said that could continue in January. The figures released Tuesday calculate medical care and airfares differently, and those categories were especially strong in January. The Labor Department’s measure also puts a much higher weight on shelter costs, which for both owners and renters are derived from rents. Shelter costs accounted for 0.23 percentage point of the monthly gain in overall prices in January. Shelter costs were up 0.6% month over month.

Some Fed officials have said they are looking for evidence that a slowdown in price pressures is broadening beyond goods such as used cars, which have seen prices decline over the past year. Tuesday’s figure showed the opposite: Price declines accelerated for goods while price increases accelerated for services.

And prices are still far above where they were before the pandemic—especially for items that most Americans buy often, like groceries.

The sting of those past price increases might be part of why so many Americans remain down on the economy . An analysis conducted by Goldman Sachs economists suggests that frustration with high price levels might have contributed to low confidence readings that persisted in the early 1980s even after inflation had slipped sharply.

“It does seem like it takes a while for confidence to recover, in part because people are focused on levels rather than changes,” said Goldman chief economist Jan Hatzius .

The Labor Department’s measure of overall consumer prices was up 19.6% this January from four years earlier, just before the pandemic hit. In contrast, prices were up 8.9% in the four years ended January 2020.

Economists generally expect inflation to cool this year, though they caution the process could be bumpy. Cooling prices for newly signed leases, for example, should eventually translate into lower shelter costs.

“I can tell inflation has gotten better,” said Mike Poore, of Henderson, Ky. “That’s definitely a good thing. It’s a shame it’s not happening quicker.”

The high cost of groceries

A Bank of America Institute analysis of customer data found households tended to make far more transactions a month for food and drinks at restaurants and bars, for groceries and for gasoline than they do for other items. Labor Department figures show that prices in all three of those frequent-transaction categories are higher, relative to before the pandemic, than prices overall.

Research from University of California, Berkeley economist Ulrike Malmendier and three co-authors found that prices for items that people buy more often play an outsize role in framing their inflation expectations. “In terms of what gets ingrained in people’s brains, it’s stuff that they purchase frequently,” she said.

Other research Malmendier has conducted examines the scarring effects of inflation episodes , which can have persistent, and potentially costly, effects on people’s financial decisions. She is heartened by the fact that inflation has retreated relatively quickly from the 9.1% it hit in June 2022 —a contrast to the experience of the late 1970s and early 1980s, when inflation remained elevated for years.

“I’m a little less worried about long-lasting effects than I was in 2022,” she said.

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