THE AI BOOM IS NOW BIGGER THAN THE '90S DOTCOM BUBBLE-AND IT'S BUILT ON THE BACKS OF BOTS, MAYBE MORE THAN REAL USERS

The artificial intelligence boom has officially eclipsed the size and speed of the 1990s dotcom bubble, with tech giants and startups alike pouring billions into Al models, chips, and infrastructure.

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But as market valuations soar and product launches accelerate, an uncomfortable question is gaining traction: How much of this growth is driven by real human usage—and how much by bots, synthetic traffic, and automated systems?

From ChatGPT to Gemini, Claude to Copilot, the Al gold rush is reshaping the tech industry faster than any previous wave of innovation. Yet unlike the early internet, where metrics like monthly active users and page views were grounded in relatively clear user behavior, today’s Al metrics are murkier—measured in prompts, API calls, model queries, and synthetic interactions that may or may not reflect sustainable human demand.

BIGGER THAN THE DOTCOM ERA—IN RECORD TIME

According to Goldman Sachs, the total market capitalization of companies heavily invested in Al has surpassed $25 trillion, outpacing the Nasdaq's peak valuation during the height of the dotcom bubble in 2000. NVIDIA alone—whose chips power most large-scale Al models—has reached a valuation above $3 trillion, becoming one of the most valuable companies on earth.

The pace of investment and valuation growth has stunned even seasoned investors. In just under 18 months, Al has gone from speculative frontier to the dominant narrative in tech and capital markets. From cloud giants to chipmakers, enterprise software to biotech, Al is being integrated into nearly every sector, often with promises of exponential productivity gains and cost savings.

But as in the dotcom era, where websites with little revenue commanded sky-high valuations, the current Al frenzy is being fueled less by traditional financial performance and more by expectations of transformative impact. What's less clear is who—if anyone—is actually using many of these Al tools at the scale implied by their valuations.