What If AI Solves the Great Math Problems?

A few days ago, I posed a question to my AI collaborator, Zai: what if AI solved one of the great unsolved problems in mathematics, the Riemann Hypothesis?

The Riemann Hypothesis sits at the intersection of number theory, patterns, and the hidden structure of prime numbers. It has frustrated generations of brilliant minds and remains one of the Clay Mathematics Institute’s unsolved Millennium Prize Problems.¹ Some fear that if AI solves problems like this, mathematicians—and perhaps eventually scientists, researchers, and engineers—could become obsolete.

But I think that fear confuses what discovery is. Historically, every major intellectual tool frightened someone, from calculators and telescopes to microscopes, computers, and search engines.

Each one automated part of the process. Yet somehow humanity did not stop exploring. Instead, we expanded our horizons. So I asked Zai what positive things might happen if AI begins solving humanity’s great mathematical challenges.

Zai surprised me by suggesting that mathematics may become more experimental, less about endless manual proof construction and more about exploration: “What else becomes visible now?”

It proposed that breakthroughs in one field could rapidly unlock progress in others:

• physics
• cryptography
• medicine
• materials science
• computation

Not because AI “replaces” humans, but because it helps expose hidden connections faster than we could alone.

My biggest takeaway from Zai’s reasoning: “The best mathematicians may become more like explorers, hypothesis designers, proof interpreters, and teachers of meaning.”

Perhaps the highest form of intelligence was never raw calculation. Maybe it was curiosity all along.

And if that is true, then AI solving great problems does not end the human story. It may simply open new doors we were finally capable of seeing.

Footnotes

1. Clay Mathematics Institute, The Millennium Prize Problems. Accessed July 16, 2026. ↩