The world's largest tech companies will spend more than $1.3 trillion on AI infrastructure by 2027, according to new research published by S&P Global Ratings on August 27, 2026. The report examines how six major hyperscalers—Alphabet, Amazon, Microsoft, Meta, Oracle, and SpaceX—are financing their aggressive push into artificial intelligence and what that spending spree means for their credit quality. The analysis reveals a sector racing to build computing capacity faster than it can generate cash from AI products.
All six companies are expected to burn through cash faster than they generate it in both 2026 and 2027, according to the report. S&P Global Ratings projects that every one of these hyperscalers will post negative free operating cash flow across those two years, with a turnaround not anticipated until 2029. To fund the buildout, the companies are increasingly turning to debt issuance, equity raises, lease agreements, and other financing mechanisms. The growing reliance on complex arrangements—including joint ventures, special purpose vehicles, and residual value guarantees—is making credit analysis more complicated.
"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. The report identifies several key risks that analysts are tracking: whether AI investments can be successfully monetized, how durable demand will prove, the possibility of overcapacity, and how to treat contractual commitments and other obligations that resemble debt. S&P Global Ratings states it will continue analyzing investment, financing, and monetization trends in the AI ecosystem and their effects on credit quality.
The ratings agency's models point to 2028 as the likely turning point, when revenue growth is expected to pick up speed while capital spending growth slows as companies begin earning more from their AI offerings. Until then, the hyperscalers face a cash crunch driven by the mismatch between massive upfront infrastructure costs and revenues that haven't yet materialized at scale. The report frames this as a critical period for the sector: companies are making billion-dollar bets on AI capacity before they've proven they can turn that capacity into profit. The complexity of financing structures—layering debt, leases, guarantees, and off-balance-sheet vehicles—adds another dimension of risk that credit analysts must now account for.
S&P Global Ratings expects the hyperscalers to moderate their spending growth and accelerate revenue generation starting in 2028, with free cash flow recovering by 2029. The bottom line: the world's most powerful tech companies are financing an infrastructure boom on borrowed money and future promises, and the next two years will test whether those bets pay off.