Artificial intelligence is now a capital markets story

By Mallika Khoobarry, Fixed Income Specialist

• We believe AI can support productivity growth over time. The credit market is now financing the infrastructure required for those future gains, drawing increased attention to execution, utilisation and cash-flow visibility.
• Technology has become a larger share of both investment grade and high-yield credit markets, with sector weightings and issuance volumes rising over the past year.
• The AI theme is more attractive for equities, where investors can benefit from AI-driven growth and value creation. For credit, upside is limited by current spread levels, while downside risks remain if AI investments fail to deliver expected returns.

AI has been a significant force in financial markets in recent years. It has supported earnings, driven market leadership and helped sustain investor enthusiasm. To date, it has largely been an equity story, with valuations reflecting future growth expectations, productivity gains, and new revenue pools.

But AI is no longer solely a story about models, applications, and productivity. It is increasingly about physical infrastructure: chips, data centres, power, grid connections, land, and construction. 

That matters for investors. When a technology theme starts competing for infrastructure, it progresses from a software story to a capital cycle — one that creates value but demands disciplined financing and clear returns. At this stage, it also becomes more relevant for credit markets, as funding requirements expand and the focus on cash-flow grows.

Estimates for AI-related investment now run into trillions of dollars. Analysts forecast that the five largest US hyperscalers could spend more than $4.5 trillion in capital expenditures (capex) over the next five years, with roughly $3.2 trillion financed through capital markets, according to Bloomberg consensus estimates.

The spending is front-loaded. Companies are investing today to secure capacity, scale advantages, and market share, while productivity gains and monetisation are expected to build over time. That timing gap is why capital markets are becoming central to the AI story.

The value of investments, and the income from them, can fall as well as rise and you may not get back what you put in. Past performance should not be taken as a guide to future performance. You should continue to hold cash for your short-term needs. This article should not be taken as advice.

Capex is absorbing more free cash flow

The first phase of the AI build-out was largely funded from existing operations. The largest technology companies entered this cycle with high margins, strong balance sheets, and significant free cash flow.

That remains broadly true. The leading hyperscalers are still highly profitable, and many continue to have strong financing flexibility. However, capex intensity has risen sharply. Free cash flow has not disappeared; rather, a larger share of it is being redirected towards AI infrastructure.

AI is moving from an operating growth story funded through free cash flow (FCF), where internally generated cash is reinvested into the business, to a broader capital markets story. This means investors should pay closer attention to the funding mix, borrowing costs and returns on invested capital.

AI is becoming an infrastructure story

The second shift is that a growing proportion of capex is dedicated to physical infrastructure, with grid connection delays and other supply chain constraints slowing deployment. Infrastructure bottle necks are changing not only what is being built, but when returns are realised.

This changes the investment profile. AI capex supports near-term growth through construction, semiconductors, electrical equipment, engineering services, power infrastructure and real estate. But infrastructure projects typically have longer lead times, higher upfront costs and more gradual revenue realisation than software.

We believe AI can support productivity growth over time. However, the market is now financing the infrastructure required for those future gains and that raises the importance of execution, utilisation and cash-flow visibility.

Credit markets are becoming part of the theme

The financing mix is wide, ranging from equity and corporate debt to securitised markets financing data centres, and private markets investing infrastructure capital for complex or longer-duration projects.

Within public credit markets, this broadening is already visible in issuance patterns. Technology has become a larger share of both investment grade and high yield credit markets, with sector weightings and issuance volumes rising over the past year.

Off-balance sheet financing structures have also expanded rapidly as companies benefit from funding while preserving balance sheet flexibility. However, for bond investors this adds complexity, making it harder to gauge the true scale and timing of obligations.

This broadening is a positive feature of the cycle. It reduces reliance on any single funding channel and helps explain why markets have successfully absorbed supply so far. Issuers have diversified across currencies, maturities, structures and investor bases rather than relying on one large wave of public borrowing.

But valuation still matters. Credit investors are increasingly being asked to help finance AI infrastructure. The debate is less about whether AI can transform the economy and more about when that transformation becomes visible in financial returns. In our view, current spreads do not fully compensate for the uncertainty around timing, execution and utilisation.

Equities and credit: different implications

AI capex has different implications for equities and credit.

For equities, the theme remains attractive. Equity investors participate in the upside if AI adoption accelerates, revenues grow, margins expand and scarce assets such as compute, data, and power capacity command higher economic rents.

Credit investors receive coupon and principal. At current spreads, they do not participate meaningfully in the upside if AI monetisation is stronger than expected. But they are exposed to the downside if free cash flow weakens, refinancing conditions tighten, projects are delayed or utilisation disappoints.

That asymmetry is not a reason to avoid AI-related credit altogether. Many large issuers remain fundamentally strong and have managed their financing carefully. It does, however, argue for selectivity.

Our interpretation: a powerful theme, but not a free lunch

While AI capex remains central to the long-term investment case, the next phase requires investors to look beyond the growth story and assess how efficiently capital is deployed, financed, and converted into cash flow. AI should be analysed both as a technology theme and a capital cycle.

For equities, we remain constructive on the long-term opportunity, while recognising that concentration and valuation require discipline. Equities offer a clearer route to participate in the upside if AI adoption accelerates and returns on investment materialise.

For credit, investors need to be more selective, favouring higher-quality issuers, clearer collateral, stronger cash-flow support, and adequate compensation for the risks being taken.