Stock Markets June 6, 2026 04:39 PM

Asset Managers Load Up on AI-Linked Debt to Weather Potential Credit Strain

DoubleLine and Oaktree favor structurally resilient and well-capitalized credits as data-center financing and hyperscaler bond issuance accelerate

By Priya Menon
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Two large credit managers are buying debt positioned to withstand a possible credit downturn tied to heavy corporate investment in artificial intelligence. They are focusing on deal structure and borrower balance-sheet strength amid rapid issuance tied to data-center build-outs and broad AI-related capital expenditure plans.

Asset Managers Load Up on AI-Linked Debt to Weather Potential Credit Strain
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Key Points

  • Asset managers DoubleLine and Oaktree are buying debt positioned to survive a potential credit downturn linked to AI investment activity.
  • Concerns include long-dated securities that may outlive the relevance of current technology and the risk of data-center overbuilding due to lengthy construction schedules and many concurrent projects.
  • Hyperscalers have increased unsecured bond issuance, and industry estimates point to about $5 trillion of AI-related capex over the next five years, much of it expected to be debt-financed; sectors impacted include technology, data centers, and corporate credit markets.

Two asset managers are positioning their portfolios to withstand a potential credit shock related to the wave of corporate spending on artificial intelligence, according to reporting that cited comments from their portfolio managers.

At the Bloomberg Global Credit Forum, Robert Cohen, a portfolio manager at DoubleLine Capital LP, warned that markets could become overheated in the months or years ahead as technology companies commit large sums to AI. Cohen said investors should favor credits that can endure stress either through conservative deal structures or because the borrowers maintain robust balance sheets.

Cohen highlighted particular challenges tied to AI-related lending. Many securities being put up for sale now will not mature for decades, which raises the prospect that the technologies underpinning those assets could be obsolete long before maturity. He also pointed to an elevated risk of overbuilding in data-center markets, noting that those facilities can take a long time to construct and that many projects are currently moving forward simultaneously.

The note cited a Barclays report dated May 21 that found large U.S. technology companies - often called hyperscalers - have sold more than $155 billion of unsecured bonds globally, an increase of more than 45% compared with their total issuance the prior year.

Christina Lee, co-portfolio manager in private credit at Oaktree Capital Management, said the market for data-center financing is still in its early stages. Oaktree is being selective, she said, because it is not yet clear which projects or operators will prevail.

Bloomberg Intelligence has estimated that companies will invest roughly $5 trillion in capital expenditures for AI over the next five years, and that much of that investment will be financed with debt.


Implications and market focus

  • Credit managers are prioritizing structure and balance-sheet strength when buying AI-linked debt.
  • Data-center financing and unsecured bond issuance by hyperscalers are central to the changing credit picture.
  • Large-scale AI capital expenditure plans are expected to be largely debt-funded.

Outlook

Portfolio managers cited in the reporting are preparing for a market environment that could grow frothy as AI investment accelerates. Their approach reflects caution around long-duration securities and concentrated build cycles in the data-center sector.

Risks

  • Long maturities on AI-linked debt could leave investors exposed if technologies become obsolete before securities mature - impacts credit investors and fixed-income markets.
  • Potential overbuilding in the data-center sector due to many simultaneous projects increases the risk of weaker returns for developers and lenders - impacts real estate and infrastructure financing.
  • Uncertainty over which data-center operators will succeed means selectivity is required; misjudging winners and losers could harm private credit and leveraged lenders.

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