Science has been described as an “endless frontier” (Bush 1945). But how fast we explore that frontier has historically been limited by a scarce resource: the time and talent of human researchers. Artificial intelligence could ease that limit by amplifying what researchers can do, transforming both the process of discovery and the pace of exploration (Wang et al. 2023; Amodei 2024). Few applications of AI could matter more for human welfare. Given the highly cognitive nature of research compared with most sectors of the economy, AI’s effects may be particularly large and early in this domain.

Recent examples show AI playing a growing role in scientific discovery. In structural biology, AlphaFold predicted the three-dimensional shapes of over 200 million proteins (Jumper et al. 2021; Varadi et al. 2024), and its creators shared the 2024 Nobel Prize in Chemistry. In materials science, GNoME predicted 380,000 stable new crystals (Merchant et al. 2023). In mathematics, researchers have used AI systems to help resolve decades-old Erdős problems, produce a potential proof for a Millennium Prize problem, and make progress on other major problems, from open conjectures to verifying landmark proofs (Anthropic 2026a, 2026b; OpenAI 2026a, 2026b; Tsoukalas et al. 2026).