AI CRASH COULD DWARF DOT-COM BUST, WARNS NYU PROFESSOR

Damodaran identifies two critical vulnerabilities in the current AI boom. First, the industry's heavy reliance on expensive hardware and infrastructure creates substantial financial exposure. Unlike dot-com startups that could scale software with minimal capital, modern AI requires significant upfront investment in data centers, computing equipment, and research facilities—much of it financed through debt. Second, the professor flags a deeper structural problem: the core AI business model centers on job displacement. Even if AI technology succeeds as promised, widespread automation raises fundamental questions about societal impact and economic sustainability that remain unresolved. Damodaran's warning highlights the tension between AI's technological promise and its economic realities. The combination of heavy capital requirements and uncertain long-term business viability creates conditions for a sharper downturn than the 2000 tech crash if market expectations shift.