Déjà vu: AI’s debt binge draws European telco parallels

AI is rewriting the rules of capital markets – but at what cost? In 2025, ‘hyperscalers’ including Amazon, Google, Meta and Microsoft are fuelling an unprecedented surge in equity and debt issuance to bankroll massive AI-driven capital expenditure. While their credit ratings remain pristine today, history warns that even the biggest names aren’t immune to the pressures of aggressive, debt-fuelled growth.

Certainly, 2025 will go down as yet another year dominated by the growth of the major technology companies, with AI-themed investments headlining a surge in equity and debt capital market activity. 

Much of this activity is funding burgeoning AI capital expenditures, with further significant growth expected in the coming years as the major technology players make an almost 5x increase in combined capital outlays over the 7 years to 2028 (refer to Chart 1).

Chart 1. AI ‘Hyperscalers’ – Annual Capex Expenditures (Actuals and Estimates, $USbn)

Aside from growth in capital expenditure fuelling equity prices and underpinning US economic growth, the major global technology players are increasingly turning to debt markets for funding. Mega debt deals CYTD are already many multiples of previous annual totals, with the prospect of much more debt issuance to come (refer to Chart 2).

Chart 2. AI Tech Giants – Borrowings (Bonds and Loans, $USbn)

Renowned for their creditworthiness and strong cash flow generation, the AI hyperscalers appear very well placed to manage increased debt on their balance sheet. But everything, including even AI, has its limit. 

Given that capital expenditures are expected to accelerate further over the outlook, we may very well reach the theoretical limits of debt funding in the years ahead without significant downgrades in credit quality, even for such illustrious names as Amazon, Google, Meta, and Microsoft.

To date, credit markets have absorbed large sums of new debt from AI companies, but higher CDS pricing is beginning to reflect some indigestion across the sector. This is especially the case for triple B-rated Oracle (refer to Chart 3). Going forward, further debt capital issuance is likely to further pressure credit spreads. 

Chart 3. CDS Spreads – US Technology Companies (bps)

For those of us in credit markets, major events can often be eerily similar to historical periods. From our perspective, highly rated AI companies increasingly tapping debt markets to fund burgeoning capital expenditures bears an uncanny resemblance to the early 2000s, where similarly rated European telcos (massively) overpaid for 3G spectrum licenses and associated infrastructure. 

In the second half of 2000, the likes of Deutsche Telekom (DT), Orange S.A. (France Telecom), British Telecom and Vodafone, etc., used debt funding to pay European governments more than $US100 billion for 3G spectrum licenses on the lucrative early promise of the ‘Internet of Things’ (IOT) age.

As we now know, those roads to 3G riches were more potholed than expected, with associated debt issuance and lower-than-expected returns leading to significant negative credit migration and much higher credit spreads. 

For instance, the spreads of Credit Default Swap – insurance against default – for DT peaked at 400bps in 2002 (refer to Chart 4) and its credit rating declined from a high of AA- in 2000 to a low of BBB+ in 2004. It still resides there some 20 years later.

Chart 4. CDS Spreads – European Telcos (bps)

The history books confirm that credit investors incurred significant marked-to-market (M2M) losses funding Europe’s 3G capital expenditure binge in the 2000s, with a sense of Déjà vu now on the horizon for AI investors. 

While current credit quality – as assessed by S&P – for the likes of Meta (AA-), Amazon (AA), Alphabet (AA+) and Microsoft (AAA) is unquestionably pristine, if the past experience of the European telcos are anything to go by, their credit quality is unlikely to remain so. We believe the credit ratings of hyperscalers in the years ahead are likely to migrate down to single A and maybe even triple B categories.

Credit investors buying the bonds of hyperscalers should clearly be factoring in future credit migration risk into new issuance credit spreads, which for the most part does not appear to be occurring. 

For instance, Meta recently issued $US13bn (total) across 10 and 30-year tranches at Treasuries +78 and 98bps, respectively. 

While you can debate whether the 10-year securities represent good value, we struggle to make any coherent argument in support of the relative value of the 30-year tranche, with any negative credit migration in the years ahead likely to lead to steep M2M losses.  

The likely current pricing and credit migration for hyperscaler bonds are illustrative of our portfolio management ethos. We always seek to maximise risk-adjusted returns, factoring in credit ratings with a forward-looking bias rather than at the issuance point in time. This ethos is consistently applied across all bond/credit funds and mandates including our Australian Bond, Enhanced Income and Higher Income Funds.

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