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AI borrowing pushes long-term bond yields to 15-year highs

Long-term bond yields have risen to their highest levels in 15 years or more across most major advanced economies, with heavy borrowing by artificial intelligence companies emerging as one of the factors putting upward pressure on borrowing costs.

AI borrowing pushes long-term bond yields to 15-year highs

Long-term bond yields have risen to their highest levels in 15 years or more across most major advanced economies, with heavy borrowing by artificial intelligence companies emerging as one of the factors putting upward pressure on borrowing costs.

The Organisation for Economic Co-operation and Development (OECD) stated this in its September 2026 Interim Economic Outlook report, titled Weathering Successive Shocks, released on Wednesday.

The OECD said concerns about longer-term government finances and heavy corporate bond issuance by AI companies are contributing to higher market yields and the additional return investors demand to hold longer-term bonds.

The development is increasing pressure on government finances and raising borrowing costs across the global economy, while also creating risks for financial markets if AI-related earnings fail to meet investor expectations.

What is driving the rise in yields

The OECD said long-term sovereign bond yields are now at their highest levels in 15 years or more in most major advanced economies, while real long-term interest rates have also increased.

It identified concerns about longer-term fiscal risks and heavy longer-term corporate bond issuance by AI companies as key factors putting upward pressure on market yields and the term premium required to hold bonds.

  • “Mounting concerns about longer-term fiscal risks and the heavy longer-term corporate bond issuance by AI-firms are key factors placing upward pressure on market yields and the term premium required to hold bonds,” the report said.

The term premium refers to the additional compensation investors require to hold longer-term bonds rather than shorter-term securities.

The scale of AI investment is also increasing demand for funding. The OECD said further increases in long-term sovereign bond yields could come from increased competition for funding from the private sector because of strong bond issuance by AI companies.

What this means for AI companies

The OECD also flagged broader financial risks from the way AI companies are financing their expansion.

It said the growing use of leverage and increasingly complex financing structures, combined with signs of rising credit risk, could amplify the impact of a sharp change in investor sentiment.

  • “The growing reliance of AI firms on leverage and increasingly complex financing structures, together with signs of rising credit risk, might also amplify any sharp shift in investor sentiment,” the report said.

The OECD added that earnings forecasts indicate AI-related companies will need rapid earnings growth over the coming years to meet current investor expectations.

  • “Analyst earnings forecasts for AI-related firms suggest that earnings growth will need to rise rapidly over the coming few years for investor expectations to be met,” the report said.

The report said disappointing earnings growth could materially slow investment in the sector.

It could also affect industries associated with AI investment, including engineering and construction, while contributing to deteriorating valuations in financial markets.

Major tech firms are raising billions for AI

The OECD’s concerns come as major technology companies increasingly turn to debt markets to finance the rapid expansion of their AI infrastructure.

In February, Nairametrics reported that Oracle planned to raise $45 billion to $50 billion through a combination of debt and equity financing to expand its cloud infrastructure and meet demand from major AI customers. The company expected part of the funding to come through a large bond issuance.

Nairametrics also reported in July that SpaceX had turned to the bond market to raise $25 billion to fund AI infrastructure investment, highlighting the scale of financing required as major technology companies expand their AI capacity.




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