Morgan Stanley Sees Attractive Entry Point in High-Quality AI Hyperscaler Bonds

Morgan Stanley has identified an attractive entry point in high-quality hyperscaler bonds, even as investors remain cautious about the debt used to fund artificial intelligence build-outs.

The firm expects a growing divide in financing terms between higher-quality and lower-quality companies. Hyperscalers, which have investment-grade ratings, have strong balance sheets, while more leveraged, junk-rated companies tend to be more exposed.

“We see an improving risk-reward for HQ hyperscalers and expect more spread volatility for data center bonds and neoclouds given execution and funding risk,” Morgan Stanley strategist Fernanda Lima said in a Tuesday note.

Debt worries have continued to escalate this year as artificial intelligence-related supply flooded the bond market. Several names saw yields rise, and five-year credit default swap spreads widened. Credit default swaps are essentially insurance against default. Bond yields move inversely to prices.

Lower-grade bonds were hit especially hard. CoreWeave became a focal point of AI debt worries after its bond yield topped 16% earlier this month. The neocloud company moved to ease concerns after reporting a third-quarter revenue beat and raising its full-year guidance after markets closed Tuesday. Its shares jumped more than 25% on Wednesday.

The U.S. bond market was closed in observance of Veterans Day. Lima said the credit market will remain open for hyperscalers and that they have already shown willingness to pay more to issue bonds.

Microsoft, Meta Platforms and Oracle have issued new bonds in the U.S. since Sept. 30, while Alphabet went to the European market for its latest issuance. Some of Meta’s bonds also went to Europe. The total came to $67 billion across both markets since that time, Lima noted.

“For HQ hyperscalers, strong balance sheets and earnings cushions provide the capacity to absorb higher borrowing costs, while attractive prospective returns sustain the incentive to invest,” Lima wrote.

She said spreads have somewhat tightened on most names since the recent deals were priced, though only Oracle saw spreads widen. When spreads tighten, it usually means the bond price has gone up.

Lima said the rest of the year should be quiet, with little issuance activity, if any, from AI companies. However, she expects 2027 to be a different story.

Morgan Stanley anticipates $1.66 trillion in capital expenditures from AI names next year, up 75% from 2026, and $1.77 trillion in 2028. That comes as project timing may shift.

With Democrats sweeping Congress and voters favoring local data center restrictions, construction will likely be pushed back, Lima said. She believes the hyperscalers will have an easier time navigating this post-election world.

“Even with risks emanating for future capacity build-out post elections, we are of the view that HQ hyperscalers will remain well capitalized to pursue their capex ambitions, and are better prepared to navigate further uncertainty to secure power and start new data center construction,” she said.

Lima also said she would not be surprised to see more transactions announced, like recent equity issuances, to help fund the gap between investments and monetization.

“All-in-all, with hyperscalers trading not far from YTD wides, and at levels consistent with A/BBB ratings, risk-reward is as good as it’s been all year,” Lima said.

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