Impact of artificial intelligence on employees working in industry 4.0 led organizations
Purpose: This study attempts to develop a practical understanding of the positive and negative employee experiences due to artificial intelligence (AI) adoption and the creation of technostress. It unravels the human resource development-related challenges with the onset of Industry 4.0. Design/methodology/approach: Semi-structured interviews were conducted with 32 professionals with average work experience of 7.6 years and working across nine industries, and the transcripts were analyzed using NVivo. Findings: The findings establish prominent adverse impacts of the adoption of AI, namely, information security, data privacy, drastic changes resulting from digital transformations and job risk and insecurity brewing in the employee psyche. This is followed by a hierarchy of factors comprising the positive impacts, namely, work-related flexibility and autonomy, creativity and innovation and overall enhancement in job performance. Further factors contributing to technostress (among employees): work overload, job insecurity and complexity were identified. Practical implications: The emerging knowledge economy and technological interventions are changing the existing job profiles, hence the need for different skillsets and technological competencies. The organizations thus need to deploy strategic manpower development measures involving up-gradation of skills and knowledge management. Inculcating requisite skills requires well-designed training programs using specialized tools and virtual reality (VR). In addition, employees need to be supported in their evolving socio-technical relationships, for managing both positive and negative outcomes. Originality/value: This research makes the unique contribution of establishing a qualitative hierarchy of prominent factors constituting unintended consequences, positive impacts and technostress creators (among employees) of AI deployment in organizational processes.
Year of publication: |
2021
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Authors: | Malik, Nishtha ; Tripathi, Shalini Nath ; Kar, Arpan Kumar ; Gupta, Shivam |
Published in: |
International Journal of Manpower. - Emerald, ISSN 0143-7720, ZDB-ID 2032092-9. - Vol. 43.2021, 2 (18.06.), p. 334-354
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Publisher: |
Emerald |
Saved in:
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