We are witnessing one of the largest waves of investment spending in recent decades, with technology companies raising hundreds of billions through debt markets to finance AI infrastructure.
As a result, AI is not simply reshaping the economy; it is changing the composition, pricing and opportunities within global bond markets.
The scale of financing required to support AI infrastructure is driving a surge in bond issuance reminiscent of the infrastructure booms that accompanied previous industrial revolutions. What began as a niche technology story is becoming a meaningful fixed-income market story.
For bond investors, the implications extend far beyond simply financing growth. AI is changing who issues debt, how credit markets are constructed and where active investors may find opportunities.
The current landscape: Financing the AI revolution
The first stage of the AI revolution has been defined by the infrastructure required to support its growth. Explosive demand for AI-enabled services is driving a surge in expenditure as hyperscalers commit unprecedented sums to data centres, power infrastructure and chips, and increasingly rely on public bond markets to fund this expansion.
Since late last year, AI-related infrastructure debt issuance has surpassed $300bn, proving how technology issuers are becoming a significant portion of global credit markets.
What initially began as a US phenomenon is now spreading globally. As technology companies increasingly raise funding in international markets and investors pursue AI exposure, the impact of the AI capex boom is being felt across global credit markets.
Even companies with exceptionally strong balance sheets are borrowing at scale. This is changing the composition of credit markets, increasing the representation of large technology issuers within investment-grade benchmarks and potentially raising concentration risks for index investors.
For example, AI-related issuance has comprised around 18% of total investment grade (IG) issuance in the US IG market this year, but a very high 42% in the long-dated US IG markets. Therefore, traditional insurance companies and pension funds that invest more in longer-dated debt will be facing these concentration risks quite rapidly.
It is also changing market dynamics, where the opportunity is no longer simply to participate in attractive new issuance but to identify pricing dislocations that emerge across different maturities, currencies and structures as diverse investor groups compete for access to AI-related borrowers.
The evolution of the AI story
The AI story is no longer solely about spending levels. The focus is increasingly shifting from capital expenditure to competitive advantage. Companies are unlikely to adopt AI uniformly. Some will harness the technology to improve productivity, lower costs and strengthen market positions, while others may struggle to adapt.
As companies experiment with the technology and what it can do for them there is a dawning realisation of how AI could potentially change the way society currently conducts itself. Investors will become focused on the real-world impact of AI on earnings, margins and business models.
For credit investors, the downside risk from companies that fail may outweigh upside from winners. As a result, the ability to identify companies that are struggling to adopt AI could become just as important as those best positioned to benefit.
For example, there were equity market fears in the first quarter of 2026 over the impact of AI on software companies, where software developers’ businesses may be challenged by AI tools replicating their software.
There is a concentration of software companies, particularly in high yield US private credit. Therefore, investors have been concerned about potential contamination between US public market and private credit high yield.
Looking ahead
Historically, periods of disruption have been associated with greater divergence, and as AI adoption accelerates across industries, this pattern is likely to become more pronounced.
Differences in AI readiness could widen the gap between industry leaders and laggards, resulting in greater dispersion across credit markets and a richer opportunity set for active managers.
While geopolitical developments will continue to generate periods of market volatility, AI appears set to become a long-term structural force within fixed income.
The next chapter of the story will not simply be about how much companies spend on AI infrastructure, but which companies successfully use it to strengthen their competitive position. For bond investors, that distinction is likely to matter for years to come.
Matthew Rees is head of global bond strategies – unconstrained at L&G. The views expressed above should not be taken as investment advice.