Publication date: 12 October 2026
Investors are entering a crucial earnings week with an unusual combination: forecasts for exceptional profit growth, rising borrowing costs and greater doubt about whether artificial-intelligence revenue can justify the debt funding its expansion.
Reuters reported on 12 October that the S&P 500 is expected to deliver third-quarter earnings growth of more than 30 percent, with technology accounting for much of the increase. At the same time, the US investment-grade credit default swap index, a measure of the cost of insuring corporate debt, has risen to its highest level since the US-Israeli war with Iran began.
Asian markets opened unevenly, with South Korean shares falling sharply while US and European futures edged higher. Oil prices eased, but long-term government borrowing costs remained elevated and investors awaited US inflation and retail-sales data.
Strong profits do not remove financing risk
The AI expansion has required enormous spending on data centres, chips, power, networks and property. Much of that investment is being funded through corporate borrowing. When interest rates and credit spreads rise together, projects must generate more cash simply to clear their cost of capital.
This creates a gap between accounting momentum and investment quality. A technology supplier can report rapid revenue growth while its customers take on expensive, long-lived obligations to build infrastructure. The market’s central question is shifting from how fast AI spending can grow to whether users can produce reliable returns from it.
Upcoming bank results will add another view. Major lenders can reveal whether corporate demand for credit remains healthy, whether defaults are increasing and how funding costs are affecting dealmaking. Inflation data will then influence expectations for the Federal Reserve’s next decisions.
Concentration makes the index vulnerable
Reuters noted that recent US equity gains have been concentrated in technology. That concentration means strong results from a small group can sustain headline indices, but disappointment from the same companies can have an outsized effect.
Leaders and investors should separate three layers of the AI cycle: suppliers earning from immediate scarcity, infrastructure builders committing capital for years, and customers expected to create productivity gains. Profits at the first layer do not automatically prove returns at the third.
Boards approving major AI expenditure should require measurable use cases, staged investment gates and realistic assumptions about energy and financing. Investors should examine free cash flow and debt maturity profiles alongside revenue forecasts.
This earnings season is therefore more than a test of quarterly numbers. It will show whether an AI-led market can remain resilient when money is expensive and expectations are already exceptionally high.