The massive AI buildout requires significant capital. As AI-related debt is becoming a meaningful source of new investment grade (IG) bond supply, investors are increasingly alert to new opportunities as well as new risks, including concentration risk.
Total investment in U.S. data centers and AI infrastructure is projected to reach $10.3 trillion from 2025 to 2032.2 Large technology companies are increasingly turning to bond markets to help fund that investment.
The market value of AI-related debt outstanding is the third largest sector within the U.S. IG market and could challenge the Banking sector market value in the IG Index within the next two years (See Figures 1 and 2.)
Other sectors with revenue related to the AI infrastructure buildout include Banking, which provides underwriting, lending, and structuring activities to the AI ecosystem. These activities boost revenue but may increase balance sheet exposures. Life Insurers’ AI-related investments account for about 1.4 percent of the industry’s total investments, which are modest at this stage, but could grow.3
Select Capital Goods companies have double-digit revenue exposure to AI infrastructure related to materials needed for the data center (DC) buildout.4 In the Energy sector, Midstream companies are developing DC power solutions.
Utility capex and bond issuance is forecast to track rising electricity demand.5 Utilities have exposure to the AI infrastructure buildout through contracted power for data centers and we monitor exposures through a percentage of capacity and/or revenues.
DC bonds are single or multi-asset project financings that involve constructing a shell that will house compute for the purposes of AI, often tenanted by Hyperscalers.6 IG-rated DC bonds outstanding are about $70 billion.7
As AI-related capital expenditures and bond issuance grow, we are actively seeking investment opportunities, given the credit spread widening in related sectors this year. In addition, we also continue to manage direct and indirect AI concentration risk exposures.8
Since our founding more than 30 years ago, we have employed essential disciplines that are intrinsic to our investment philosophy and are well-aligned with our efforts to manage risk, including concentration risk, in our clients’ portfolios.
Specifically, we believe our commitment to rigorous bottom-up research, active portfolio management, and issuer, sector, maturity, and duration diversification help to mitigate potential concentration risks, including those that may arise as the AI buildout advances.
Long experience strengthens our capabilities in key risk-aware management disciplines. For example:
- Rigorous bottom-up research: More debt means credit selection becomes increasingly important. Higher capital spending can pressure free cash flow, while greater reliance on debt can strain balance sheets and credit metrics over time. Most IG-rated, AI-related borrowers remain highly rated and able to service additional debt today, but our corporate security analysis and research team monitors the trend on a day-to-day basis.
- Active portfolio management: Active fixed income managers are accustomed to concentration risks, having dealt with them for years in Banking and outsized tickers across other sectors. Active managers do not need to match the passive Index, creating strategic opportunities to underweight or overweight large or small sectors, while maintaining overall portfolio risk targets. We manage issuer and sector concentrations through setting sector and issuer risk limits, incorporating the views of our investment team.
- Focus on IG bonds: The IG corporate bond market is typically accommodative to highly rated AI issuers, although spread widening and higher borrowing costs are headwinds. Still, most issuers look poised to continue to borrow in unsecured corporate bond markets. Lower-rated Hyperscalers and high-yield issuers have seen the sharpest spread widening. These entities have less financial flexibility than higher-rated Hyperscalers and may seek out secured financing.
- Issuer, sector, maturity, and duration diversification: With an average maturity longer than the Bloomberg U.S. Corporate Bond Index (the Index) and elevated credit spreads, the relative size within the Index of the AI complex is expected to increase. This AI investment cycle is not just about how much debt is being issued, as some issuers have mitigated credit and leverage impacts by issuing hybrids and common equity. It is about identifying the issuers that can absorb additional debt, avoiding issuers whose credit profile may deteriorate, and trying to find the best relative value for investors.
Discerning Opportunities Among Wider Sector Spreads
So far in 2026, a deluge of bond supply has pushed spreads wider and driven underperformance across the AI complex. Technology (+33 basis points (bps)), Retailers (+22bps), Media Entertainment (+59bps), and Cable Satellite (+85bps), have seen greater credit spread widening vs the Index (+13bps), where Hyperscalers and AI issuers reside.9,10 Spread tightening has primarily been limited to Energy (-11bps) a sector, which has benefited from high oil and gas prices while higher-quality, defensive sectors such a Consumer Non-Cyclical (+2bps) have seen a negligible change in credit spreads. (See Figure 3).
Volatility and spread underperformance in the AI complex are driven primarily by supply indigestion, credit default swap (CDS) hedging activities, and longer-term credit concerns. We expect opportunities to emerge in more resilient issuers. As we discern investment opportunities among newly issued and secondary market corporate bonds moving forward, our long experience in risk-aware management disciplines will continue to support our corporate bond research and portfolio management efforts.
[1] The AI complex includes the following sectors: Technology, Retailers, Media Entertainment, Data Centers, and Cable Satellite. “Hyperscalers” use DC infrastructure to deliver cloud computing, storage, and digital services.
[2] “The AI Build-Out Is Becoming the Biggest Economic Bet in U.S. History,” The Wall Street Journal, September 23, 2026.
[3] Moody’s Investor’s Services, U.S. Life Insurers Increase AI Investments as Exposure Risks Grow, 23 October, 2026.
[4] Morgan Stanley Research, Following AI’s $1.6 trillion Money Trail, 15 October 2026.
[5] Breckinridge Capital Advisors, Quantifying Power Demand from Artificial Intelligence, 15 January, 2026.
[6] Hyperscalers are large cloud service providers that own and operate outsized global data centers that offer on-demand computing, storage, and networking resources.
[7] Barclays Research, Data Center Bond Comp Sheet, IG and HY AI Data Center Bonds Outstanding were $70 billion and $46 billion, respectively, 20 October 2026.
[8] Strategies intended to identify, monitor, diversify or otherwise manage exposure to AI-related issuers, sectors or investments may not be effective. The growing integration of AI-related spending, financing, infrastructure, energy demand and revenues across the broader economy and fixed income market may create direct and indirect exposures that are difficult to identify, measure or mitigate. Correlations among issuers and sectors may increase during periods of market stress, and portfolio diversification may provide less protection than expected. Accordingly, efforts to manage AI concentration risk cannot eliminate the risk of loss or ensure that a portfolio will avoid adverse effects associated with a slowdown, repricing or disruption in AI-related investment.
[9] Bloomberg IG Corporate Bond Index Option-Adjusted Spread (OAS) Data, October 26, 2026.
[10] Breckinridge Capital Advisors, The Price of AI: How Capex is Rewriting Tech Balance Sheets, 24 April, 2026.
Request #501755 (11/2/2026)
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