As of now, the evidence is strong that AI has materially advanced some previously unsolved mathematical problems, and in a few cases has produced genuinely new mathematical results that were independently checked or formally verified. It is not yet evidence that AI has broadly or routinely solved the hardest flagship open problems of mathematics.
What the current evidence shows
1) AI has produced real advances on open problems
There are now publicly documented cases where AI systems found:
- new constructions that improve known bounds,
- counterexamples that overturn long-held conjectures, and
- proofs formalized in Lean and checked by a theorem prover kernel.[4][5][6]
A particularly important example is 
OpenAI’s public claim that one of its models disproved a longstanding conjecture in discrete geometry, specifically related to the planar unit-distance problem.[2][3] That is a genuine mathematical advance, even though it is not the same as solving every aspect of the underlying broader problem.
2) Formal proof systems matter a lot
Some of the strongest evidence comes from results that were not merely “plausible” but were machine-checked in a formal system such as Lean. For example, AI-assisted work has been reported on Erdős problems, including fully formalized proofs for specific open problems.[4][5] This matters because it sharply reduces the risk of hidden gaps.
3) AI can materially help human mathematicians
There is also evidence of AI acting as a research collaborator: suggesting proof ideas, helping explore cases, and accelerating work that a human expert then verifies and writes up. OpenAI highlighted an example where GPT-5 helped with a roughly 40-year-old open problem in nonconvex optimization, but the human mathematician still did the verification and final mathematical judgment.[7] That is strong evidence of material assistance, not necessarily autonomous solving.
4) Systems are improving on benchmark-style research tasks
Google 
DeepMind and others have shown systems that solve competition-level problems and some research-style open problems, especially in areas with strong automated checking or search structure.[1] These results demonstrate real capability growth, but benchmark success is not the same as settling a major open theorem.
Best current summary
The most accurate summary is:
AI has already helped solve or materially advance several previously unsolved mathematical problems, especially in combinatorics, geometry, number theory, and optimization, but it has not yet broadly conquered the deepest open problems in mathematics.[1][4][7]
Important caveat
Some public claims about “solving many open problems” are stronger than what is currently independently established. The most reliable evidence is where there is:
- a clear problem statement,
- a public proof or construction,
- formal verification or expert review, and
- an attributable announcement or paper.[2][4][5]
Bottom line
Yes: AI has crossed the line from toy examples into real mathematical research advances.
No: the current evidence does not show that AI has generally solved the hardest open problems of mathematics.
