AI Bubble Risks Burst as Tech Limits Emerge, Analysts Warn

Over the past five years, AI has shifted from a science-fiction concept to an embedded part of daily life, integrated into search engines, phone applications, and business operations. This rapid adoption has fueled investor enthusiasm, with billions flowing into a small set of tech giants. However, the article outlines a critical inflection point: as companies deploy AI more widely, the gap between advertised capabilities and actual performance is becoming visible to both users and operators.

The bubble risk centers on what Jeremy Grantham calls the "utility fallacy"—a pattern observed with railways and the internet, where overinvestment follows an initial wave of innovation, but profits ultimately concentrate in the companies that build services around the infrastructure, not the infrastructure providers themselves. The article suggests AI is following this same trajectory: consumers and businesses have been impressed by AI's apparent intelligence, but practical deployment reveals significant limits. Users are losing confidence as AI's limitations surface; manufacturing firms experimenting with AI automation discover that the technology cannot handle the real variability and complexity of production environments—supplier delays, equipment failures, demand swings, and regulatory rules—all of which fall outside the stable, repeatable scenarios where AI currently performs reliably. This mismatch between investment appetite and operational reality is what prompts analysts to forecast a correction.