Major technology companies are significantly increasing their borrowing to fund artificial intelligence infrastructure, creating a potential mismatch between long-term debt obligations and the short economic life of AI hardware.

According to data from iShares, the world's largest technology firms—Meta Platforms (NASDAQ:META), Amazon.com (NASDAQ:AMZN), Microsoft (NASDAQ:MSFT), Alphabet (NASDAQ:GOOGL, NASDAQ:GOOG), and Oracle (NYSE:ORCL)—issued approximately $200 billion of investment-grade debt during the first half of 2026. This figure represents almost double the total debt issued during all of 2025.

Tom Lee, co-founder of Fundstrat, predicts that bond yields will normalize over the next six months. He stated that a 10-year Treasury yield below 5% would be "really positive for risk-on" assets, as lower yields reduce borrowing costs and increase the present value of future earnings.

However, the financing structure presents a unique risk profile. Oracle expects to raise $45 billion to $50 billion in gross cash during 2026 through a mix of debt and equity to expand cloud infrastructure for clients including Meta, Nvidia, and OpenAI. Alphabet spent $80.6 billion on capital expenditures during the first half of 2026, more than double the $39.6 billion spent during the same period in 2025. The company’s long-term debt stood at $98.2 billion as of June.

The concern lies in the duration mismatch. AI infrastructure hardware, such as GPUs, can have an economic life of roughly two to three years before becoming obsolete due to newer, more powerful chips. Hyperscalers are financing these assets with long-term debt, such as 10-year bonds, meaning they may be paying off loans long after the hardware they purchased has been replaced or relegated to less demanding tasks.

Goldman Sachs forecasts that the five hyperscalers will issue roughly $250 billion of bonds in 2026 and $400 billion in 2027. As borrowing costs rise, with the 10-year Treasury yield moving above 5%, investors are demanding higher yields. This situation creates a critical test for the AI trade: whether the revenue generated by the infrastructure arrives before the debt obligations come due.