The artificial-intelligence boom will almost certainly mint millions of new millionaires. That is the story most often told: algorithms as ladders, automation as liberation, code as the great equalizer. What receives far less attention is the opposite and equally predictable outcome. As AI lowers the barriers to short-term earnings, it may also reduce the number of young people who complete college degrees, quietly increasing the risk of long-term economic instability later in life.

We have seen this movie before, just not with AI. For decades, stories of the self-made entrepreneur, actors, entertainers, creators, and early-stage technologists, have dominated the cultural imagination. Many bypassed formal education in favor of immediate opportunity. Some succeeded spectacularly. Many more did not. The ruins are less visible than the winners, but they are far more common.

The same pattern appears outside of celebrity. Non-college graduates who choose early financial compensation over academic training often experience sharp income spikes when things go well, followed by long periods of decline when markets shift, industries collapse, or skills become obsolete. By contrast, college-educated workers tend to earn less early on, but their income trajectories are steadier. They lose more slowly. They recover faster. They endure.

This is not an argument that college guarantees wealth, nor that entrepreneurship is folly. It is an argument about time. Everybody gets old. What is new eventually breaks. No individual, or industry, wins forever.

Physics offers an inconvenient metaphor here. The second law of thermodynamics tells us that all systems tend toward disorder. Careers are no exception. Without reinforcement, without adaptation, without structure, entropy sets in. Credentials, broad training, and intellectual foundations do not eliminate entropy but they slow it. They provide scaffolding when novelty fades.

The educational value of college, then, is not merely vocational. It is cumulative. It trains people to write, reason, evaluate evidence, and retool when conditions change. Those capacities age better than any platform, language model, or monetization strategy.

What we have not yet seen is the long-term outcome of a generation choosing AI over higher education. What we have seen, repeatedly, are the consequences of under-credentialing in a volatile economy. Workers without degrees are disproportionately exposed during downturns. Their earnings fluctuate more sharply. Their recovery windows are longer. Their later years are less secure.

AI will undoubtedly create enormous wealth. But wealth creation follows a familiar distribution. The Pareto principle still applies: a small fraction will capture most of the gains. For those without educational foundations or durable credentials, the downside risk is substantial.

The danger, then, is not that AI will replace college. It is that AI will convince young people they no longer need it right up until the moment they do.

And by then, the ladder may be harder to climb.