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Artificial-Intelligence-Supported Reduction of Employees’ Workload to Increase the Company’s Performance in Today’s VUCA Environment

Author

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  • Maja Rožman

    (Department of Quantitative Economic Analysis, Faculty of Economics and Business, University of Maribor, 2000 Maribor, Slovenia)

  • Dijana Oreški

    (Department of Information Systems Development, Faculty of Organization and Informatics, University of Zagreb, 10000 Zagreb, Croatia)

  • Polona Tominc

    (Department of Quantitative Economic Analysis, Faculty of Economics and Business, University of Maribor, 2000 Maribor, Slovenia)

Abstract

This paper aims to develop a multidimensional model of AI-supported employee workload reduction to increase company performance in today’s VUCA environment. Multidimensional constructs of the model include several aspects of artificial intelligence related to human resource management: AI-supported organizational culture, AI-supported leadership, AI-supported appropriate training and development of employees, employees’ perceived reduction of their workload by AI, employee engagement, and company’s performance. The main survey involved 317 medium-sized and large Slovenian companies. Structural equation modeling was used to test the hypotheses. The results show that three multidimensional constructs (AI-supported organizational culture, AI-supported leadership, and AI-supported appropriate training and development of employees) have a statistically significant positive effect on employees’ perceived reduction of their workload by AI. In addition, employees’ perceived reduced workload by AI has a statistically significant positive effect on employee engagement. The results show that employee engagement has a statistically significant positive effect on company performance. The concept of engagement is based on the fact that the development and growth of the company cannot be achieved by increasing the number of employees or by adding capital; the added value comes primarily from increased productivity, which is a result of the innovative ability of employees and their work engagement, which improve the company’s performance. The results will significantly contribute to creating new views in the field of artificial intelligence and adopting important decisions in creating working conditions for employees in today’s rapidly changing work environment.

Suggested Citation

  • Maja Rožman & Dijana Oreški & Polona Tominc, 2023. "Artificial-Intelligence-Supported Reduction of Employees’ Workload to Increase the Company’s Performance in Today’s VUCA Environment," Sustainability, MDPI, vol. 15(6), pages 1-21, March.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:5019-:d:1094833
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    References listed on IDEAS

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    1. Xin Wang & Hong Zhu & Di Jiang & Shaoang Xia & Chunqu Xiao, 2023. "“Facilitators” vs “substitutes”: the influence of artificial intelligence products’ image on consumer evaluation," Nankai Business Review International, Emerald Group Publishing Limited, vol. 14(1), pages 177-193, January.
    2. Henry Kaiser, 1974. "An index of factorial simplicity," Psychometrika, Springer;The Psychometric Society, vol. 39(1), pages 31-36, March.
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    Cited by:

    1. Hazem Ahmed Khairy & Mohamed Ahmed & Arwa Asiri & Foziah Gazzawe & Mohamed A. Abdel Fatah & Naim Ahmad & Ayman Qahmash & Mohamed Fathy Agina, 2024. "Catalyzing Green Work Engagement in Hotel Businesses: Leveraging Artificial Intelligence," Sustainability, MDPI, vol. 16(16), pages 1-17, August.
    2. Nikita Bodani & Abhishek Lal & Afsheen Maqsood & Sara Altamash & Naseer Ahmed & Artak Heboyan, 2023. "Knowledge, Attitude, and Practices of General Population Toward Utilizing ChatGPT: A Cross-sectional Study," SAGE Open, , vol. 13(4), pages 21582440231, November.

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