“Our upside is generally capped, while downside from credit deterioration can be meaningful — so our focus is on whether we are being adequately compensated for the risks of financing AI's growth.”
Q. How do you assess the risk-return profile of AI-related investments in the current market environment?
A. As fixed income investors, we start from an asymmetric position: our upside is generally capped, while the downside from credit deterioration or spread widening can be meaningful. So rather than focusing on the growth potential of AI itself, we focus on whether investors are being adequately compensated for the risks that come with financing that growth.
We never look at AI-related issuers in isolation. Every credit is measured against the broader fixed income opportunity set, asking whether its spread represents compelling relative value versus similarly rated credits elsewhere in the market. Many of the large technology platforms driving AI investment have exceptional business franchises and strong balance sheets — but the sheer scale and pace of AI-related capital spending raises real questions around free cash flow, leverage, future funding needs, and ultimately the return on that investment.
Technical factors matter too. The wave of hyperscaler and data center issuance has prompted the market to reassess fair value, and spreads in this segment have increasingly decoupled from the rest of corporate credit. We view this repricing as warranted, and it is beginning to create selective opportunities. With substantial additional supply still ahead, however, we remain cautious in the near term.
Q. Which criteria drive your security selection and portfolio weighting decisions in this area?
A. Our process starts with fundamental credit analysis — not a thematic view on AI. At the issuer level, we evaluate free cash flow generation, leverage (including lease obligations and other off-balance-sheet commitments), liquidity, funding requirements, and the issuer's capacity to protect its balance sheet and credit ratings if future earnings fall short of expectations.
Security structure carries equal weight. We look closely at tenor, seniority, collateral and liens, covenant protection, amortization, and other structural safeguards. For data center project financings specifically, we also assess the strategic importance of the asset to its owner, operator, and tenant; counterparty quality; contractual protections; geographic and political considerations; and potential operational or climate-related risks.
Technical factors — deal size, liquidity, expected future supply, and new-issue pricing — also materially shape our view of relative value, and the scale of AI infrastructure financing needs makes these considerations especially important today.
“A large benchmark weight does not, in itself, justify owning a security.”
Portfolio weights ultimately reflect our assessment of relative value and the balance of potential upside and downside. Higher-conviction positions — where we see meaningfully more upside than downside — receive larger allocations, within our diversification and risk-management framework. We also evaluate correlated exposures across the portfolio to make sure that aggregate AI, technology, data center, and related infrastructure risk is intentional, rather than simply the accumulation of individually attractive securities.
Importantly, we are not benchmark-driven in constructing portfolios. Our underweight to ultra-long hyperscaler debt illustrates this well: despite this segment's growing representation in corporate bond indices, we believe valuations at the long end still do not fully compensate investors for the combination of duration, supply, and issuer-concentration risk they carry.
Q. To what extent do you expect your exposure to AI-related companies to increase or decrease going forward?
A. We remain tactical and highly selective toward hyperscalers and AI-related issuers, and currently maintain an underweight bias. We generally favor intermediate-duration exposure: the long end of the investment-grade market has become increasingly concentrated in hyperscaler debt, leaving ultra-long bonds particularly exposed to supply and issuer-concentration risk. In our view, intermediate maturities currently offer a more attractive risk-adjusted total-return profile across a range of macroeconomic scenarios.
Given our currently modest exposure, it is reasonable to expect our allocation could grow over time as valuations become more compelling. Any increase, however, would be driven by security-specific relative value and conviction in our ability to generate alpha — not by a desire to increase AI exposure for its own sake.
We expect AI infrastructure to remain a significant and growing source of financing activity, and therefore an expanding part of the fixed income opportunity set. At the same time, substantial capital needs and additional issuance still lie ahead, which argues for patience and selectivity. Recent repricing has begun to create attractive opportunities in certain issuers and structures, but we do not believe that adjustment has fully run its course. We will continue to deploy capital selectively, where spread, structure, and fundamentals offer adequate compensation for risk.
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