AI hyperscalers must boost productivity 2.7× to justify $1.1 trillion data‑center spend by 2030

The hyperscalers—Alphabet, Microsoft, Amazon, Meta and Oracle—are already pouring about $750 billion into AI infrastructure this year, with projections of more than $5 trillion over the next four years. Yet current AI revenues sit at $150‑200 billion, creating a massive gap. If demand for compute stalls, the borrowed capital and rapid depreciation of GPU assets could turn these massive facilities into stranded, debt‑laden “hulks,” threatening both the companies and the broader financial system.

Economists warn that without measurable productivity gains across the economy, the AI gamble could become the largest capital misallocation in history, risking bankruptcies, tighter credit, and public backlash as jobs are displaced.