Short answer: yes, there is now credible evidence that AI has materially advanced mathematics and has even solved a small number of previously open problems—but not that it has broadly “solved mathematics.” The strongest evidence comes from recent, primary announcements and accompanying formal proofs/benchmarks.
What the evidence shows
1) AI has solved at least one major open problem
The clearest current example is 
OpenAI’s announcement that an internal reasoning model disproved the Erdős unit-distance conjecture, a long-standing discrete-geometry problem from 1946.[1] OpenAI says the proof was externally checked by mathematicians and published with supporting materials, including a proof write-up and formalization.[1] That makes this one of the strongest public cases that an AI system has produced a genuine new result on an open mathematical problem.
2) AI has also solved some smaller open Erdős problems
Google 
DeepMind reported a study on the Erdős problem database in which its agent produced a number of correct results, including a small set that appeared to be novel autonomous solutions rather than literature rediscoveries.[3][4] The same work also found that many “open” problems were actually obscure, already-known results, which is an important caution: AI can look impressive while sometimes just recovering hidden literature.[4]
3) AI systems have made material advances in constructive mathematics and bounds
DeepMind’s AlphaEvolve produced improved constructions and bounds in several areas, including a rank-48 algorithm for \(4\times4\) matrix multiplication over characteristic-zero fields—an improvement over the long-standing rank-49 baseline.[6][7] It also improved bounds in combinatorics, uncertainty-type inequalities, packing, and related problems.[7] These are real mathematical advances even when they do not settle a famous conjecture outright.
4) AI can now solve elite competition problems at or above medal level
DeepMind’s AlphaProof / AlphaGeometry work showed that AI can solve several problems from the International Mathematical Olympiad at silver-medal level, and later DeepMind reported a Gemini Deep Think result at gold-medal level.[8][9] This is strong evidence of advanced reasoning, but these are not previously unsolved research problems in the usual sense.
5) Benchmarks on research-level problems are now more convincing
The First Proof benchmark and related public evaluations show that frontier models can sometimes produce correct proofs or major steps on unpublished research-level problems, though not reliably and not always autonomously.[10] That suggests the field is moving from competition math toward real research assistance.
What this does not yet show
- AI has not been shown to routinely solve the hardest open problems across mathematics.
- The best results still often depend on formal verification, human selection of problems, careful scaffolding, or post-hoc checking.[4][7]
- Some claims in the public discussion are overstated; for example, “many landmark breakthroughs” is not supported by DeepMind’s own taxonomy, which still distinguishes these results from top-tier “landmark” advances.[2]
Bottom line
The current evidence supports this balanced conclusion:
AI has already made genuine, verifiable contributions to unsolved mathematics—ranging from improved bounds and constructions to at least one high-profile disproof of a long-standing conjecture—but it has not yet broadly automated frontier mathematical discovery.[1][2][7]
Key primary sources
- OpenAI, An OpenAI model has disproved a central conjecture in discrete geometry.[1]
- Google DeepMind, Accelerating mathematical and scientific discovery with Gemini Deep Think.[2]
- Google DeepMind, AI solves IMO problems at silver-medal level.[8]
- Google DeepMind, Advanced version of Gemini with Deep Think officially achieves gold-medal standard at the IMO.[9]
- OpenAI, Ten advances in mathematics.[10]
- DeepMind/related paper on Erdős problems and autonomous discovery.[3][4]
- DeepMind, AlphaEvolve report and technical paper.[6][7]
