The recent surge in US Treasury bond yields, reaching levels not seen since 2007, poses a significant challenge to companies in the artificial intelligence (AI) sector that heavily rely on debt. As borrowing costs rise, these companies face increased expenses, potentially impacting their ability to fund ambitious projects and infrastructure development. According to a report by CNBC, the AI infrastructure build-out, already at record levels, is set to become even more costly.
The impact of rising yields is particularly concerning for companies that have issued substantial amounts of debt to finance their AI initiatives. JPMorgan Chase estimated in June that $4.1 trillion in AI-related debt will be issued by 2030, as data center companies and others tied to the AI boom seek to expand their capacities to meet what many industry experts see as insatiable demand for AI services. With yields on 10-year Treasury bonds approaching 5.17% – up nearly one percentage point since the start of the year – companies issuing debt will need to offer more attractive returns to attract investors.
While the market is not yet in a state of panic, some AI companies are already feeling the strain. CoreWeave, a cloud company with significant debt, saw its shares rise about 8% this week, while Oracle, which has relied on debt markets to expand its AI activities, experienced a 7% decline in its stock over the same period and a 30% drop since the start of the year. In contrast, SoftBank, a major provider of capital for AI ventures, successfully raised $11.1 billion through the sale of high-risk bonds this week, with yields reaching 9.75% for a 7-year tranche.
According to Mark Malk, chief investment officer at Siebert Financial, many AI companies are willing to accept higher costs to secure funding, prioritizing growth over expense management. Malk noted that these companies need to raise substantial capital to remain competitive, suggesting that they are less concerned about the immediate cost of borrowing. This strategy may be viable for industry leaders like OpenAI and Anthropic, which are developing cutting-edge AI models and have valuations approaching $1 trillion in the private market.
The demand for AI services is driving significant investment in the sector, with tech giants like Amazon, Google, Meta, and Microsoft committing hundreds of billions of dollars to capital expenditures this year, and expecting to increase spending further by 2027. While these large tech companies enjoy strong credit ratings, allowing them to access capital at lower costs, smaller players in the AI space may face greater challenges. According to some market participants, the rising cost of borrowing could lead to a slowdown in deal-making for cloud startups and other AI-related ventures.
As bond yields continue to climb, some AI companies are already taking steps to mitigate the impact on their businesses. CoreWeave, for example, has warned in its regulatory filings that a 100-basis-point increase in interest rates could lead to a $30 million increase in interest expenses, based on its current debt levels. Meanwhile, concerns about the environmental and social implications of AI infrastructure development are growing, with some communities expressing opposition to the construction of new data centers.
Despite these challenges, many experts believe that the demand for AI services will continue to drive growth in the sector. The recent launch of Meta's AI assistant, "Muse," has been highly successful, with over 2.5 million downloads in its first two weeks, and some analysts predict that it could reach 100 million users within six to 12 months. As the AI industry continues to evolve, companies will need to navigate the complexities of rising borrowing costs, regulatory scrutiny, and growing demand for their services.
Key points
- AI companies reliant on debt face increased borrowing costs as US bond yields rise
- Sector leaders like OpenAI and Anthropic have valuations approaching $1 trillion
- Tech giants are committing hundreds of billions of dollars to AI infrastructure development
