February 25, 2026
Where the Signal Is: Credit Opportunities in the Artificial Intelligence Infrastructure Build‑Out
KEY SUMMARY POINTS
- Artificial Intelligence (AI) is now driving market performance, shifting investor attention from software to the physical infrastructure powering Artificial Intelligence (AI).
- CI GAM fixed income is avoiding software credit due to high leverage, high valuations, and growing competitive risk from AI disruption.
- Private equity owned software firms face added strain from floating-rate debt and AI-related uncertainty.
- The strongest risk-adjusted opportunities are currently in companies building and enabling AI infrastructure, not in software providers.
Since the launch of ChatGPT in 2022, artificial intelligence has emerged as the dominant force shaping markets, with leading technology franchises linked to generative AI accounting for an estimated 65-75% of equity returns, profits and capital spending for the S&P 500.1 The speed and scale of this shift has been extraordinary. News flow has been constant, investment commitments have accelerated, and the competitive landscape continues to evolve, creating an environment where distinguishing durable signal from short-term noise has become increasingly challenging for investors.
In periods of rapid change, clarity and focus matter. From a cross-asset perspective, CI GAM remains anchored on where capital is being deployed, how it is financed, and whether the economic value created is sustainable. For credit investors in particular, understanding the use of proceeds is critical. Against this backdrop, attention has shifted beyond software itself toward the physical infrastructure that enables AI adoption: data centres, compute and power.
Software Disruption Through a Credit Lens
Within fixed income, we have maintained no exposure to software across our high yield and leveraged loan portfolios. This positioning reflects long-standing concerns around elevated leverage, particularly in the leveraged loan market, alongside rich valuations and increasingly optimistic assumptions around customer retention, pricing power and long-term customer lifetime value.
Recent developments have sharpened those concerns. A widely circulated example from Dave Clark, former CEO of Amazon’s Worldwide Consumer Division, highlighted how quickly AI tools are lowering barriers to entry in certain software categories. His ability to build a customized Customer Relationship Management (CRM) solution for a start-up over a single weekend illustrated both the potential of AI and the growing risk to business models predicated on recurring per-seat licensing and high switching costs. While writing code is becoming easier, maintaining secure, resilient and differentiated platforms remains far more complex.
Nonetheless, the direction of travel is clear. Assumptions that customers will automatically renew and expand contracts each year are increasingly being tested. This has prompted broader questions about how software companies will adapt: whether pricing models evolve toward consumption- or outcome-based structures, and whether traditional web-based interfaces persist or are gradually replaced by AI-driven agents operating in the background. These transitions may not be immediate, but they are no longer abstract. From a fixed income perspective, the appropriate response today may well be restraint. Unlike equity investors, fixed income is not as punitive for missing exponential upside. A six to eight percent coupon is fixed, and if the overall risk-reward profile of a company and its securities is unattractive, we are comfortable reallocating capital elsewhere.
Exhibit 1:
Source: PitchBook, Barclays Research as of February 2nd, 2026
Why Infrastructure Has Come into Focus
Where we are finding opportunity is in the infrastructure layer supporting AI growth. The expansion of data centres, compute capacity and power generation is not discretionary; it is a prerequisite for continued AI adoption and deployment. These assets tend to exhibit more tangible economic linkages, longer-dated contracts and, in many cases, hard-asset backing with clear replacement value. This is a theme where equity and credit perspectives converge. Equity investors focus on capital intensity, scalability and long-term returns on invested capital. Credit investors emphasize leverage, cash-flow durability, covenant protection and asset coverage. Facilitating AI growth, rather than being defined by it, results in a materially different risk profile. We are also seeing benefits extend beyond the technology sector. Businesses such as live sports, theme parks, industrial operators and logistics companies can be enhanced by AI-driven efficiency gains and data analytics without relying on aggressive monetization assumptions. In this respect, AI is an enabling force rather than the core investment thesis.
A Private Equity Overhang
At its core, the current re-rating of software credit is also a private equity story. Many private credit portfolios, including publicly traded Business Development Companies (BDCs), have significant exposure to software, often estimated near 20%. Historically, legacy software companies were attractive buyout targets due to high switching costs, predictable cash flows and opportunities for bolt-on acquisitions. This has increasingly become a vintage issue.
Many 2021 and 2022 buyouts were financed with floating-rate debt, leaving capital structures exposed as interest costs rose and growth slowed. The additional risk of AI-driven disintermediation has prompted a reassessment of equity values, lifting loan-to-value ratios and making refinancing more expensive or more complex. This adjustment is unlikely to resolve quickly and will likely unfold over several years as maturities approach.
Conclusion
At its core, the current re-rating of software credit is also a private equity story. Many private credit portfolios, including publicly traded BDCs, have significant exposure to software, often estimated near 20%. Historically, legacy software companies were attractive buyout targets due to high switching costs, predictable cash flows and opportunities for bolt-on acquisitions. This has increasingly become a vintage issue. Many 2021 and 2022 buyouts were financed with floating-rate debt, leaving capital structures exposed as interest costs rose and growth slowed. The additional risk of AI-driven disintermediation has prompted a reassessment of equity values, lifting loan-to-value ratios and making refinancing more expensive or more complex. This adjustment is unlikely to resolve quickly and will likely unfold over several years as maturities approach.
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1Michael Cembalest, Eye on the Market: Outlook 2026 – Smothering Heights (New York: J.P. Morgan Asset & Wealth Management, 2026).
About the Author
Brad Benson, Vice President, Portfolio Manager – Fixed Income, has over 22 years of industry experience and is responsible for high yield bonds, convertible bonds, and leveraged loans. Prior to joining CI GAM in 2007, Brad worked at CPP Investment Board in the Principal Investing Group. Before that, he held a role at RBC Capital Markets in the mergers and acquisitions department. Brad holds a Bachelor of Arts in Business Administration (Honors) from the University of Western Ontario and a Master of Science in Finance from the London Business School.
About the Author
Geof Marshall, SVP, Head of Fixed Income & Lead – Private Markets, joined CI GAM in 2006 and leads the fixed income group’s high yield team efforts in addition to leading the private markets group. Geof is also the lead manager on CI GAM’s income strategies, and co-manages the private markets and income & growth funds as well as a number of multi-asset fixed income portfolios. He brings over 25 years of valued industry experience to his role at CI GAM, especially in asset allocation and analyzing, managing and trading corporate bonds, leveraged loans, and private credit. Prior to CI GAM, Geof was a portfolio manager at Manulife Financial. Geof is a CFA charterholder with a Bachelor of Arts in Political Science from the University of Western Ontario. He is also a member of the CFA Society Toronto and sits on the Investment Committee at the Royal Ontario Museum.
About the Author
Jeremy Rosa, Vice-President, Portfolio Manager – Equities, joined CI GAM in 2006. He brings over 17 years of industry experience to his role and team as portfolio manager, US equity. Prior to this role, Jeremy led the research effort in the information technology sector for another Canadian asset manager. Jeremy holds the CFA designation, is a graduate of Financial Planning Management at George Brown College, and is a member of CFA Society Toronto.
About the Author
Carla Robinson is a Senior Investment Analyst covering Global Technology and Latin American equities. She joined CI Global Asset Management (CI GAM) in October 2023. Prior to joining CI, Carla gained 14 years of experience in equity research, covering Latin America, Eastern Europe, Middle East at Invesco (2016-2023) and Burgundy Asset Management (2006-2016). She has a master’s degree in Criminology and Sociology from University of Windsor.
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Leverage: An investment strategy of using borrowed money - specifically, the use of various financial instruments or borrowed capital - to increase the potential return of an investment.
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