After years of inflated promises, the market is moving past the initial AI hype cycle. Leaders realize that simply attaching "AI" to a company name is not a strategy. This shift leads to a more realistic understanding of where AI provides practical value, which will stabilize hiring and investment.

The current AI boom mirrors the dot-com era. The underlying technology is revolutionary and will transform the economy, but valuations may have already priced in decades of future growth. This means investors buying now risk poor returns even if the companies ultimately succeed, as both technology enthusiasts and valuation skeptics can be correct simultaneously.

The massive $700B capital injection into AI demands a return. The next few years will shift focus from hype to demonstrable results. Companies that can't show a quick, real, and efficient ROI will face a reckoning, even if they have grand aspirations.

For a proven, hyper-growth AI company, traditional business risks (market, operational, tech) are minimal. The sole risk for a late-stage investor is overpaying for several years of future growth that may decelerate faster than anticipated.

The stock market's enthusiasm for AI has created valuations based on future potential, not current reality. The average company using AI-powered products isn't yet seeing significant revenue generation or value, signaling a potential market correction.

Despite numerous world-changing innovations over 150 years (electricity, PCs, internet), US stock market valuations (via CAPE ratio) have only been higher once, in 2000. This implies an extreme level of optimism is priced in for AI's impact on corporate profits compared to historical tech booms.

AI is currently a challenging business because it's in a heavy infrastructure investment cycle, similar to the early days of the web or cloud. Significant value creation typically occurs years after this initial investment phase, and the market isn't there yet.

In the current AI hype cycle, a common mistake is valuing startups as if they've already achieved massive growth, rather than basing valuation on actual, demonstrated traction. This "paying ahead of growth" leads to inflated valuations and high risk, a lesson from previous tech booms and busts.

Unlike the dot-com era where valuations far outpaced a small, slow user base, the current AI shift is driven by products with immediate, massive adoption and revenue. The technology is delivering value today, not just promising it for the future, which fundamentally changes the financial dynamics.