Scientists are increasingly using artificial intelligence (AI) to do their work. Many say the tools save them time and money, but others have seen the negative effects such tools can have on research.
In a survey of more than 2,400 researchers published in October by publisher Wiley, 62% of respondents said they used AI for tasks related to research or publishing – up from 45% in 2024, when there were 1,043 respondents. Scientists and early-career researchers in the natural sciences were the most likely to use AI tools in their work, and were more likely to be early adopters of AI than later-career researchers or researchers working in the humanities, mathematics, or statistics.
Researchers use AI tools to assist with writing, editing, and translation. They also use them to detect errors or biases in their writing and to summarize large amounts of research. In a sample of 2,059 respondents, 85% said AI helped with efficiency, 77% said it helped increase the amount of work completed, and 73% said 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 and help them process huge data sets. His team has been using AI to identify the characteristics of neutron stars in their data for about a decade. “If you have 10,000 candidates, it’s useful to be able to scroll through them in a few seconds, instead of having to manually review 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 boost
AI also has an impact on the results of scientists and their careers. A preprint from 20241 published on arXiv reports that scientists who used AI published more papers, received 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-enabled articles from the 67.9 million studies published between 1980 and 2024 in six fields. The authors note that “AI accelerates work in established, data-rich domains.” That suggests that while AI could increase the productivity of individual scientists, it could reduce scientific diversity, they say.
Many researchers are concerned about other harmful effects of AI on research. The survey from Wiley, based in Hoboken, New Jersey, found that 87% of people were concerned about AI making mistakes, called hallucinations, as well as data security, ethics and a lack of transparency around training. In last year’s survey this was 81%.
