AI spending boosts corporate debt issuance
According to MFS Investment Management analysts Benoit Anne and David Peterson, the AI expansion has progressed beyond its equity-focused origins, presenting new challenges for fixed income investors as companies seek financing for growth.
The analysts emphasize that fixed income investors must focus on identifying companies capable of funding investments, generating sufficient returns, and maintaining strong balance sheets throughout economic cycles, rather than solely considering AI spending beneficiaries.
MFS Investment Management predicts a sustained AI investment cycle, but notes that credit performance will increasingly depend on individual company factors, such as funding mechanisms, debt levels, and cash flow predictability.
The analysts highlight security selection as key for outperformance, arguing that tight credit spreads and varying issuer fundamentals make bottom-up analysis more attractive than broad market exposure.
AI Fuels Financing Cycle
AI has transitioned from a technology-focused equity trend to a broader financing cycle, fueled by rapid spending from hyperscalers and a 2025 tax package encouraging R&D and capital investment.
While this spending has boosted economic growth and corporate profits, Anne and Peterson note that the next phase of AI development is increasingly reliant on credit markets for funding.
As AI investments become more debt-financed, credit performance is expected to vary widely, making security selection a key driver of active fixed income returns, according to the analysts.
Datacenters are at the heart of much AI investment, requiring extensive infrastructure, including power, cooling systems, CPUs, GPUs, memory, networking equipment, and fiber connectivity.
Initial spending has concentrated on physical infrastructure like land, construction, power, and cooling, benefiting sectors such as construction equipment and modular power providers.
Debt Issuance Surges Ahead
The most significant fixed income impact of AI is anticipated to come from increased debt issuance, with datacenter investment already attracting hundreds of billions of dollars and projected to reach trillions annually by decade’s end.
Microsoft, Alphabet, Amazon, Meta, and Oracle dominate demand, leveraging their investment-grade ratings and strong cash flows to access public credit markets at tight spreads.
Investment-grade credit is the primary market for AI-related debt, though the ecosystem is expanding as lower-rated borrowers enter public and private markets, often with weaker balance sheets and less proven business models.
Some emerging compute-as-a-service firms use financing structures pledging GPUs as collateral, offering attractive yields. However, Anne and Peterson caution investors to assess demand for excess compute capacity, utilization rates, and collateral values.
The analysts stress that fixed income managers must identify borrowers capable of sustaining new debt levels through stable cash flows, distinguishing them from those vulnerable if growth expectations falter.
Shift to Chips and Servers
As facilities near completion, spending is expected to shift toward chips, servers, and networking equipment, broadening the impact of AI investment across a wider range of credit issuers.
AI-related issuance is likely concentrated in technology, communication services, utilities, infrastructure, and select industrial sectors, potentially increasing their representation in credit benchmarks.
However, the analysts warn that this balance could shift if supply increases while demand weakens, showing the need for careful security selection.
Technology sector spreads remain tight, posing challenges for investors seeking value. Markets may be pricing many AI-related credits as if their fundamentals are closely aligned.
Anne and Peterson conclude that the next phase of AI investment will be defined less by broad participation and more by differences between individual issuers.
