Tech Giants’ Borrowing Spree Pushes 30-Year Treasury Yields to 20-Year High

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First, let’s look at the scale of the borrowing. U.S. investment-grade bond issuance hit a record $145.2 billion in August, while AI hyperscalers have issued nearly $220 billion this year, more than double all of 2025. The pace shows that the AI build-out is entering a far more capital-intensive phase

Alphabet is leading the charge. The Google parent has already raised nearly $77 billion through public bonds this year, across multiple currencies. The aggressive fundraising shows that Big Tech is securing massive amounts of capital to keep its AI expansion on track

And it’s not just cloud giants. AMD recently raised $4.75 billion, its largest dollar bond sale ever, while JPMorgan now expects technology companies to issue around $540 billion in bonds this year. The message is clear: the AI arms race is increasingly being financed with debt

Here’s the bigger problem. Tech companies are competing with the U.S. government for long-term capital at a time when fiscal borrowing is already enormous. That competition is pushing long-term yields higher, making the cost of money increasingly expensive

Why does that matter for AI stocks? Higher Treasury yields raise companies’ financing costs and the return required from AI investments. In other words, AI projects now need to generate much bigger profits to justify the spending. The era of cheap money and easy AI valuations is fading

This is creating a clear divide in the market. Companies like Microsoft and Alphabet have strong balance sheets and easy access to capital. Smaller AI infrastructure companies with weak cash flow and heavy financing needs face much greater pressure. Investors are starting to reward financial strength and clear monetization, not just ambitious spending

So, is the AI bull market over? Not necessarily. But the rules are changing. The market is shifting from “who can spend the most” to “who can earn the most.” The winners will be companies that can turn massive AI investments into sustainable profits and cash flow. The AI supercycle is maturing, and capital efficiency will matter just as much as technology

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