Can AI answer the $3 trillion question?

The article examines the massive financial gap between the trillions of dollars being spent on AI infrastructure and the revenue currently being generated by AI companies. Sequoia partner David Cahn, who first calculated the implications of AI spending in 2023, now estimates that AI infrastructure spending for 2026 will reach $1.5 trillion, requiring the industry to earn $3 trillion to justify the investment. This figure may be an underestimate due to rising costs. In contrast, Anthropic is thought to have hit $60 billion in ARR, while OpenAI reportedly earned $13 billion in 2025. The article highlights a risk identified by Apollo economist Torsten Slok: hyperscalers like Google, Meta, Microsoft, and Amazon are predicting massive accelerations in free cash flow by 2028, expecting a payback from their chip investments. However, the trend of organizations turning to cheaper open-weight models and falling token prices could threaten these goals. Slok warns that if hyperscalers fail to meet their cash-flow goals, the market reaction could be severe, potentially tipping the economy into a recession and the S&P 500 into a correction.