Mathematics research has seen a significant advancement with the integration of AI-driven formal proof search, leveraging large language models (LLMs) to generate formal proofs in languages like Lean. A recent evaluation assessed the capability of LLMs to solve open problems, with the most capable agent successfully resolving 9 out of 353 open Erdős problems1. This breakthrough demonstrates the potential of AI-driven methods to accelerate mathematical discoveries. The use of LLMs in formal proof search mitigates the limitations of traditional methods, providing a more reliable and efficient approach to mathematical reasoning. As AI technology continues to improve, its application in mathematics research is likely to expand, enabling researchers to tackle complex problems with greater ease. The successful resolution of open problems using AI-driven formal proof search matters to practitioners because it has the potential to significantly accelerate progress in mathematics, enabling researchers to focus on higher-level problems and driving innovation in the field.