Staggering 90% of biomedical papers now show signs of AI help - Nature

Email Bluesky Facebook LinkedIn Reddit Whatsapp X Save article View saved research Paper introductions and discussions show more signs of AI use than results sections. Credit: Laurence Dutton/Getty The use of artificial intelligence to write scientific papers could be much more prevalent than was previously thought. That’s the upshot of a study that estimates that almost nine out of ten papers published in December 2025 in a major biomedical-article database showed signs of AI-assisted writing. The study, which was posted on the arXiv preprint site on 12 August 1 and has not yet been peer reviewed, puts the rate of usage of AI large language models (LLMs) at 77% for papers archived in the PubMed Central repository and published in the whole of 2025, and 52% for those published in 2024, suggesting LLM use is on the rise. (The study included only papers written in English). These figures are substantially higher than previous estimates of LLM use in the scientific literature. A 2025 paper authored by some of the same researchers that analysed abstracts of papers in PubMed, rather than the full text, puts the figure at at least 13.5% for 2024 2 . Meanwhile, a 2026 study that looked at papers across academic disciplines estimated that 57% of 2025 papers were probably AI-influenced 3 . Dmitry Kobak, a computer scientist at Ghent University in Belgium and co-author of the preprint and the 2025 paper, says he was initially sceptical of the calculations in the latest study: “I was sure that we did something wrong.” But further checks convinced him that the data stood up. Like many previous studies, the latest work analysed the frequency of words commonly used by LLMs to detect signs of their deployment in papers. Kobak attributes the higher figure to the particular method his team used this time around, which is more sensitive to LLM use and therefore more likely to give a higher figure. This method, which yields direct estimates for AI use rather than lower bounds, increased the LLM use rate for 2024 abstracts from 13.5% to 31%. The authors also say that the figures are consistent with the findings of a survey conducted in 2025 — in which 71% of researchers said they use AI for writing assistance — and that the true figure is probably higher than people admit or report in surveys. Other researchers told Nature that the high rates of estimated LLM use reported in the latest paper could make sense given the widespread use of LLMs. They also cautioned that the figures in the study might not be representative of the entire scientific literature and that more analysis is needed to fully understand the rates of usage more broadly. But the results indicate that LLMs are here to stay, says Kyle Siler, a social scientist at the University of Toronto, Canada, and author of the 2026 study that estimated lower LLM use 3 . “The toothpaste is out of the tube, and it’s not going back.” Abstracts versus methods The latest study also found that LLM use was more frequent in abstracts, introductions and discussion sections than in methods and results sections. An estimated 78% of discussion sections in December 2025 papers showed signs of AI, compared with 58% of results sections. AI-assisted results sections could be worrying, says Kobak, because of the propensity of LLMs to fabricate, or ‘hallucinate’, data . Using LLMs to write or edit introductions, meanwhile, could skew the leading ideas in a field. “Whatever bias the LLM may have will just suddenly permeate the literature,” says Kobak. Enjoying our latest content? Log in or create an account to continue Access the most recent journalism from Nature's award-winning team Explore the latest features & opinion covering groundbreaking research Access through your institution or Sign in or create an account Continue with Google Continue with ORCiD doi: https://doi.org/10.1038/d41586-026-02551-z References Holzwarth, L., González-Márquez, R. & Kobak, D. Preprint at arXiv https://doi.org/10.48550/arXiv.2608.10715 (2026). Kobak, D., González-Márquez, R., Horvát, E.-Á. & Lause, J. Sci. Adv. 11 , eadt3813 (2025). Article PubMed Google Scholar Siler, K. Proc. Natl Acad. Sci. USA 123 , e2605754123 (2026). Article PubMed Google Scholar Gray, A. Preprint at arXiv https://doi.org/10.48550/arXiv.2512.01560 (2025). 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