Hyperscaler AI Spending to Hit $1.3 Trillion by 2027

The world's largest technology companies are embarking on an unprecedented infrastructure spending spree that will push their combined capital expenditures beyond $1.3 trillion by 2027, according to new analysis from S&P Global Ratings.

The credit ratings agency examined how six major hyperscalers—Alphabet, Amazon, Microsoft, Meta, Oracle, and SpaceX—are financing their AI infrastructure buildouts and what the investment cycle means for their financial health. The findings reveal a sector willing to accept years of negative cash flow in pursuit of AI dominance.

Cash flow pressures mount

S&P Global Ratings expects all six companies to generate negative free operating cash flow in both 2026 and 2027, with recovery not anticipated until 2029. This represents a significant shift for companies that have historically been cash-generating machines.

The scale of spending is forcing hyperscalers to tap multiple funding sources beyond traditional cash reserves. Companies are increasingly relying on debt issuance, equity raises, lease commitments, and complex financing arrangements to support their infrastructure investments, according to the report first published by S&P Global Ratings.

Financing complexity grows

The report highlights growing use of sophisticated financial structures including joint ventures, special purpose vehicles, and residual value guarantees. These arrangements are making credit analysis more complex, as traditional metrics may not fully capture the financial obligations companies are taking on.

"As AI infrastructure investment accelerates, the focus is expanding beyond the scale of spending to the funding models, financial commitments and long-term implications that accompany it," said Naveen Sarma, Managing Director and Sector Lead at S&P Global Ratings.

Why it matters

This spending wave represents one of the largest capital deployment cycles in technology history, but it comes with substantial execution risk. Companies are betting that AI monetization will eventually justify the investments, but S&P's models assume an inflection point won't arrive until 2028. Until then, investors and creditors face years of uncertainty around whether demand will materialize, how quickly revenues will grow, and whether the industry is building excess capacity. The financing structures being used to fund this buildout also create new forms of financial obligation that may not appear prominently on balance sheets, making credit quality harder to assess.

Key risks under watch

S&P Global Ratings identified several areas it will monitor closely: the pace of AI monetization, durability of customer demand, risk of overcapacity in the market, and how contractual commitments and debt-like obligations are treated in credit analysis.

The agency's baseline scenario assumes capital expenditure growth will moderate and revenues will accelerate starting in 2028 as companies begin generating meaningful returns from their AI investments. However, the two-year period of negative free cash flow represents a significant test of balance sheet strength across the sector.

The analysis was published in S&P Global Ratings' report "S&P Global Ratings' View On Artificial Intelligence And Hyperscalers" and does not constitute a rating action. Details were first reported by S&P Global Ratings.