IDEAS home Printed from https://ideas.repec.org/a/eee/teinso/v81y2025ics0160791x2500003x.html
   My bibliography  Save this article

Generative Artificial Intelligence (GenAI) in the research process – A survey of researchers’ practices and perceptions

Author

Listed:
  • Andersen, Jens Peter
  • Degn, Lise
  • Fishberg, Rachel
  • Graversen, Ebbe K.
  • Horbach, Serge P.J.M.
  • Schmidt, Evanthia Kalpazidou
  • Schneider, Jesper W.
  • Sørensen, Mads P.

Abstract

This study explores the use of generative AI (GenAI) and research integrity assessments of use cases by researchers, including PhD students, at Danish universities. Conducted through a survey sent to all Danish researchers from January to February 2024, the study received 2534 responses and evaluated 32 GenAI use cases across five research phases: idea generation, research design, data collection, data analysis, and writing/reporting. Respondents reported on their own and colleagues' GenAI usage. They also assessed whether the practices in the use cases were considered good research practice. Through an explorative factor analysis, we identified three clusters of perception: "GenAI as a work horse", "GenAI as a language assistant only", and "GenAI as a research accelerator". The findings further show varied opinions on GenAI's research integrity implications. Language editing and data analysis were generally viewed positively, whereas experiment design and peer review tasks faced more criticism. Controversial areas included image creation/modification and synthetic data, with comments highlighting the need for critical and reflexive use of GenAI. Usage differed by main research area, with technical and quantitative sciences reporting slightly higher usage and more positive assessments. Junior researchers used GenAI more than senior colleagues, while no significant gender differences were observed. The study underscores the need for adaptable, discipline-specific guidelines for GenAI use in research, developed collaboratively with experts to align with diverse research practices and minimize ethical and practical misalignment.

