U.S. stocks fell today, with the Dow down 0.09%, S&P 500 losing 1.10%, Nasdaq falling 1.88%, and Russell 2000 dropping 1.93%.
The decline snapped a 53-session streak in which the S&P 500 had avoided a daily loss of 1% or more.
Technology led the selloff. Semiconductors, memory, software and networking stocks were broadly weaker, while concerns around heavily indebted AI infrastructure companies added to the pressure. More defensive areas, including healthcare, consumer staples and telecom, held up considerably better.
Interestingly, Treasury yields ultimately moved lower despite a hotter-than-expected inflation report, while WTI crude rose 1%.
Inflation Comes in Hotter Than Expected
Today’s biggest economic news was the September CPI report. Headline inflation rose 0.6% from August, while core inflation, which excludes food and energy, rose 0.3%, slightly above expectations. Annual core inflation accelerated to 2.6%.
More concerning was the breadth of the increase. Prices strengthened across services as well as goods, with pressure showing up in areas including shelter, hotels, medical services, used vehicles and apparel.
That complicates the Fed’s decision. Investors had recently become more optimistic that policymakers could wait before raising rates again. Today’s report makes that argument somewhat harder because inflation isn’t cooling as quickly or consistently as the Fed would like.
But markets didn’t react in the most obvious way. Treasury yields initially jumped after the report before reversing sharply, with longer-term yields ultimately finishing lower. Expectations for an October hike also faded from their morning highs.
That suggests investors may be increasingly concerned not just about inflation, but about what higher rates could eventually do to economic growth and riskier investments.
The AI Trade Faces a Bigger Test
That concern was particularly visible in AI-related stocks. Semiconductors fell again today, extending what has become a six-session losing streak for the group. The selloff is notable because there was little evidence that underlying AI demand itself is weakening. ASML actually raised its full-year sales outlook and said demand is strong enough that it is considering expanding production capacity beyond previously planned increases.
The problem is increasingly elsewhere: valuations, financing and return on investment. CoreWeave fell more than 15% as investors focused on the company’s debt burden and sharply higher borrowing costs. Dell, Hewlett Packard Enterprise and NetApp also fell following analyst downgrades that cited valuation or slowing growth expectations after enormous rallies. We’ve been watching this shift develop over the past several weeks.
The first question surrounding AI was whether demand would materialize. It clearly has. The next question is becoming much harder: Can companies earn enough from that demand to justify the enormous amount of capital being spent?
Financing Is Becoming Part of the AI Story
That’s particularly important because the AI buildout is increasingly dependent on outside capital. Data centers require enormous investments in chips, power generation, networking equipment and supporting infrastructure. For companies with strong balance sheets and substantial cash flow, those investments may be manageable.
For newer infrastructure providers relying heavily on debt, higher interest rates can change the economics dramatically. That doesn’t mean the AI investment cycle is ending. In fact, ASML’s results suggest demand remains exceptionally strong.
But investors are increasingly distinguishing between companies selling into the AI boom and companies borrowing heavily to build for it. That distinction may become one of the most important investment themes of the next phase of the AI cycle.
Banks Add to the Pressure
Financial stocks also struggled following another round of earnings. Bank of America’s results were hurt by a large regulatory charge and weaker trading revenue, while Morgan Stanley reported strong wealth-management and equity-trading results but softer fixed-income trading and investment banking.
The broader picture was more constructive than the stock reactions suggested. Consumer spending and credit quality remain relatively healthy, while banks continue to see significant opportunities financing the AI infrastructure buildout. But the reports also reinforced a familiar message: higher long-term interest rates create both opportunities and risks. Banks can earn more on certain loans, but volatile rates can hurt trading activity, borrowing demand and financing conditions across the economy.
Here’s Our Take
Today’s selloff looks less like investors abandoning the AI story and more like the market beginning to demand a higher standard of proof. AI demand remains enormous. ASML’s results reinforce that point. But demand alone is no longer enough. After extraordinary gains across semiconductors, servers, networking and data-center companies, investors increasingly want to know how much capital will be required, how expensive that capital will be and what returns companies can ultimately generate from it.
That’s especially important in today’s interest-rate environment. At the same time, today’s CPI report reminds investors why those financing costs may remain high. Inflation is still proving difficult to eliminate, limiting how quickly the Fed can become more accommodative. Put those two stories together and the market’s current challenge becomes clearer.
AI can continue growing rapidly while AI stocks become more selective. Companies with strong balance sheets, pricing power and clear paths to monetization may continue benefiting from the investment cycle. Companies relying heavily on debt or aggressive assumptions about future growth could face much greater scrutiny. The fact that defensive sectors held up while technology and small caps sold off suggests investors are already becoming somewhat more cautious.
That doesn’t necessarily signal the end of the bull market. But after a long period in which enthusiasm and expanding valuations rewarded nearly everything connected to AI, the next phase may be much more about execution, financing discipline and actual returns on capital.
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