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AI-employee collaboration and business performance: Integrating knowledge-based view, socio-technical systems and organisational socialisation framework

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  • Chowdhury, Soumyadeb
  • Budhwar, Pawan
  • Dey, Prasanta Kumar
  • Joel-Edgar, Sian
  • Abadie, Amelie

Abstract

The extant literature has outlined the significance of collaborative intelligence stemming from effective partnership between artificial intelligence (AI) systems and human workers to achieve organisationally valued outcomes. However, there is paucity of research insights on the factors influencing AI-human partnership and its impact on business performance. To bridge this knowledge gap, this paper draws on the knowledge-based view, (KBV) socio-technical systems (STS) and organisational socialisation framework (OSF) to develop and validate a novel theoretical model examining the relationships between knowledge sharing, employees’ AI skills, trust, and role clarity in a collaborative working environment to enhance business performance. A primary survey-based research method was used to capture responses from 164 employees in the UK creative industries, and further analysed by employing Structural Equation Modelling technique. Our findings will provide managers and the AI community with primary evidence and strategies that will help to develop collaborative intelligence capabilities within the organisations.

Suggested Citation

  • Chowdhury, Soumyadeb & Budhwar, Pawan & Dey, Prasanta Kumar & Joel-Edgar, Sian & Abadie, Amelie, 2022. "AI-employee collaboration and business performance: Integrating knowledge-based view, socio-technical systems and organisational socialisation framework," Journal of Business Research, Elsevier, vol. 144(C), pages 31-49.
    • Handle: RePEc:eee:jbrese:v:144:y:2022:i:c:p:31-49
    DOI: 10.1016/j.jbusres.2022.01.069
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    4. Ion Popa & Marian Mihai Cioc & Andreea Breazu & Catalina Florentina Popa, 2024. "Identifying Sufficient and Necessary Competencies in the Effective Use of Artificial Intelligence Technologies," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 26(65), pages 1-33, February.
    5. Zhao, Jingyou & Hu, Enhua & Han, Mingyan & Jiang, Keshen & Shan, Hongmei, 2023. "That honey, my arsenic: The influence of advanced technologies on service employees’ organizational deviance," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
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    7. Lea Kocjancic & Sergej Gricar, 2023. "Usage of AI in Sustainable Knowledge Management and Innovation Processes; Data Analytics in the Electricity Sector," FinTech, MDPI, vol. 2(4), pages 1-19, November.

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