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Cobots in knowledge work

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  • Sowa, Konrad
  • Przegalinska, Aleksandra
  • Ciechanowski, Leon

Abstract

Current technological developments, as well as widespread application of artificial intelligence, will doubtlessly continue to impact how people live and work. In this research, we explored synergies between human workers and AI in managerial tasks. We hypothesized that human-AI collaboration will increase productivity. In the paper, several levels of proximity between AI and humans in a work setting are distinguished. The multi-stage study, covering the exploratory phase in which we conducted a study of preferences using 10-item Likert scale, was conducted with a sample of 366 respondents. The study focused on working with different types of AI. The second and third phase of the study, in which we primarily used qualitative methods (scenario-based design combined with semi-structured interviews with six participants), focused on researching modes of collaboration between humans and virtual assistants. The study results generally confirmed our hypothesis about increased productivity due to enhanced human-AI collaboration, proving that the future of AI in knowledge work needs to focus not on full automation but rather on collaborative approaches where humans and AI work closely together.

Suggested Citation

  • Sowa, Konrad & Przegalinska, Aleksandra & Ciechanowski, Leon, 2021. "Cobots in knowledge work," Journal of Business Research, Elsevier, vol. 125(C), pages 135-142.
    • Handle: RePEc:eee:jbrese:v:125:y:2021:i:c:p:135-142
    DOI: 10.1016/j.jbusres.2020.11.038
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    2. Olimpia Ban & Irina Maiorescu & Mihaela Bucur & Gabriel Cristian Sabou & Betty Cohen Tzedec, 2024. "AI between Threat and Benefactor for the Competences of the Human Working Force," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 26(67), pages 762-762, August.
    3. Volkmar, Gioia & Fischer, Peter M. & Reinecke, Sven, 2022. "Artificial Intelligence and Machine Learning: Exploring drivers, barriers, and future developments in marketing management," Journal of Business Research, Elsevier, vol. 149(C), pages 599-614.
    4. Jun Liu & Yu Qian & Yuanjun Yang & Zhidan Yang, 2022. "Can Artificial Intelligence Improve the Energy Efficiency of Manufacturing Companies? Evidence from China," IJERPH, MDPI, vol. 19(4), pages 1-18, February.

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