Global AI-related bond issuance totaled only about $23 billion in September, marking the second-lowest month of the year, while AI issuance in the U.S. investment-grade market dropped to zero.

Morgan Stanley characterized this slowdown as a "pause rather than a retreat," expecting issuance to pick up in the fourth quarter but not to replicate the explosive growth seen in the first half.

As of the end of September, total global AI-related bond issuance for the year had reached $466 billion, more than double the $216 billion recorded for all of last year.

In its latest report, Morgan Stanley analyzed that September's cooldown was not caused by deteriorating fundamentals or capital shortages, but rather by a combination of three factors: a significant front-loading of earlier issuance, regulatory and political hurdles facing data center construction, and a sharp rise in interest rates forcing project-level terms to be renegotiated.

Why September Cooled Down

This year's AI financing pace has been highly uneven. June set the annual peak with $113 billion in single-month issuance, followed by a steady decline in subsequent months.

High-quality hyperscalers — Alphabet (NASDAQ: GOOGL), Amazon (NASDAQ: AMZN), Meta (NASDAQ: META), and Microsoft (NASDAQ: MSFT) — issued approximately $132 billion in the investment-grade market this year, a roughly 25-fold year-over-year increase. Including Oracle (NYSE: ORCL) and SpaceX, total issuance from the six major hyperscalers across all currencies has reached approximately $254 billion, heavily concentrated in the first half.

Morgan Stanley noted that "after a busy summer, given the volume already completed and issuers' efforts to establish a cadence, we expect near-term supply to slow."

U.S. investment-grade AI issuance was zero in September. Non-dollar markets saw some activity, with Amazon (NASDAQ: AMZN) issuing a four-tranche deal worth 4.25 billion pounds. On the leveraged finance side, SoftBank Group (TSE: 9984) issued approximately $10 billion in high-yield bonds, and AI data center operator Crusoe issued about $500 million in loans. Total September leveraged finance volume was approximately $14 billion.

The second factor is regulatory and political constraints. New data center construction faces permitting, power supply, and political headwinds — which Morgan Stanley previously summarized as the "three Ps": people, power, and politics. These constraints are shifting from potential risks to real obstacles.

The third factor is interest rates. The sharp rise in yields means project-level transactions may need to be renegotiated, with lower-rated issuers and project financings being more sensitive to funding costs.

Q4 Outlook: Hyperscalers Will Return, but at a Different Pace Than Last Year

Morgan Stanley expects fourth-quarter issuance to exceed September levels but not to cluster as heavily as last year, when most supply emerged in Q4.

High-quality hyperscalers are expected to return to the U.S. investment-grade market while continuing to raise funds in non-dollar markets. Non-dollar hyperscaler issuance has reached approximately $72 billion this year, approaching one-third of total global hyperscaler issuance, with currencies expanding from last year's sole dollar and euro denominations to include Canadian dollars, British pounds, Swiss francs, Australian dollars, and Japanese yen. Morgan Stanley expects euro-denominated deals to enter the market in Q4 as well.

The pace of data center project financing is harder to predict. Morgan Stanley has lowered its ABS and CMBS issuance estimate for the year to $25-30 billion, implying approximately $5-10 billion of remaining supply space in Q4.

An important driver of the Q4 rebound is the 2027 capital expenditure outlook. Morgan Stanley forecasts combined capex for the six major hyperscalers in 2027 at approximately $1.4 trillion, significantly above the market consensus of about $1-1.1 trillion. Third-quarter earnings reports (expected in October) could bring another round of capex upgrades, directly fueling financing demand.

Morgan Stanley believes high-quality hyperscalers are "largely insensitive" to higher rates — return on invested capital (ROIC) prospects are strong, and debt financing costs remain below equity financing costs. These companies have an overall leverage ratio of just 1.3 times (net leverage of 0.4 times), a cash-to-debt ratio of 132%, a median credit rating of AA-, and ample balance sheet capacity.

Macro Test More Important Than Supply Shock

Morgan Stanley emphasized that for the investment-grade credit market, "the macro environment — not excess supply — is the biggest test before year-end."

Investment-grade bonds have posted a total return decline of 3% year-to-date and a quarterly return decline of 4%, a drawdown that has reached levels that could trigger large-scale redemptions from mutual funds and ETFs. The 10-year U.S. Treasury yield has risen from 1% to above 5%, and multiple interest rate repricings over the past five years have repeatedly impacted credit spreads and fund flows.

However, Morgan Stanley believes the credit market overall can absorb rising yields because nominal growth remains above 6%, corporate earnings growth is even stronger, and the rate rise has solid fundamental support. The firm's economists expect the Federal Reserve to hike only twice more, more dovish than market pricing of close to four hikes.

On credit differentiation, Morgan Stanley reiterated its preference for secured assets, which account for roughly 30% of AI-related debt. Spread volatility in secured data center bonds is primarily driven by construction risks — permitting delays, power supply, and lease uncertainties — while ABS and CMBS assets already in stable operation are less affected by such shocks. Chip financing's asset characteristics allow for faster cash flow generation and amortization, but publicly traded products in this space remain limited.

Looking beyond the fourth quarter, Morgan Stanley believes much of the hyperscaler spread compression trade may have already played out: issuance cadence is becoming more predictable, capital expenditure is shifting toward shorter-duration assets such as chips, and strong returns on AI investment continue to validate the soundness of the spending rationale.