Tether CEO warns Big Tech's $5.5 trillion AI bet risks Bitcoin contagion

Tether Chief Executive Paolo Ardoino warned July 4 that Big Tech's artificial intelligence spending binge, projected to reach $5.5 trillion by 2030, risks a correction that could spread to Bitcoin and other risk assets.

"The capital being deployed into AI infrastructure is not matched by the timeline to profitability, and open-source models are eroding the pricing power that was supposed to justify these investments," Ardoino said.

Ardoino identified four specific mismatches: compute token prices that do not reflect true costs, a gap between upfront investment and profitability timelines, capital maturity structures misaligned with hardware lifespans of three to five years, and open-source AI models undercutting commercial revenue projections. Hyperscaler capital expenditures are expected to climb to $725 billion in 2026, a 77% year-over-year increase, before reaching $1.1 trillion in 2027, according to JPMorgan estimates. Goldman Sachs projects that four companies — Microsoft, Meta Platforms, Amazon and Alphabet — will account for roughly $5.3 trillion in combined spending between 2025 and 2030.

The warning carries weight because of its source. Ardoino first flagged the AI bubble as the biggest risk to Bitcoin in December 2025, arguing that a sharp correction in AI stocks could trigger margin calls on institutional portfolios holding both Nvidia shares and Bitcoin, forcing simultaneous selling across correlated assets. Tether, which manages the world's largest stablecoin, has been investing in AI infrastructure through its QVAC initiative.

The scale of the spending is unprecedented. Global AI-related spending could hit $5.5 trillion by 2030, JPMorgan projects, while the Bureau of Economic Analysis reported that growth in the information sector slowed to just 1.5% in the first quarter of 2026. Companies including Amazon and Uber have internally pushed back on rising AI-related costs.

For crypto investors, the transmission mechanism is direct. Institutional portfolios that hold both AI equities and Bitcoin would face margin calls if AI stocks correct sharply, forcing liquidations across asset classes. Traders should watch hyperscaler earnings for signs of deteriorating returns on AI capital expenditure and monitor whether open-source model adoption accelerates enough to undercut commercial AI pricing, Ardoino said.

The 77% year-over-year jump in planned AI spending for 2026 leaves little margin for error if revenue growth fails to materialize, he added. BlackRock's 2026 midyear outlook identified the AI buildout as an accelerating theme, noting that physical infrastructure requirements — power, memory, chips and data centers — remain constant regardless of which model architecture wins the competitive race.

This article is for informational purposes only and does not constitute investment advice.