How Big Tech’s AI Debt Could Raise Euro-Area Borrowing Costs

U.S. technology giants are becoming more important borrowers in Europe just as the cost of building AI infrastructure is rising. For now, their outstanding euro-denominated debt is limited relative to the overall market. The risk is that a handful of similarly exposed, highly rated companies become major recurring issuers quickly enough to affect the price and availability of credit for other borrowers. 1

Why AI spending is bringing Big Tech to Europe’s bond market

Alphabet, Amazon, Meta, Microsoft and Oracle are projected to require more than $1 trillion in combined capital expenditure by 2028, according to the European Central Bank’s analysis. The spending is tied to AI-related infrastructure, including data centres and the energy infrastructure needed to support them. 1

The companies have increasingly used euro-denominated bonds as part of their funding mix. They have around €40 billion of such bonds outstanding, represent slightly more than 1% of benchmark euro corporate-bond indices, and account for just under 10% of gross new issuance by non-financial companies. Their share of euro-denominated “reverse Yankee” issuance—debt sold in euros by non-euro companies—nearly doubled between 2025 and 2026. 1

That contrast matters: the existing stock is still modest, but the flow of new issuance is already large enough to influence a market segment.

1. More supply can push borrowing costs higher

Bond markets must absorb new debt. If large, frequent deals from highly rated technology companies add materially to supply, investors may demand higher yields to hold the additional duration and credit exposure.

That pressure need not remain confined to the technology issuers. Corporate borrowers seeking funding at the same time may face higher coupons or less attractive terms. Reuters, reporting on the ECB analysis, said the effect could extend to governments as broader market pricing adjusts. 2

The mechanism is not that every euro-area sovereign directly competes with Big Tech for the same bond buyer. Rather, a sustained rise in corporate yields can alter investors’ required returns and market conditions more broadly.

2. Other companies could be crowded out of issuance windows

Large, well-known borrowers can draw substantial investor demand, particularly when they offer liquid, investment-grade bonds. If hyperscalers continue to take a sizable share of the new-issue calendar, European industrial, utility, financial and smaller corporate issuers may have less favourable opportunities to raise money.

They could be pushed toward issuing at a different time, accepting a higher coupon, shortening or extending maturities, or reducing the size of a deal. This is the practical meaning of crowding out: not necessarily an inability to borrow, but borrowing on worse terms or with less flexibility. 12

3. Benchmark tracking could deepen concentration

The ECB notes that hyperscaler bonds already make up slightly more than 1% of benchmark indices for euro-denominated corporate bonds. 1 If their debt stock grows, their index weight can grow too.

That matters for passive funds and exchange-traded funds designed to follow those benchmarks. Such investors may have to buy more of the issuers’ bonds as their weights rise, regardless of whether spreads fully compensate for the risk. The result can be greater portfolio concentration in a small group of U.S. technology companies and less room for other issuers in benchmark-driven portfolios.

4. A rapid increase could test investor capacity and liquidity

Around €40 billion outstanding is manageable in normal market conditions. The bigger question is whether investors can comfortably absorb a much faster stream of large deals while the same companies collectively pursue more than $1 trillion in capital expenditure by 2028. 1

A market that absorbs issuance smoothly in calm conditions can become more fragile when risk appetite falls. If several closely related issuers need to borrow or investors want to reduce exposure at the same time, secondary-market liquidity may be tested. Large transactions can be difficult to execute without moving prices when dealer balance sheets and buyer demand are constrained.

5. Strong ratings may not eliminate AI-investment credit risk

The hyperscalers generally enter this period with strong credit profiles. But bond valuations and ratings ultimately depend on assumptions about future cash flow, capital spending and leverage.

The credit risk could be underpriced if AI-related revenue arrives more slowly than expected, infrastructure spending stays high for longer, or competitive pressure weakens margins. In that scenario, debt could rise faster relative to earnings and cash flow than investors currently anticipate. Spreads could widen, bond prices could fall and ratings could face pressure. The ECB has flagged the possibility that rising leverage and shared investment risks could increase vulnerabilities. 12

6. Different issuers may still share the same shock

Holding bonds from Alphabet, Amazon, Microsoft and other hyperscalers can appear diversified at the issuer level. Yet their AI investment plans share important exposures: demand for AI services, data-centre buildout, energy costs, regulation and the broader technology cycle.

If a common assumption changes—for example, if expected returns on AI infrastructure disappoint—several issuers could face a similar reassessment at once. That correlation is central to the concern: a group of individually strong borrowers can still create a concentrated risk in a market when they borrow heavily at the same time. 1

The key takeaway: vulnerability, not a forecast of crisis

The available evidence does not imply that Big Tech borrowing will cause a euro-area bond-market crisis. The companies’ current credit quality and their still-limited share of the outstanding market are meaningful buffers. 1

But the direction of travel deserves attention. A small cohort of U.S. companies already accounts for almost one-tenth of gross new euro corporate issuance, while projected AI capital expenditure exceeds $1 trillion through 2028. If borrowing accelerates, the consequences could reach beyond technology: higher financing costs, tougher issuance conditions for European companies and a more concentrated corporate-bond market. 12