"Build it and they will come" is among the fundamental assumptions of dot-com era startups. The belief was that getting big fast, creating a large audience of users, was the foundation for monetization. So, many venture-backed firms essentially spent more money to acquire a user than the lifetime value of that user was reasonable to anticipate, if in fact entrepreneurs even had an idea what that number might be.
The goal was to build market share first and figure out sustainable economics later. So instead of revenue indicators, startups used non-financial metrics such as page views, unique visitors, and user growth, rather than revenue metrics.
To be sure, there is some element of “user engagement” that observers note.
But artificial intelligence represents a fundamentally different paradigm. Rather than hoping to monetize attention, AI tools aim to address concrete business problems with measurable returns from day one: productivity gains, cost savings, or revenue improvements.
That doesn’t eliminate the danger of overinvestment. But the focus on financial returns does ground AI investments in financial reality. Instead of “build it and they will come,” AI developers are much more grounded in "build it because they're already asking for it and willing to pay."
Also, the funding of AI firms is not led by venture capital, but by profitable, revenue-generating, profitable hyperscalers.
Also, where many dot-com companies were essentially trying to become digital magazines or shopping malls, competing for finite consumer attention. AI companies are building tools that enhance work. So the focus is on productivity rather than entertainment spending.
Some amount of overinvestment will likely happen. That tends to be the case for many new general-purpose technologies. Not all the efforts will succeed, but the assets will be rationalized, as was the case for railroads, for example.
The point is that AI might not be analogous to the “dot com bubble.” It might be more akin to the investment pattern for lots of general-purpose technologies, where some amount of overinvestment eventually happens, but the assets are rationalized over time.