How scientists use Claude
Anthropic (AI lab research) · 5 Nov 2026
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Where this sits in the debate
- Will AI actually boost productivity and growth? · its finding supports the claim (why studies differ)
Direction of the finding as read from the abstract by an AI model (AI-written).
Source excerpt
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). Beyond these developments, most scientific progress involves many specialized, interlinked research tasks, which can vary substantially across fields. How much AI accelerates scientific discovery depends not only on AI’s capabilities, but also on how it is adopted across these tasks. In this report, we use privacy-preserving infrastructure to study the scientific use of Claude, Claude Code, and Claude Science. We document how usage varies across fields and tasks, identify what explains these usage patterns, and outline scenarios for how AI could accelerate research. Claude use in science varies by field. Relative to their number of researchers, formal sciences such as computer science, mathematics, and statistic
About this publication
AI lab or institute. Published by an AI lab or research institute on its own site. Not peer reviewed, and the publisher may have a stake in the findings.
- Published
- 2026 (recently)
- Citations
- Not recorded for this source
Citation counts come from OpenAlex; none are recorded for this source — absence of a count is not absence of citations.
Reaches a different conclusion
Papers on the same question whose finding points the other way, as read from the abstracts by an AI model (AI-written). Why studies differ.
- The simple macroeconomics of AI
Productivity: its finding goes against the claim · Daron Acemoğlu · 2024 - Past Automation and Future A.I.: How Weak Links Tame the Growth Explosion
Productivity: its finding goes against the claim · Charles I. Jones and Christopher Tonetti · 2026
Related papers
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Ezra Karger et al. · NBER · 2026 - Task Expansion with Generative AI: Experimental Evidence on Middle-Skilled, Early-Career Workers
Hanna Brosch et al. · CESifo · 2026
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