Like the dot-com era, many overvalued AI startups will fail. However, this is distinct from the underlying technology. Artificial intelligence itself is a fundamental, irreversible shift that will permanently change the world, similar to how the internet and social media became globally dominant despite early market bubbles.

Today's massive AI company valuations are based on market sentiment ("vibes") and debt-fueled speculation, not fundamentals, just like the 1999 internet bubble. The market will likely crash when confidence breaks, long before AI's full potential is realized, wiping out many companies but creating immense wealth for those holding the survivors.

Citing theorist Carlotta Perez, Gurley argues that only genuinely transformative technologies create bubbles. The rapid wealth creation from the real innovation attracts speculators and charlatans, which inflates the bubble. Therefore, a bubble is evidence of a real shift, not a sign the technology is fake.

History shows that transformative technologies like railroads and the internet often create market bubbles. Investors can lose tremendous amounts of capital on overpriced assets, even while the technology itself fundamentally rewires the economy and creates massive societal value. The two outcomes are not mutually exclusive.

Overvaluing assets in a new tech wave is common and leads to corrections, as seen with mobile and cloud. This differs from a systemic collapse, which requires fundamental weaknesses like the massive debt and fraud that fueled the dot-com crash. Today's AI buildout is funded by cash-rich companies.

We overestimate technology's short-term impact (the hype peak) and then overcorrect into skepticism (the trough of disillusionment). The real, transformative changes happen slowly and quietly after most people have stopped paying attention.

Many dot-com era predictions, like the demise of physical retail, were directionally correct. The primary forecasting error was "timeline compression"—assuming a multi-decade societal transformation would happen in just a few years. This serves as a cautionary tale for the current AI boom, where the "when" is as important as the "what."

The dot-com crash didn't stop internet adoption; it only decimated stock values. Similarly, an "AI winter" for investors is possible even as AI technology becomes more integrated into society. Investors should distinguish between technological adoption and market valuation.

Howard Marks distinguishes between two bubble types. "Mean reversion" bubbles (e.g., subprime mortgages) create no lasting value. In contrast, "inflection bubbles" (e.g., railroads, internet, AI) fund the necessary, often money-losing, infrastructure that accelerates technological progress for society, even as they destroy investor wealth.