The purpose of the paper is to create a multidimensional talent management model with embedded aspects of artificial intelligence in the human resource processes to increase employees' engagement and performance of the enterprise. The research was implemented on a sample of 317 managers/owners in Slovenian enterprises. Multidimensional constructs of the model include several aspects of artificial intelligence implementation in the organization's activities related to human resource management in the field of talent management, especially in the process of acquiring and retaining talented employees, appropriate training and development of employees, organizational culture, leadership, and reducing the workload of employees, employee engagement and performance of the enterprise. The results show that AI supported acquiring and retaining a talented employees, AI supported appropriate training and development of employees, appropriate teams, AI supported organizational culture, AI supported leadership, reducing the workload of employees with AI have a positive effect on performance of the enterprise and employee engagement. The results will help managers or owners create a successful work environment by implementing artificial intelligence in the enterprise, leading to increased employee engagement and performance of the enterprise. Namely, our results contribute to the efficient implementation of artificial intelligence into an enterprise and give owners or top managers a broad insight into the various aspects that must be taken into account in business management in order to increase employee engagement and enterprise’s competitive advantage.

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.

Organizations thrive on attaining and sustaining competitiveness because of the turbulent, rapidly changing business environment. The research shows that it is possible to improve organizations’ competitiveness by considering the multidimensional model viewpoints, which include the strategic talent management ecosystem viewpoints and the strategic agile management ecosystem viewpoints. The multidimensional model includes the essential constructs for developing strategic talent management, i.e., acquiring talented employees, target development of talented employees, designing talent teams, and talent leadership, as well as the following essential constructs for developing strategic agile management, i.e., designing agile teams, agile leadership, and support agile management culture. The research was implemented on 532 owners/managers in organizations. Structural equation modeling was used to test the hypotheses. Results show that developing a strategic talent management ecosystem positively affects developing a strategic agile management ecosystem and leads to higher organization competitiveness. A developed multidimensional model will help owners and managers comprehensively embrace and implement agility in their organization to increase competitiveness.

The purpose of this article is to present research on the importance of requisitely holistically selected organisational climate components and to determine their impact on work engagement of employees in 626 medium-sized organisations in Slovenia, the EU. The quantitative research is based on the implementation of an exploratory factor analysis, a simple linear regression analysis and the CFA 6-factor solution for validity purposes. Based on the research results, we confirmed the hypothesis that organisational climate components leadership, employee relations, employee commitment, employee satisfaction and employee motivation have a significant positive impact on work engagement of employees in medium-sized organisations. The results help users to better understand the importance of organisational climate in the Slovenian organisations. Successful organisations should realise the importance of organisational climate components, which enhance job performance and work engagement. Thus, they must fully master all of the employee-related processes of the organisation. The article is based on examination of the selected components of organisational climate with which organisations can impact work engagement of their employees. A new conceptual model was developed and confirmed.

The purpose of the paper is to present a model of factors affecting the successful project implementation by introducing agility and artificial intelligence to increase the company’s competitiveness. In the model, the multidimensional constructs describing the implementation of an agile work environment and artificial intelligence technologies and tools were developed. These multidimensional constructs are agile work environment, agile leadership, agile team skills and capabilities, improving the work of the leader in the project, adopting AI technologies in the project, and using AI solutions in a project. Their impact on successful project implementation and on the company competitiveness was tested. The fundamental reason for conducting this research and developing the model is to enhance the understanding of factors that contribute to the successful implementation of projects and to increase a company’s competitiveness. Our developed model encompasses multidimensional constructs that describe the agile work environment and the utilization of AI technologies. By examining the impact of these constructs on both successful project implementation and company competitiveness, we aimed to establish a comprehensive framework that captures the relationship between agility, AI, and successful project implementation. This model serves as a valuable tool for companies seeking to improve their project implementation processes and gain a competitive edge in the market. The research was based on a sample of 473 managers/owners in medium-sized and large companies. Structural equation modeling was used to test the hypotheses. In today’s turbulent environment, the results will help develop guidelines for a successful combination of agile business practices and artificial intelligence to achieve successful project implementation, increasing a company’s competitiveness.

Background and Purpose: Age diverse employees are faced with different types of occupational stress and different symptoms of burnout when carrying out their work. Therefore, the role of age in job design and implementation of work should not be ignored. The main aim of this paper is to investigate the age differences of occupational stress and symptoms of burnout of employees and to analyze the impact of occupational stress, symptoms of burnout and age on employees’ work satisfaction. Methodology : The paper is based on research that includes a survey of employees in two age groups: younger employees under 50 years of age and older employees between 50 to 65 years of age. Factor analysis was used to form the constructs of occupational stress, symptoms of burnout and employees’ work satisfaction. The non-parametric Mann-Whitney U test was used to test differences in the obtained constructs of occupational stress and symptoms of burnout in the workplace between two independent groups. The multiple regression analysis was used to examine the impact of occupational stress, symptoms of burnout and age on employees’ work satisfaction. Results : The results show there are statistically significant differences in occupational stress and symptoms of burnout in the workplace between older and younger employees. On average, younger employees perceived higher levels of occupational stress and burnout as compared to the older group. Research results also show that occupational stress, behavioral symptoms and emotional symptoms of burnout, as well as age, have a significant impact on employees’ work satisfaction. Conclusion: Managing diversity requires a strategic approach to managing people at work. Therefore, this research adds to the body of knowledge by pointing out the relationship between age and occupational stress and burnout symptoms. Because the role of age in job design has largely been ignored, these relationships have not been studied enough.