The AI trade is acquiring a new kind of leverage: debt.

UBP estimates Microsoft Corp (MSFT), Amazon.com Inc (AMZN), Alphabet Inc (GOOGL) (GOOG), Meta Platforms Inc (META) and Oracle Corp (ORCL) could spend $1 trillion to $1.3 trillion on capital expenditure in 2027, pushing AI financing far beyond the stock market and deeper into global credit markets.

AI Spending Outruns Cash

The numbers explain why borrowing has become unavoidable.

UBP estimates the five hyperscalers will spend roughly $820 billion on capex in 2026, compared with about $750 billion in operating cash flow. In 2027, projected spending rises to $1 trillion to $1.3 trillion, creating a financing gap that earnings alone cannot cover.

Bonds are taking much of the load, but they are no longer the only source of capital. UBP points to project finance, securitization, leveraged loans and chip-backed financing as additional channels supporting the AI buildout.

The Financial Times adds another measure of the scale: Goldman Sachs estimates investors have provided roughly $500 billion of financing to AI-linked groups this year. The five hyperscalers account for about $200 billion of that figure and could issue more than $1 trillion of additional debt over the next few years.

AI Is Changing Credit Markets

The ECB says hyperscalers issued more than $100 billion of bonds last year and now account for close to a tenth of new euro bond issuance by non-financial companies. Its analysis warns that a continued borrowing wave could eventually force other companies to compete harder for investor capital.

The market is already seeing signs of that adjustment. Some companies are timing bond sales around hyperscaler issuance or shortening maturities to avoid competing directly for demand, the FT reported. Even sovereign debt managers are reportedly watching the timing of major technology deals.

The result is a feedback loop: AI requires more infrastructure, infrastructure requires more capital, and more borrowing increases the supply of bonds investors must absorb.

The Risk Moves Beyond Stocks

Credit investors are increasingly financing the same companies, data centers, chips and power infrastructure supporting the AI boom. UBP estimates the five hyperscalers' cumulative investment could reach $5.6 trillion through 2030, while the FT notes that riskier AI infrastructure companies such as CoreWeave, Inc. (CRWV) are also tapping high-yield markets.

That creates a wider test for the AI investment thesis. The boom ultimately has to generate enough operating cash flow to support the infrastructure being financed today. If spending keeps accelerating while returns lag, the pressure would show up not only in stock valuations, but also in bond spreads, borrowing costs and future capex decisions.

For investors, the next AI catalyst may therefore come from the credit market rather than the Nasdaq: whether the world's biggest technology companies can turn extraordinary capital spending into the cash flow needed to finance the next phase of the boom.