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Generative AI and Changes to Knowledge Work

Author

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  • Butollo, Florian
  • Haase, Jennifer
  • Katzinski, Ann-Kathrin
  • Krüger, Anne K.

Abstract

The application of generative AI (genAI) tools has led to widespread speculation about the implications of technological change for the future of knowledge work. This article illuminates how the use of genAI affects work practices in the fields of IT programming, science, and coaching based on expert interviews and a quantitative survey of users of genAI. Specifically, we examine perceptions of skills, creativity, and authenticity, which we regard as key qualities of knowledge work. Our results belie the expectation that human expertise and skills lose importance: on the contrary, debates about and experiences with genAI help clarify and revalue the core of a profession's identity. Our study thus highlights that professions consist of more than the sum of single work tasks and contain experiential and tacit knowledge about how to frame, prepare, and interpret work steps, which are difficult for machines to replicate. However, there are concerns that professions could be hollowed out and, especially, that the quality of products and services could deteriorate as automated "good-enough-versions" of former offers become commonplace.

Suggested Citation

  • Butollo, Florian & Haase, Jennifer & Katzinski, Ann-Kathrin & Krüger, Anne K., 2025. "Generative AI and Changes to Knowledge Work," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 5(4), pages 1-30.
    • Handle: RePEc:zbw:espost:335580
    DOI: 10.34669/WI.WJDS/5.4.1
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    References listed on IDEAS

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    1. Davenport, Thomas H., 2018. "The AI Advantage: How to Put the Artificial Intelligence Revolution to Work," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262039176, December.
    2. Erik Brynjolfsson & Danielle Li & Lindsey Raymond, 2025. "Generative AI at Work," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 140(2), pages 889-942.
    3. Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
    4. Chris Stokel-Walker & Richard Van Noorden, 2023. "What ChatGPT and generative AI mean for science," Nature, Nature, vol. 614(7947), pages 214-216, February.
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