Monitoring A.I. Exposure Across Credit and Securitized Landscapes

Many areas of the investment landscape have recently become an 'A.I.'-driven marketplace. We spoke with IR+M to discuss where we are in today's A.I.-driven market cycle, along with how insurers should evaluate and monitor their A.I. exposure within their portfolio's corporate and securitized sectors.

Rob Lund, CFA | Head of Consultant Relations and Insurance Solutions | Income Research + Management
rlund@incomeresearch.com | Learn More >>

SAA: Where are we today in the AI-driven market cycle?

IR+M: The AI-driven market cycle is in the middle innings, with the investment phase still accelerating rather than peaking. What began with the launch and adoption of generative AI applications has evolved into a massive infrastructure buildout led by hyperscalers such as Microsoft, Alphabet, Amazon, Meta, and Oracle. The market is increasingly treating hyperscaler financing as a multi-year structural theme rather than a one-time wave of issuance. Projections of AI/datacenter financing needs continue to rise, with hyperscaler capital expenditures increasing from roughly $400 billion in 2025 to an estimated $700 billion in 2026 and $1 trillion by 2028, suggesting that the AI buildout remains a prolonged investment cycle rather than a short-term technology trend.

From a fixed income perspective, AI has become a structural theme that we believe is reshaping debt markets. AI investments are increasingly drawing financing from investment-grade corporates, project finance, high-yield debt, ABS, CMBS, private credit, and other asset-backed or infrastructure-oriented structures. This broadening AI-related ecosystem is expanding the investable universe and creating new opportunities across sectors and structures, while also increasing benchmark exposure to AI-related credits.

SAA: As AI datacenter investment accelerates, how should insurance investors evaluate and monitor AI-related exposure across corporate credit and securitized markets?

IR+M: As AI datacenter investment accelerates and index compositions evolve, we believe insurers should focus on issuer-specific fundamentals rather than relying on a broad thematic view. Historically, hyperscalers have traded at a premium due to their strong balance sheets and cash flow generation. However, that relationship has narrowed as debt supply has increased and investors have become more focused on leverage, execution risk, and return on invested capital. A thorough credit assessment could also assess contractual obligations that traditional leverage metrics may not fully capture, such as power commitments, utility collateral requirements, take-or-pay agreements, long-term lease obligations, and other capital commitments associated with large-scale AI infrastructure. The key question is no longer whether a company is participating in the AI buildout, but whether it can generate attractive economic returns from its investments. The utilization and profitability of new data center assets will likely depend, in part, on how key industry and market developments evolve.

Tenant concentration risk is another factor that may warrant consideration. Tenant quality may become as important as traditional measures such as leverage, amortization, and collateral coverage as financing structures evolve. Many AI-related financings rely on a single hyperscaler or cloud provider, making credit outcomes increasingly dependent on the tenant's financial strength, strategic priorities, and long-term demand for compute capacity.

The lines between traditional corporate debt and structured finance are blurring as issuers develop new financing structures and capital-recycling strategies. We believe the most effective framework combines corporate credit analysis with securitized asset expertise, uniting traditional issuer analysis, collateral assessment, cash flow modeling, and structural risk evaluation. This allows investors to develop a consistent language around risk, compare opportunities across asset classes, and identify where compensation is most attractive.

SAA: What are the broader implications of the AI investment cycle for corporate and securitized sectors going forward? What in particular should insurers continue to be mindful of?

IR+M: The most important variable for both corporate and securitized sectors may not be access to capital, but access to power. As data center demand grows, the availability of electricity, transmission capacity, and utility support could influence whether projects achieve expected utilization and cash flow targets. Consequently, exposure to AI infrastructure alone does not guarantee attractive investment outcomes due to obsolescence risks. Whether projects become productive assets may depend, in part, on the strength of their counterparties, the realism of development timelines, access to power, and the soundness of underlying economic assumptions.

For insurers, one key area to monitor is refinancing and structural risk within securitized markets. If interest rates remain elevated or spreads widen materially, refinancing conditions could become more challenging, particularly for datacenter-related securitizations that depend on long-term capital market access. In some cases, projects may require additional equity support, which can be difficult to secure when third-party investors, rather than original sponsors, hold ownership stakes. These dynamics increase completion, utilization, residual value, and refinancing risks across certain structures. Going forward, outcomes may increasingly depend on bottom-up security selection, the adequacy of risk compensation, and the ability to differentiate between AI-branded projects and those supported by durable economics, strong counterparties, and sustainable cash flow prospects.

Source: Bloomberg as of 8/18/26 unless stated otherwise. Chart 1: 2026 and 2027 Capital Expenditure Estimates are based on consensus estimates from Bloomberg as of 6/30/26. Chart 2: Sourced from Morgan Stanley as of 5/26/26. Chart 3: Hyperscaler OAS is a weighted average of MSFT, GOOGL, AMZN, META, and ORCL spreads within the Bloomberg Corporate Index. IG Corporate spreads are based on the Bloomberg Corporate Index. Securities listed above are for illustrative purposes only and are not a recommendation to purchase or sell any of the securities listed. The views contained in this report are those of Income Research + Management (“IR+M”) and are based on information obtained by IR+M from sources that are believed to be reliable but IR+M makes no guarantee as to the accuracy or completeness of the underlying third-party data used to form IR+M’s views and opinions. This report is for informational purposes only and is not intended to provide specific advice, recommendations, or projected returns for any particular IR+M product. No part of this material may be reproduced in any form, or referred to in any other publication, without express written permission from Income Research + Management. This is not a recommendation to purchase or sell any of the securities or issuers in sectors listed above. “Bloomberg®” and Bloomberg Indices are service marks of Bloomberg Finance L.P. and its affiliates, including Bloomberg Index Services Limited (“BISL”), the administrator of the index (collectively, “Bloomberg”) and have been licensed for use for certain purposes by IR+M. Bloomberg is not affiliated with IR+M, and Bloomberg does not approve, endorse, review, or recommend the products described herein. Bloomberg does not guarantee the timeliness, accurateness, or completeness of any data or information relating to any IR+M product

Source: Strategic Asset Alliance, Income Research + Management. The information contained herein has been obtained from sources believed to be reliable, but the accuracy of information cannot be guaranteed.