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Drivers and barriers of AI adoption and use in scientific research

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  • Bianchini, Stefano
  • Müller, Moritz
  • Pelletier, Pierre

Abstract

We study the early adoption and use of artificial intelligence (AI) in scientific research. Using a large dataset of publications from OpenAlex (all fields, up to 2024) and building on theories of scientific and technical human capital, we identify key factors that influence AI adoption. We find that early adopters were domain scientists embedded in AI-rich collaboration networks and affiliated with institutions with strong AI credentials. Access to high-performance computing (HPC) mattered only in a few scientific disciplines, such as biology and medical sciences. More recently, as tools like Large Language Models (LLMs) have diffused, AI has become more accessible, and institutional advantages appear to matter less. However, social capital—especially ties to AI-experienced collaborators and early-career researchers—remains a persistent driver of adoption. We discuss the implications for science policy and the organization of research in the age of AI.

Suggested Citation

  • Bianchini, Stefano & Müller, Moritz & Pelletier, Pierre, 2025. "Drivers and barriers of AI adoption and use in scientific research," Technological Forecasting and Social Change, Elsevier, vol. 220(C).
    • Handle: RePEc:eee:tefoso:v:220:y:2025:i:c:s0040162525003348
    DOI: 10.1016/j.techfore.2025.124303
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    1. Bianchini, Stefano & Müller, Moritz & Pelletier, Pierre, 2022. "Artificial intelligence in science: An emerging general method of invention," Research Policy, Elsevier, vol. 51(10).
    2. Viswanath Venkatesh, 2022. "Adoption and use of AI tools: a research agenda grounded in UTAUT," Annals of Operations Research, Springer, vol. 308(1), pages 641-652, January.
    3. James G. March, 1991. "Exploration and Exploitation in Organizational Learning," Organization Science, INFORMS, vol. 2(1), pages 71-87, February.
    4. Kathryn Tunyasuvunakool & Jonas Adler & Zachary Wu & Tim Green & Michal Zielinski & Augustin Žídek & Alex Bridgland & Andrew Cowie & Clemens Meyer & Agata Laydon & Sameer Velankar & Gerard J. Kleywegt, 2021. "Highly accurate protein structure prediction for the human proteome," Nature, Nature, vol. 596(7873), pages 590-596, August.
    5. Rose, Michael E. & Georg, Co-Pierre, 2021. "What 5,000 acknowledgements tell us about informal collaboration in financial economics," Research Policy, Elsevier, vol. 50(6).
    6. Haefner, Naomi & Parida, Vinit & Gassmann, Oliver & Wincent, Joakim, 2023. "Implementing and scaling artificial intelligence: A review, framework, and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    7. Jian Gao & Dashun Wang, 2024. "Quantifying the use and potential benefits of artificial intelligence in scientific research," Nature Human Behaviour, Nature, vol. 8(12), pages 2281-2292, December.
    8. Stefano Bianchini & Moritz Müller & Pierre Pelletier, 2022. "Artificial intelligence in science: An emerging general method of invention," Post-Print hal-03958025, HAL.
    9. 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.
    10. Rotolo, Daniele & Hicks, Diana & Martin, Ben R., 2015. "What is an emerging technology?," Research Policy, Elsevier, vol. 44(10), pages 1827-1843.
    11. Koppman, Sharon & Leahey, Erin, 2019. "Who moves to the methodological edge? Factors that encourage scientists to use unconventional methods," Research Policy, Elsevier, vol. 48(9), pages 1-1.
    12. Parteka, Aleksandra & Kordalska, Aleksandra, 2023. "Artificial intelligence and productivity: global evidence from AI patent and bibliometric data," Technovation, Elsevier, vol. 125(C).
    13. Daniel Hain & Roman Jurowetzki & Sungjoo Lee & Yuan Zhou, 2023. "Machine learning and artificial intelligence for science, technology, innovation mapping and forecasting: Review, synthesis, and applications," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1465-1472, March.
    14. Richard Van Noorden & Jeffrey M. Perkel, 2023. "AI and science: what 1,600 researchers think," Nature, Nature, vol. 621(7980), pages 672-675, September.
    15. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    16. Jeffrey L. Furman & Florenta Teodoridis, 2020. "Automation, Research Technology, and Researchers’ Trajectories: Evidence from Computer Science and Electrical Engineering," Organization Science, INFORMS, vol. 31(2), pages 330-354, March.
    17. Chiara Franzoni & Paula Stephan & Reinhilde Veugelers, 2022. "Funding Risky Research," Entrepreneurship and Innovation Policy and the Economy, University of Chicago Press, vol. 1(1), pages 103-133.
    18. Michaël Bikard & Fiona Murray & Joshua S. Gans, 2015. "Exploring Trade-offs in the Organization of Scientific Work: Collaboration and Scientific Reward," Management Science, INFORMS, vol. 61(7), pages 1473-1495, July.
    19. Kristina McElheran & J. Frank Li & Erik Brynjolfsson & Zachary Kroff & Emin Dinlersoz & Lucia Foster & Nikolas Zolas, 2024. "AI adoption in America: Who, what, and where," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 33(2), pages 375-415, March.
