Goldman Sachs Warns AI Capital Spending May Hit Credit Saturation; Hyperscalers Face $5.3 Trillion Financing Gap Through 2030

According to Goldman Sachs, capital expenditures by hyperscalers on AI and data centers from 2025 through 2030 will reach $5.3 trillion, the largest capital spending cycle on record. The report warns that these cloud giants will face potential saturation in liquidity credit markets as they seek financing. Morgan Stanley estimates that by 2028, global data center capital expenditures will approach $2.9 trillion, with funding sources including $1.4 trillion in internal cash flow, $200 billion in corporate bonds, and approximately $2.3 trillion in credit and other financing—indicating significant debt reliance.

Meanwhile, corporate spending on AI is showing signs of restraint. Uber exhausted its annual AI budget by April and implemented a $1,500 monthly limit per employee on AI tool usage, with president Andrew Macdonald stating it has become increasingly difficult to establish clear causality between spending and actual product benefits. Walmart similarly capped internal AI assistant usage, according to global CTO Suresh Kumar. The pullback reflects shifting billing models, as Anthropic and OpenAI transitioned from subscription to token-based pricing, making enterprises more cost-conscious about each query and automated process.