20.500.12556/DKUM-86981-1d056245-bb09-d759-1483-01af174e21c4 Artificial-intelligence-supported reduction of employees’ workload to increase the company’s performance in today’s VUCA environment 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. artificial intelligence leadership employee engagement company performance umetna inteligenca vodenje zavzetost zaposlenih uspešnost podjetja true false true MDPI Angleški jezik Slovenski jezik Znanstveno delo 2024-02-02 14:09:52 2024-02-02 14:24:24 2024-11-11 14:44:56 0000-00-00 00:00:00 2023 0 0 Str. 1-21 št. 6, št. članka 5019 Letn. 15 2023 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2023-02-15 2023-03-10 2023-03-12 331.1 145075715 10.3390/su15065019 2071-1050 Rozman-2023-Artificial-Intelligence-Supported.pdf Rozman-2023-Artificial-Intelligence-Supported.pdf 1 4EB09D19324B5647ECB22F8F89EADA0E c877ab5f7c8e694af5fdbdf70d1d5ff9aab4969b6da8d099e1a2ffa5871f96ff 22537f79-c1ce-11ee-b96a-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=175888 https://doi.org/10.3390/su15065019 0 5a609ba5-c1cc-11ee-b96a-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=175887 Ekonomsko-poslovna fakulteta 0 0 0