    20. Hanchen Wang & Tianfan Fu & Yuanqi Du & Wenhao Gao & Kexin Huang & Ziming Liu & Payal Chandak & Shengchao Liu & Peter Katwyk & Andreea Deac & Anima Anandkumar & Karianne Bergen & Carla P. Gomes & Shir, 2023. "Scientific discovery in the age of artificial intelligence," Nature, Nature, vol. 620(7972), pages 47-60, August.
    21. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation," NBER Working Papers 24449, National Bureau of Economic Research, Inc.
    22. Arianna Martinelli & Andrea Mina & Massimo Moggi, 2021. "The enabling technologies of industry 4.0: examining the seeds of the fourth industrial revolution [Mapping innovation dynamics in the Internet of Things domain: evidence from patent analysis]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 30(1), pages 161-188.
    23. Jonas Degrave & Federico Felici & Jonas Buchli & Michael Neunert & Brendan Tracey & Francesco Carpanese & Timo Ewalds & Roland Hafner & Abbas Abdolmaleki & Diego de las Casas & Craig Donner & Leslie F, 2022. "Magnetic control of tokamak plasmas through deep reinforcement learning," Nature, Nature, vol. 602(7897), pages 414-419, February.
    24. Katz, J. Sylvan & Martin, Ben R., 1997. "What is research collaboration?," Research Policy, Elsevier, vol. 26(1), pages 1-18, March.
    25. Pierre Azoulay & Joshua S. Graff Zivin & Jialan Wang, 2010. "Superstar Extinction," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(2), pages 549-589.
    26. Lee, You-Na & Walsh, John P. & Wang, Jian, 2015. "Creativity in scientific teams: Unpacking novelty and impact," Research Policy, Elsevier, vol. 44(3), pages 684-697.
    27. Ajay Agrawal & John McHale & Alexander Oettl, 2018. "Finding Needles in Haystacks: Artificial Intelligence and Recombinant Growth," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 149-174, National Bureau of Economic Research, Inc.
    28. Ameye, Nicolas & Bughin, Jacques & van Zeebroeck, Nicolas, 2023. "How uncertainty shapes herding in the corporate use of artificial intelligence technology," Technovation, Elsevier, vol. 127(C).
    29. Bozeman, Barry & Corley, Elizabeth, 2004. "Scientists' collaboration strategies: implications for scientific and technical human capital," Research Policy, Elsevier, vol. 33(4), pages 599-616, May.
    30. David ARRANZ & Stefano BIANCHINI & Valentina, DI GIROLAMO & Julien RAVET, 2023. "Trends in the use of AI in science," EU research and innovation paper series KI-BD-23-003-EN-N, Directorate General for Research and Innovation (DG RTD) of the European Commission.
    31. Lili Wang & Xianwen Wang & Niels J. Philipsen, 2017. "Network structure of scientific collaborations between China and the EU member states," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(2), pages 765-781, November.
    32. Heinze, Thomas & Shapira, Philip & Rogers, Juan D. & Senker, Jacqueline M., 2009. "Organizational and institutional influences on creativity in scientific research," Research Policy, Elsevier, vol. 38(4), pages 610-623, May.
    33. Myra Mohnen, 2022. "Stars and Brokers: Knowledge Spillovers Among Medical Scientists," Management Science, INFORMS, vol. 68(4), pages 2513-2532, April.
    34. Hanchen Wang & Tianfan Fu & Yuanqi Du & Wenhao Gao & Kexin Huang & Ziming Liu & Payal Chandak & Shengchao Liu & Peter Katwyk & Andreea Deac & Anima Anandkumar & Karianne Bergen & Carla P. Gomes & Shir, 2023. "Publisher Correction: Scientific discovery in the age of artificial intelligence," Nature, Nature, vol. 621(7978), pages 33-33, September.
    35. Stefano Baruffaldi & Brigitte van Beuzekom & Hélène Dernis & Dietmar Harhoff & Nandan Rao & David Rosenfeld & Mariagrazia Squicciarini, 2020. "Identifying and measuring developments in artificial intelligence: Making the impossible possible," OECD Science, Technology and Industry Working Papers 2020/05, OECD Publishing.
    36. John Jumper & Richard Evans & Alexander Pritzel & Tim Green & Michael Figurnov & Olaf Ronneberger & Kathryn Tunyasuvunakool & Russ Bates & Augustin Žídek & Anna Potapenko & Alex Bridgland & Clemens Me, 2021. "Highly accurate protein structure prediction with AlphaFold," Nature, Nature, vol. 596(7873), pages 583-589, August.
    37. Kinkel, Steffen & Baumgartner, Marco & Cherubini, Enrica, 2022. "Prerequisites for the adoption of AI technologies in manufacturing – Evidence from a worldwide sample of manufacturing companies," Technovation, Elsevier, vol. 110(C).
    38. Daniele Archibugi, 2021. "Choosing your Mentor: A Letter to Creative Minds," Journal of Innovation Economics, De Boeck Université, vol. 0(3), pages 103-115.
    39. Tobias Koopmann & Maximilian Stubbemann & Matthias Kapa & Michael Paris & Guido Buenstorf & Tom Hanika & Andreas Hotho & Robert Jäschke & Gerd Stumme, 2021. "Proximity dimensions and the emergence of collaboration: a HypTrails study on German AI research," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(12), pages 9847-9868, December.
    40. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation: An Exploratory Analysis," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 115-146, National Bureau of Economic Research, Inc.
    41. Ida Merete Enholm & Emmanouil Papagiannidis & Patrick Mikalef & John Krogstie, 2022. "Artificial Intelligence and Business Value: a Literature Review," Information Systems Frontiers, Springer, vol. 24(5), pages 1709-1734, October.
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