Schroders Credit Portfolio Manager Martin Coucke notes that artificial intelligence is transforming the global economy and creating new divergences across the broader public credit market.

For active credit investors allocating across different sectors, the focus is not on blindly chasing the theme, but on identifying mispriced assets and adjusting portfolio positioning accordingly. Market attention on hyperscalers has shifted from initial enthusiasm over AI-driven business growth to a strict scrutiny of AI-fueled capital expenditure. While the economic benefits of generative AI remain uncertain, this uncertainty impacts equity investors more deeply, as they must assess whether such massive investment can generate sufficient returns, sustain margins, and support elevated valuations.

However, for bondholders, the investment opportunities presented by AI are vastly different from those in equities. Equity investors must translate AI investments into stronger growth, higher margins, and better valuations, whereas credit investors adopt a more defensive approach: assessing whether issuers can maintain cash flow, control leverage, and continue to service debt on schedule. On this basis, many companies remain among the highest-quality borrowers in the market, offering investors seeking exposure to the AI theme a more income-oriented option. The key to seizing these opportunities lies in investors' ability to reassess and adjust portfolio positioning as the AI theme evolves.

Until recently, hyperscalers held relatively limited appeal to bond investors. Given that U.S. hyperscaler credit spreads were tight relative to the overall U.S. investment-grade bond market, such bonds were not typically an ideal source of income. This phenomenon was even more pronounced when excluding Oracle (due to spreads widening significantly from idiosyncratic factors). This situation has shifted recently. The surge in AI-related capital expenditure has driven a significant rise in bond issuance, causing hyperscaler bonds to underperform notably. Although issuance activity remains concentrated among U.S. companies, issuers are increasingly raising funds across multiple currencies to support their massive capital spending plans. Issuance in 2026 is expected to reach $250 billion, including Apple and Nvidia.

For active investors, the crucial point is the ability to adjust portfolio deployment in response to these valuation changes, capturing opportunities arising from market repricing. The extent to which hyperscaler credit spreads have widened relative to the overall U.S. investment-grade index is indeed striking. This contrast becomes even more pronounced considering these issuers carry an average credit rating of around AA/AA- (excluding Oracle), while the overall U.S. investment-grade credit market averages only A-, predominantly comprising BBB-rated issuers. In some cases, although corporate fundamentals remain highly resilient, bond spreads are priced as if multiple downgrades are expected. While substantial issuance volumes have clearly weighed on bond performance, the market's reaction to AI capital expenditure risks may be overly pessimistic.

This is where the value of active asset management lies—being able to distinguish whether corporate credit quality has genuinely deteriorated or is merely affected by supply dynamics, deteriorating sentiment, or equity market volatility. When valuations diverge so clearly from fundamentals, attractive alpha opportunities often emerge. In fact, active credit management is particularly well-suited to the AI theme, as it allows flexible choice over sectors, weights, and maturities, rather than relying passively on broad index weights and absorbing the associated concentration risk. Looking at hyperscalers alone, these issuers currently represent roughly 4% of the total market value of the U.S. dollar investment-grade corporate bond market. While this number appears modest, the impact on overall risk is far greater than the figure suggests. This is because such companies tend to issue longer-dated bonds, which, when measured on a duration-times-spread (DTS) basis, generate greater risk and therefore more significant influence.

Active management offers ample flexibility to deliberately control these risk exposures, avoiding over-concentration in the largest borrowers and adjusting positioning promptly when market supply-demand conditions shift. Investment opportunities are not limited to hyperscalers—data centre financing, for example, represents another avenue to participate in the AI theme, given its critical role in supporting generative AI and cloud computing. Select issuers may offer attractive yield premiums, stable and predictable long-term cash flows, high-quality counterparties, and solid structural protections, enabling investors to share in the growth of AI infrastructure without being confined solely to bonds issued by large technology giants. Active asset management helps to separate AI as a long-term structural investment theme from the specific credit risks of individual issuers and bonds. Rather than blindly holding a bond simply because it is an index constituent, investors can carefully assess whether spreads adequately compensate for leverage levels, duration risk, risks from increased supply, potential free cash flow pressure, and whether future investments will deliver anticipated returns.

This precise screening is critical because different categories of AI-related investments face varying risks and opportunities. Hyperscalers, semiconductor-related issuers, data centre owners, and companies broadly adopting AI technologies may all be classified under the technology sector, yet their credit fundamentals, financing needs, and degree of exposure to the AI capital expenditure cycle can differ significantly. Equities and credit each offer distinct characteristics under the AI theme. If massive AI investments ultimately drive breakthrough long-term earnings growth, equity markets may provide greater upside potential, but they are also more susceptible to margin pressure and shifts in market expectations. In contrast, credit offers more limited upside but delivers attractive income, stronger resilience, and access to issuers with ample debt-servicing capacity.

The true credit investment opportunity, however, lies in adopting a flexible and targeted global credit management strategy—increasing deployment when valuations become more attractive, avoiding areas where risk expectations outweigh returns, and opportunistically seeking better risk-adjusted opportunities across the broader AI ecosystem, such as data centres, graphics processing units (GPUs), infrastructure, and AI adopters. AI is not the sole factor influencing credit markets, but it is expected to continue playing a pivotal role and represents one of many avenues for generating meaningful alpha for clients.