NEWS05 December 2025Artificial intelligence tools are boosting researchers’ productivity, but some worry about the effect of a growing reliance on them.ByRachel Fieldhouse0Rachel FieldhouseRachel Fieldhouse is a reporter for Nature in Sydney, Australia.View author publicationsSearch author on: PubMed Google ScholarMore than 60% of researchers surveyed about AI say they use it for work.Credit: MD Abu Sufian Jewel/NurPhoto via GettyScientists are increasingly using artificial intelligence (AI) to do their work. Many say the tools are saving them time and money, but others have seen the negative effects that such tools can have on research.In a survey of more than 2,400 researchers released in October by the publishing company Wiley, 62% of respondents said they used AI for tasks related to research or publication — up from 45% in 2024, when there were 1,043 respondents. Early-career scientists and researchers in physical sciences were the most likely to use AI tools in their work, and were more likely to be early adopters of AI than were later-career researchers or those working in humanities, mathematics or statistics.Researchers are using AI tools to help with writing, editing and translating. They are also using them to detect errors or bias in their writing, and to summarize large volumes of studies. In a sample of 2,059 respondents, 85% said AI helped with efficiency, 77% that it helped to increase the quantity of work completed, and 73% that it improved the quality of their work.Matthew Bailes, an astrophysicist at Swinburne University of Technology in Melbourne, Australia, says AI tools are popular among astronomers, helping them to process massive data sets. His team has been using AI for about a decade to identify neutron-star signatures in their data. “When you’ve got 10,000 candidates, it’s handy to just be able to whip through it in a few seconds, rather than manually looking at everything.”His team is also developing a virtual simulation of the Universe. The project uses a plug-in version of the generative AI model Claude, developed by Anthropic in San Francisco, California, to display data alongside visualizations. Bailes hopes to use it as a “co-teacher”. It could show a simulation of a globular cluster — a collection of thousands to millions of stars — against graphs showing how many black holes or neutron stars develop over time. “The opportunities for education there are phenomenal,” he adds.Productivity boostAI is also having an impact on scientists’ outputs and their careers. A 2024 preprint1 published on arXiv reports that scientists who used AI published more papers, had more citations and became team leaders four years earlier than those who did not use AI.The researchers used a large language model to identify more than one million AI-assisted papers among 67.9 million studies published in six fields between 1980 and 2024. The authors note that “AI accelerates work in established, data-rich domains”. That suggests that although AI might enhance the productivity of individual scientists, it could reduce scientific diversity, they say.Many researchers worry about other detrimental effects of AI on research. The survey by Wiley, based in Hoboken, New Jersey, found that 87% of people were concerned about AI making errors, called hallucinations, and about data security, ethics and a lack of transparency around training. In last year’s survey, the figure was 81%.doi: https://doi.org/10.1038/d41586-025-03936-2ReferencesHao, Q., Xu, F., Li, Y. & Evans, J. Preprint at arXiv https://doi.org/10.48550/arXiv.2412.07727 (2025).Download references Universities are embracing AI: will students get smarter or stop thinking? Bring us your LLMs: why peer review is good for AI models This AI method could turbocharge the hunt for new medicinesAI tools could reduce the appeal of predatory journals How AI agents will change research: a scientist’s guide AI chatbots are already biasing research — we must establish guidelines for their use now Will AI ever win its own Nobel? Some predict a prize-worthy science discovery soon AI is dreaming up millions of new materials. 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