The AI race has been a prisoner's dilemma where companies spend massively, fearing competitors will pull ahead. As the cost of next-gen systems like Blackwell and Rubin becomes astronomical, the sheer economics will force a shift. Decision-making will be dominated by ROI calculations rather than the existential dread of slowing down.

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."

Similar to the dot-com era, the current AI investment cycle is expected to produce a high number of company failures alongside a few generational winners that create more value than ever before in venture capital history.

Companies feel immense pressure to integrate AI to stay competitive, leading to massive spending. However, this rush means they lack the infrastructure to measure ROI, creating a paradox of anxious investment without clear proof of value.

A large-scale Wharton study found 75% of business leaders see positive ROI from AI, directly contradicting a widely-cited but methodologically questionable MIT report claiming 95% of pilots fail. This confirms that despite the hype, businesses are successfully generating tangible value from their AI investments.

The AI buildout won't be stopped by technological limits or lack of demand. The true barrier will be economics: when the marginal capital provider determines that the diminishing returns from massive investments no longer justify the cost.

The current era of broad enterprise AI experimentation will end. The CEO foresees 2026 as a "year of rationalization," where CFO pressure will force companies to consolidate AI tools and cut vendors that fail to demonstrate tangible productivity gains and clear return on investment.

While AI investment has exploded, US productivity has barely risen. Valuations are priced as if a societal transformation is complete, yet 95% of GenAI pilots fail to positively impact company P&Ls. This gap between market expectation and real-world economic benefit creates systemic risk.

The current AI hype is fueled by massive corporate spending on LLMs and chips. The entire bubble is at risk of unwinding when a critical mass of these companies reports that they are not achieving the promised ROI, causing a rapid pullback in investment.