AI Bubble Risk: Lessons from Dot-Com. Comparing Today's Elevated AI Valuations with Historical Technology Bubbles

The financial markets of 2024 show a concentration of valuations in companies linked to artificial intelligence that resembles, with unsettling precision, the multiples recorded at the peak of the dot-com cycle in 1999 and 2000. This book analyzes rigorously and without unnecessary alarm whether that similarity represents a real risk of deep correction or whether, on the contrary, current fundamentals justify such elevated premiums.

The reader will learn to identify the classic phases of a speculative technology bubble using the Minsky framework and the quantitative indicators that have preceded every major correction since 1987. They will understand in detail how the dot-com bubble developed, the overinvestment cycle in fiber optics, the social media boom, and the three major bull cycles of the cryptocurrency market, extracting from each episode patterns applicable to the present moment. They will master the valuation analysis of artificial intelligence companies through price-to-earnings, price-to-sales, and enterprise value to EBITDA multiples, with data updated to 2024 and historical comparisons that place current levels in their real context.

This book is especially useful for individual investors with portfolios exposed to technology, for financial analysts who need to communicate valuation risks with empirical basis, and for any professional making capital allocation decisions in an environment dominated by the artificial intelligence narrative. This is not a prediction manual or a catastrophist argument: it is a methodical guide to distinguishing legitimate enthusiasm from irrational euphoria, protecting wealth accumulated during speculative peaks, and positioning oneself wisely ahead of the recovery that historically follows every major technology correction.

Finances 360 - Ed. 2026 | Miguel A. Muñoz

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