Tech Selloff Threatens Trump Economy as $700 Billion AI Buildout Faces Fed, Profitability Doubts
Updated
Updated · POLITICO · Jun 23
Tech Selloff Threatens Trump Economy as $700 Billion AI Buildout Faces Fed, Profitability Doubts
3 articles · Updated · POLITICO · Jun 23
Summary
Wall Street’s tech pullback is raising concern that a weaker AI trade could hit the spending power of wealthy households and spill into the broader U.S. economy.
More than $700 billion in AI capital spending this year has helped prop up growth, but investors are questioning when hyperscalers such as Amazon and Google will earn returns on costly data-center expansion.
Kevin Warsh’s hawkish inflation stance has added pressure by increasing the risk of higher borrowing costs for AI firms, while cheaper alternatives such as China’s DeepSeek have sharpened doubts about pricing power.
The concern matters politically for Donald Trump, who has touted AI and factory construction as economic proof points even as consumer sentiment remains weak.
Even after recent losses, the Nasdaq 100 is still up more than 16% this year, and some analysts say the selloff looks more like profit-taking than a collapse in AI demand.
With AI spending soaring while profits lag, is the global economy witnessing the inflation of a new tech bubble?
If AI raises living costs now and threatens jobs later, who are the real beneficiaries of this technological boom?
As AI models learn to exploit security flaws, are we building a technology that we ultimately cannot control?
$700 Billion AI Bet: Tech Selloff, Profitability Doubts, and the High-Stakes Future of Artificial Intelligence (June 2026)
Overview
In June 2026, the technology sector faces a sharp selloff and heightened volatility as investors question the immediate returns on massive AI infrastructure spending by giants like Amazon and Alphabet. Despite unprecedented capital outlays, markets remain supply-constrained and are struggling to reconcile these investments with current economic realities. Doubts about profitability are growing, especially since most enterprise AI pilots have yet to deliver measurable financial impact. While agentic AI is seen as a future solution, widespread adoption is still at least a year away. This situation echoes past periods of heavy infrastructure investment, leaving the market uncertain about when real returns will materialize.