Tether CEO warns AI infrastructure capex sustainability hinges on four critical economic mismatches.

Tether CEO Paolo Ardoino warned today on X that Big Tech's AI data center buildout relies on subsidized computing and hardware that depreciate within three to five years, exposing the sector to four structural mismatches. His concern reflects a mounting anxiety across the industry: hyperscalers are investing record sums while producing no clear return on investment.

Ardoino argues that AI companies subsidize computing to attract users while sinking capital into infrastructure with only a three- to five-year lifespan. The numbers are staggering. JPMorgan's June 24 midyear outlook raised its forecast for global AI-related capital spending through 2030 to $5.5 trillion, up from $5.1 trillion, and projects AI-related debt financing will reach $4.1 trillion. The bank predicts hyperscaler capital spending will hit $650 billion this year and exceed $1.1 trillion in 2027. Microsoft alone plans to spend about $190 billion in 2026—a 61% increase year-over-year.

Goldman Sachs estimates that Meta, Microsoft, Amazon, and Alphabet will collectively spend $5.3 trillion on capital expenses between 2025 and 2030, with $725 billion planned for this year, 77% more than last year's $410 billion. Alphabet raised $84.75 billion for AI infrastructure, described as the largest US equity capital raise ever.

Yet profitability remains elusive. The average company will spend $11.5 million on AI this year without demonstrable returns. Data from the Bureau of Economic Analysis shows Information sector growth slowed to 1.5% in Q1 2026 from 3.2% in Q3 2025. Companies that previously encouraged "tokenmaxxing"—maximizing employee AI usage—are now retreating as CFOs question rising API costs. Amazon dropped its internal AI usage leaderboard, Uber exhausted its 2026 AI coding budget in four months and capped monthly employee spending at $1,500, and Meta warned 6,000 staff about rapidly escalating costs.

IDC projects that by 2028, 70% of leading AI adopters will use multiple models rather than a single vendor, potentially igniting a price war. Regulators are alarmed: the Bank for International Settlements identified AI investment volatility as one of three primary economic risks, warning in its annual report that a sharp correction could destabilize global equity markets more severely than past recessions. Zhang Tao, BIS chief representative for Asia and the Pacific, cautioned that "the speed of a correction could be much faster than previous banking crisis episodes."

Not all analysts share this pessimism. Wedbush's Dan Ives calls the buildout "an arms race" no major company can avoid, predicting profitability within six to twelve months. JPMorgan forecasts operating cash flow will exceed $900 billion by 2027. Great Hill Capital's Thomas Hayes struck a middle ground, suggesting one or more major companies may announce lower capital spending in the coming earnings season—a crucial test of Ardoino's thesis.