AI Spending Surge Threatens Credit Quality of Amazon, Meta, Alphabet and Others

The trillion‑dollar‑per‑year AI infrastructure push by high‑tech giants is now eroding the credit quality of Amazon, Meta, Alphabet and Microsoft, according to Moody’s.

Credit Pressure on the Balance Sheet

■Direct debt of $460 billion across six hyperscalers.

■Lease commitments climbing to $1.2 trillion, with a majority still under construction.

■Capital expenditures projected at $785 billion in 2026, rising to $1 trillion in 2027.

Expanding Capacity and Financing Tactics

■Alphabet recently raised $85 billion through an equity sale.

■Firms are leaning on long‑term data‑center leases to keep debt off their books.

■Heavy reliance on debt, equity, and off‑balance‑sheet financing is evident across the sector.

Lease Burden and Future Obligations

■$820 billion of lease commitments that have not yet begun.

■These are treated as debt‑equivalent liabilities, binding companies to significant future rent payments.

■Energy‑intensive hardware and large physical footprints amplify the long‑term financial load.

Evolving Risk Profile: Asset‑Heavy Shift

■Transition from asset‑light to asset‑heavy models increases capital intensity.

■Free cash flow faces pressure due to upfront hardware costs versus delayed revenue.

■Lower‑rated players like Oracle (Baa2, negative outlook) and CoreWeave (Ba3) carry heightened credit risk.

Circular Ecosystem and Industry Dependence

■Investments in pre‑IPO AI labs such as OpenAI and Anthropic create a feedback loop of cloud spending.

■The sector’s reliance on a narrow set of customers and demand assumptions raises systemic risk.

Takeaway for Investors

■Rising capex and lease liabilities demand a reassessment of expected returns.

■Credit ratings may remain stable for the largest names, but the overall risk environment is shifting.

■Energy consumption and infrastructure sustainability will become key metrics for credit health.

Markets must now watch the structural transformation of tech giants, focusing not only on balance sheets but also on how energy usage and data‑center investments affect long‑term creditworthiness.