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Exploring the impact of AI on team collaboration dynamics in creative decision-making

Author

Listed:
  • Jörg Papenkordt

    (Paderborn University)

  • Johannes Dahlke

    (University of Twente)

  • Nicolas Neef

    (University of Hohenheim)

  • Sarah Zabel

    (University of Hohenheim)

Abstract

The integration of artificial intelligence technology in contemporary work environments raises questions about how human team members collaborate when being assisted by AI. We propose that the reductionist properties of AI technology could affect the logics by which teams operate. This experimental research project aims to identify possible changes in collaboration dynamics within teams when employing AI support in a creative task domain. We explore conversational changes in collaboration by analyzing problem-focused, procedural, action-oriented, and socio-emotional sentiments expressed by team members, as well as structural changes by examining the properties of the communication network resulting from team discussions. Based on the observed co-occurrence of contentual and structural changes, our research points toward emerging patterns of AI-augmented collaboration, indicating that the temporary duration of AI collaboration influences team dynamics differently.

Suggested Citation

  • Jörg Papenkordt & Johannes Dahlke & Nicolas Neef & Sarah Zabel, 2025. "Exploring the impact of AI on team collaboration dynamics in creative decision-making," Working Papers Dissertations 146, Paderborn University, Faculty of Business Administration and Economics.
    • Handle: RePEc:pdn:dispap:146
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    File URL: http://groups.uni-paderborn.de/wp-wiwi/RePEc/pdf/dispap/DP146.pdf
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    References listed on IDEAS

    as
    1. 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.
    2. Alain Pinsonneault & Henri Barki & R. Brent Gallupe & Norberto Hoppen, 1999. "Electronic Brainstorming: The Illusion of Productivity," Information Systems Research, INFORMS, vol. 10(2), pages 110-133, June.
    3. Fabrizio Dell'Acqua & Charles Ayoubi & Hila Lifshitz & Raffaella Sadun & Ethan Mollick & Lilach Mollick & Yi Han & Jeff Goldman & Hari Nair & Stewart Taub & Karim Lakhani, 2025. "The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise," NBER Working Papers 33641, National Bureau of Economic Research, Inc.
    4. H. Colleen Stuart, 2017. "Structural Disruption, Relational Experimentation, and Performance in Professional Hockey Teams: A Network Perspective on Member Change," Organization Science, INFORMS, vol. 28(2), pages 283-300, April.
    5. Zenan Chen & Jason Chan, 2024. "Large Language Model in Creative Work: The Role of Collaboration Modality and User Expertise," Management Science, INFORMS, vol. 70(12), pages 9101-9117, December.
    6. Laske, Katharina & Schröder, Marina, 2017. "Quantity, Quality and Originality: The Effects of Incentives on Creativity," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168151, Verein für Socialpolitik / German Economic Association.
    7. Berkeley J. Dietvorst & Joseph P. Simmons & Cade Massey, 2018. "Overcoming Algorithm Aversion: People Will Use Imperfect Algorithms If They Can (Even Slightly) Modify Them," Management Science, INFORMS, vol. 64(3), pages 1155-1170, March.
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    Keywords

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    JEL classification:

    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives

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