The AI narrative has evolved beyond tech circles to family Thanksgiving discussions. The focus is no longer on the technology's capabilities but on its financial implications, such as its impact on 401(k)s. This signals a maturation of the hype cycle where public consciousness is now dominated by market speculation.
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For the past 18 months, AI excitement has created a rising tide that boosted fortunes for all major tech companies. This is changing. In the next year, their strategic bets, investments, and results will diverge dramatically, revealing clear winners and losers as "the tide goes out for some people."
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.
Frame AI as a fundamental productivity shift, like the personal computer, that will achieve total market saturation. It's not a speculative bubble but a new, permanent layer of the economy that will be integrated into every business, even a local taco truck.
Within just six months, AI-related investment has transformed from a niche topic to a primary focus in top-down cyclical discussions at major global finance conferences like the IMF/World Bank meetings. This rapid shift highlights its perceived impact on global growth and employment.
The AI era is not an unprecedented bubble but the next phase in a recurring pattern where each new computing cycle (mainframe, PC, internet) is roughly 10 times larger than the last. This historical context suggests the current massive investment is proportional and we are still in the early innings.
The current AI boom isn't just another tech bubble; it's a "bubble with bigger variance." The potential for massive upswings is matched by the risk of equally significant downswings. Investors and founders must have an unusually high tolerance for risk and volatility to succeed.
The most immediate systemic risk from AI may not be mass unemployment but an unsustainable financial market bubble. Sky-high valuations of AI-related companies pose a more significant short-term threat to economic stability than the still-developing impact of AI on the job market.
A genuine technological wave, like AI, creates rapid wealth, which inherently attracts speculators. Therefore, bubble-like behavior is a predictable side effect of a real revolution, not proof that the underlying technology is fake. The two phenomena come together as a pair.
The risk of an AI bubble bursting is a long-term, multi-year concern, not an imminent threat. The current phase is about massive infrastructure buildout by cash-rich giants, similar to the early 1990s fiber optic boom. The “moment of truth” regarding profitability and a potential bust is likely years away.
Marks argues that speculative bubbles form around 'something new' where imagination is untethered from reality. The AI boom, like the dot-com era, is based on a novel, transformative technology. This differs from past manias centered on established companies (Nifty 50) or financial engineering (subprime mortgages), making it prone to similar flights of fancy.
