Amanda Lynam, Chief Credit Strategist in Global Investment…

PodcastAlpha ExchangeAmanda LynamSep 23

The discussion points to a broadly supportive corporate-credit backdrop, with growth around or slightly above trend and generally solid fundamentals, but weaker borrowers remain vulnerable to higher rates and refinancing risk. AI investment is driving substantial and increasingly diverse financing needs, with Goldman Sachs expecting large investment-grade issuance in 2026 and 2027 and a greater private-market role later. Foreign demand has been strong, while duration exposure and potential rates volatility remain important risks; Goldman Sachs forecasts modest spread widening.

Fixed Income Corporate Earnings Artificial Intelligence Private Credit Interest Rates Risk Management

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Key Takeaways

The AI buildout is expected to require substantial borrowing: hyperscaler capital expenditures are estimated at more than $6 trillion from 2026 through 2030, while Goldman Sachs forecasts $250 billion of hyperscaler debt issuance in 2026 and $400 billion in 2027, plus $300 billion of data-center and chip financing in 2027. Goldman expects debt to fund 35% of capital expenditures at the 2027 peak, in part because monetization may lag investment by three months to two years.

AI-related credit supply extends well beyond hyperscalers: they account for about 40% of tracked gross issuance, while data-center and GPU project finance contributes roughly 22%–24%, and other sources include software services, memory, PCs, and equipment. The index measure showing AI at around 12% of US investment-grade debt excludes private data-center project finance and chip financing, while Goldman also classifies 30% of issuance from AI-adjacent sectors such as utilities and machinery as AI-related.

Corporate credit has support from growth around or slightly above trend and generally solid leverage and coverage, but that strength masks weaker borrowers: some triple-C issuers and very small private-credit borrowers have interest coverage near one or fixed-charge coverage below one. Amanda says leveraged finance is past peak defaults for this cycle and does not expect higher base rates to cause a new peak, though she says the pressure could curb recent improvement for floating-rate borrowers.

AI disruption remains an overhang for software credit, with risk depending on firms’ business models, competitive moats, customer relationships, and data ownership. The 2028–2029 software maturity wall in broadly syndicated loans and private credit is worth monitoring: Amanda says refinancing at higher bond yields could reverse some recent improvement in interest coverage, but does not expect that pressure to create a new default peak.

The impact of rising Treasury yields on credit depends more on their cause and pace than on a single yield threshold: resilient nominal growth may make higher yields easier to absorb, while fiscal concerns or other adverse drivers could make them harder to digest. Amanda says rates volatility has not reached a credit headwind tipping point, but Goldman Sachs forecasts modest spread widening; she notes that if rates volatility rises enough to weaken yield-based demand, or growth drops sharply, spreads could widen.

TECHNOLOGY

Software Credit Risk — AI disruption remains an overhang for software credit, but the risk varies with firms’ business models, competitive moats, customer relationships, and data ownership. Uncertainty may persist until refinancings provide clearer evidence, making 2028 and 2029 loan and private-credit exposures worth monitoring.

“And I think it's just the disruption to the legacy software business model narrative as it relates to AI. It's just difficult to disprove…”—

ECONOMY

Yield Drivers — For corporate credit, the cause and pace of rising Treasury yields matter more than any single yield threshold. Higher yields may be easier to absorb when nominal growth is resilient; fiscal concerns or other adverse drivers could make a yield backup harder to digest. Resilient growth also supports corporate profitability.

“It's incredibly difficult to time that. We often get asked, is there a level of yields that becomes detrimental for corporate credit?…”—

MARKETS

AI Investment Scale — Hyperscaler capital expenditures are estimated at more than $6 trillion from 2026 through 2030. The total would be higher if it included 2025 investment and spending through 2031.

“If you just look at the CapEx figures from 2026 through 2030 for the group of hyperscalers, that CapEx estimate is upwards of $6,000,000,000,000 So it is significant if you…”—

AI Credit Supply — Hyperscalers account for about 40% of tracked AI-related gross issuance, while project finance—including data-center and GPU financing—makes up roughly 22%–24%. Software services, memory, PCs, and equipment are also significant sources, so AI financing extends well beyond hyperscalers.

“But what we found in our work is that actually the hyperscalers are only 40% of total AI related gross issuance. So the theme is actually much broader than that.”—

Credit Fundamentals — Corporate credit is supported by growth around or slightly above trend and generally solid leverage and coverage metrics. But aggregate strength masks weaker fundamentals in triple-C US and European high yield and among certain private-credit borrowers, especially very small borrowers from ultra-low-rate vintages. Some have interest coverage near one or fixed-charge coverage below one.

“So at a high level, would say we're generally constructive on corporate credit due to a few fundamental factors…”—

FORECASTS

Spread Outlook — Goldman Sachs forecasts modest spread widening, which Amanda says would remain narrow by historical standards. Elevated all-in yields have attracted yield-based investors and supported credit; spreads could widen if that demand weakens as rates volatility rises or if growth drops sharply. A sharp downturn could also bring falling yields and make the yield backdrop less compelling for credit.

“Our forecasts, however, do call for some modest spread widening, but I think it's important to frame that in the context of the overall historical pattern…”—

Alpha Exchange Introduction

Dean welcomes Amanda Lynam back to discuss the credit landscape, including supply, demand, corporate fundamentals, and AI-related capital investment.

Constructive Credit Backdrop

Lynam sees trend-like growth, solid overall credit metrics, and strong yield-driven demand supporting credit, while expecting modest spread widening and watching rates volatility.

Credit Quality And Dispersion

Fundamentals remain sound across much of the market, but weaker borrowers face tighter coverage and greater risk; she favors selective moves down in rating quality.

AI Issuance And Market Capacity

The US investment-grade market can fund much of the near-term AI buildout, but issuer concentration and market saturation may shift more financing toward private markets over time.

Hyperscaler CapEx Forecasts

Goldman expects substantial hyperscaler borrowing as AI investment accelerates, with issuance rising through 2027 and separate financing needs from data centers and chips.

Crowding Out And Diversification

Lynam sees little evidence that hyperscaler borrowing is crowding out other issuers, while investors value diversification into sectors such as banks, energy, healthcare, and food.

Measuring Broader AI Exposure

Goldman tracks direct and adjacent AI-related borrowers, finding hyperscalers and project finance are major sources of issuance, with European supply expected to increase.

Foreign Demand For US Credit

Foreign investors own a substantial share of US corporate bonds and their purchases remain strong; Goldman expects demand to hold up given market size and limited alternatives.

Rates Volatility And Spread Risk

The key risk is that rising rates volatility or weaker growth undermines yield-driven demand, with the cause and speed of a rates backup shaping credit’s resilience.

Treasury Yields And Credit Returns

Risk-free rates account for most investment-grade all-in yields, making Treasury moves central to returns even as investors accept the opportunity cost of staying overly defensive.

High-Yield Market Evolution

The high-yield market has become more institutional and liquid as smaller borrowers increasingly use private credit or loans, while the weakest credits remain concentrated in the left tail.

Refinancing And Software Risk

Refinancing pressure is manageable overall, but software maturities in 2028 and 2029 merit attention because AI disruption could challenge some borrowers’ business models.

Portfolio Diversification Strategies

Lynam recommends tracking AI exposure beyond hyperscalers and considering real assets such as commodities, infrastructure, and real estate for diversification and inflation protection.