Suggested Citation

  • Andersen, Jens Peter & Degn, Lise & Fishberg, Rachel & Graversen, Ebbe K. & Horbach, Serge P.J.M. & Schmidt, Evanthia Kalpazidou & Schneider, Jesper W. & Sørensen, Mads P., 2025. "Generative Artificial Intelligence (GenAI) in the research process – A survey of researchers’ practices and perceptions," Technology in Society, Elsevier, vol. 81(C).
  • Handle: RePEc:eee:teinso:v:81:y:2025:i:c:s0160791x2500003x
    DOI: 10.1016/j.techsoc.2025.102813
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0160791X2500003X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.techsoc.2025.102813?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. van Buuren, Stef & Groothuis-Oudshoorn, Karin, 2011. "mice: Multivariate Imputation by Chained Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i03).
    2. Lisa Messeri & M. J. Crockett, 2024. "Artificial intelligence and illusions of understanding in scientific research," Nature, Nature, vol. 627(8002), pages 49-58, March.
    3. Anton Korinek, 2023. "Generative AI for Economic Research: Use Cases and Implications for Economists," Journal of Economic Literature, American Economic Association, vol. 61(4), pages 1281-1317, December.
    4. Richard Van Noorden & Jeffrey M. Perkel, 2023. "AI and science: what 1,600 researchers think," Nature, Nature, vol. 621(7980), pages 672-675, September.
    5. Serge P J M & Mads P Sørensen & Nick Allum & Abigail-Kate Reid, 2023. "Disentangling the local context—imagined communities and researchers’ sense of belonging," Science and Public Policy, Oxford University Press, vol. 50(4), pages 695-706.
    6. Matthew Hutson, 2023. "Rules to keep AI in check: nations carve different paths for tech regulation," Nature, Nature, vol. 620(7973), pages 260-263, August.
    7. Holly Else, 2023. "Abstracts written by ChatGPT fool scientists," Nature, Nature, vol. 613(7944), pages 423-423, January.
    8. Linda Nordling, 2023. "How ChatGPT is transforming the postdoc experience," Nature, Nature, vol. 622(7983), pages 655-657, October.
    9. Bin-Nashwan, Saeed Awadh & Sadallah, Mouad & Bouteraa, Mohamed, 2023. "Use of ChatGPT in academia: Academic integrity hangs in the balance," Technology in Society, Elsevier, vol. 75(C).
    10. Brian Owens, 2023. "How Nature readers are using ChatGPT," Nature, Nature, vol. 615(7950), pages 20-20, March.
    11. Francesca Larosa & Sergio Hoyas & Javier García-Martínez & J. Alberto Conejero & Francesco Fuso Nerini & Ricardo Vinuesa, 2023. "Halting generative AI advancements may slow down progress in climate research," Nature Climate Change, Nature, vol. 13(6), pages 497-499, June.
    12. Peres, Renana & Schreier, Martin & Schweidel, David & Sorescu, Alina, 2023. "On ChatGPT and beyond: How generative artificial intelligence may affect research, teaching, and practice," International Journal of Research in Marketing, Elsevier, vol. 40(2), pages 269-275.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Deng, Ruolan & Ahmed, Saifuddin, 2025. "Perceptions and paradigms: An analysis of AI framing in trending social media news," Technology in Society, Elsevier, vol. 81(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Celiktutan, Begum & Klesse, Anne-Kathrin & Tuk, Mirjam A., 2024. "Acceptability lies in the eye of the beholder: Self-other biases in GenAI collaborations," International Journal of Research in Marketing, Elsevier, vol. 41(3), pages 496-512.
    2. Shalpegin, Timofey & Browning, Tyson R. & Kumar, Ajay & Shang, Guangzhi & Thatcher, Jason & Fransoo, Jan C. & Holweg, Matthias & Lawson, Benn, 2025. "Generative AI and Empirical Research Methods in Operations Management," Other publications TiSEM 0eb52ee8-35d0-4c97-8732-8, Tilburg University, School of Economics and Management.
    3. Wu, Qinqin & Zhuang, Qinqin & Liu, Yitong & Han, Longyan, 2024. "Technology shock of ChatGPT, social attention and firm value: Evidence from China," Technology in Society, Elsevier, vol. 79(C).
    4. Toni GIBEA & Radu USZKAI & Mihail Valentin CERNEA, 2023. "The Ethical Risks Posed By New Technologies In Research," Proceedings of the INTERNATIONAL MANAGEMENT CONFERENCE, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 17(1), pages 757-765, November.
    5. Amy Wenxuan Ding & Shibo Li, 2025. "Generative AI lacks the human creativity to achieve scientific discovery from scratch," Post-Print hal-05053017, HAL.
    6. Arpan Kumar Kar & P. S. Varsha & Shivakami Rajan, 2023. "Unravelling the Impact of Generative Artificial Intelligence (GAI) in Industrial Applications: A Review of Scientific and Grey Literature," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 24(4), pages 659-689, December.
    7. Khizar, Hafiz Muhammad Usman & Ashraf, Aqsa & Yuan, Jingbo & Al-Waqfi, Mohammed, 2025. "Insights into ChatGPT adoption (or resistance) in research practices: The behavioral reasoning perspective," Technological Forecasting and Social Change, Elsevier, vol. 215(C).
    8. repec:osf:osfxxx:h6a7c_v1 is not listed on IDEAS
    9. Julian Junyan Wang & Victor Xiaoqi Wang, 2024. "Leveraging Large Language Models to Democratize Access to Costly Datasets for Academic Research," Papers 2412.02065, arXiv.org, revised Jun 2025.
    10. Motoki, Fabio Y.S. & Pinho Neto, Valdemar & Rangel, Victor, 2025. "Assessing political bias and value misalignment in generative artificial intelligence," Journal of Economic Behavior & Organization, Elsevier, vol. 234(C).
    11. Paola Cillo & Gaia Rubera, 2025. "Generative AI in innovation and marketing processes: A roadmap of research opportunities," Journal of the Academy of Marketing Science, Springer, vol. 53(3), pages 684-701, May.
    12. Hermann, Erik & Puntoni, Stefano, 2024. "Artificial intelligence and consumer behavior: From predictive to generative AI," Journal of Business Research, Elsevier, vol. 180(C).
    13. Abhilash Bandam & Eedris Busari & Chloi Syranidou & Jochen Linssen & Detlef Stolten, 2022. "Classification of Building Types in Germany: A Data-Driven Modeling Approach," Data, MDPI, vol. 7(4), pages 1-23, April.
    14. Robertson, Jeandri & Ferreira, Caitlin & Botha, Elsamari & Oosthuizen, Kim, 2024. "Game changers: A generative AI prompt protocol to enhance human-AI knowledge co-construction," Business Horizons, Elsevier, vol. 67(5), pages 499-510.
    15. Boonstra Philip S. & Little Roderick J.A. & West Brady T. & Andridge Rebecca R. & Alvarado-Leiton Fernanda, 2021. "A Simulation Study of Diagnostics for Selection Bias," Journal of Official Statistics, Sciendo, vol. 37(3), pages 751-769, September.
    16. Christopher J Greenwood & George J Youssef & Primrose Letcher & Jacqui A Macdonald & Lauryn J Hagg & Ann Sanson & Jenn Mcintosh & Delyse M Hutchinson & John W Toumbourou & Matthew Fuller-Tyszkiewicz &, 2020. "A comparison of penalised regression methods for informing the selection of predictive markers," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-14, November.
    17. Norah Alyabs & Sy Han Chiou, 2022. "The Missing Indicator Approach for Accelerated Failure Time Model with Covariates Subject to Limits of Detection," Stats, MDPI, vol. 5(2), pages 1-13, May.
    18. Eunsil Seok & Akhgar Ghassabian & Yuyan Wang & Mengling Liu, 2024. "Statistical Methods for Modeling Exposure Variables Subject to Limit of Detection," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 16(2), pages 435-458, July.
    19. Ida Kubiszewski & Kenneth Mulder & Diane Jarvis & Robert Costanza, 2022. "Toward better measurement of sustainable development and wellbeing: A small number of SDG indicators reliably predict life satisfaction," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(1), pages 139-148, February.
    20. Georges Steffgen & Philipp E. Sischka & Martha Fernandez de Henestrosa, 2020. "The Quality of Work Index and the Quality of Employment Index: A Multidimensional Approach of Job Quality and Its Links to Well-Being at Work," IJERPH, MDPI, vol. 17(21), pages 1-31, October.
    21. Christopher Kath & Florian Ziel, 2018. "The value of forecasts: Quantifying the economic gains of accurate quarter-hourly electricity price forecasts," Papers 1811.08604, arXiv.org.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:teinso:v:81:y:2025:i:c:s0160791x2500003x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/technology-in-society .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.