Unlike typical tech bubbles characterized by excess supply, the current AI boom is severely constrained by shortages in compute, power, and data centers. This fundamental supply-side bottleneck makes a speculative bubble less likely in the short term, as overinvestment cannot easily flood the market.

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.

A true market bubble is a psychological phenomenon requiring near-universal belief that it isn't a bubble. The fact that so many people are actively questioning whether AI is in a bubble indicates the market has not reached the necessary state of widespread 'capitulation' from skeptics.

Frequent, AI-induced market volatility forces companies, regulators, and investors to stay alert about AI's impact. This constant questioning prevents complacency and a "head in the sand" mentality, ultimately averting a much larger, more devastating crash later on.

Unlike the .com bubble, which resulted in significant unused capacity and a subsequent crash, the AI bubble is driven by immediate, widespread adoption and utility. Demand for AI tools and compute is real and growing, meaning the infrastructure being built is utilized almost instantly, creating a more sustainable investment cycle.

Unlike previous tech bubbles characterized by speculative oversupply, the current AI market is demand-driven. Every time a major player like OpenAI 3x-es its compute capacity, the new supply is immediately consumed. This sustained, unmet demand indicates real utility, not just speculative froth.

Historical bubbles, like the dot-com era, occur only when everyone capitulates and believes prices can only go up. According to Ben Horowitz, the constant debate and anxiety about a potential AI bubble is paradoxically the strongest evidence that the market has not yet reached the required state of collective delusion.

David Craver argues the current AI spending boom isn't a bubble yet, precisely because widespread concern signals market rationality. He believes the real bubble will inflate later, once foundational AI companies like OpenAI are public and the technology is so widely adopted that euphoria replaces skepticism.

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.