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.

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: This article delves into an in-depth analysis of the statistically significant differences in AI support levels for project management between SMEs and large enterprises. The research was conducted based on a comprehensive survey encompassing a sample of 473 SMEs and large Slovenian enterprises. Methods: To validate the observed differences, statistical analysis, specifically the Mann–Whitney U test, was employed. Results: The results confirm the presence of statistically significant differences between SMEs and large enterprises across multiple dimensions of AI support in project management. Large enterprises exhibit on average a higher level of AI adoption across all five AI utilization dimensions. Specifically, large enterprises scored significantly higher (p < 0.05) in AI adopting strategies and in adopting AI technologies for project tasks and team creation. This study’s findings also underscored the significant differences (p < 0.05) between SMEs and large enterprises in their adoption and utilization of AI technologies for project management purposes. While large enterprises scored above 4 for several dimensions, with the highest average score assessed (mean value 4.46 on 1 to 5 scale) for the usage of predictive Analytics Tools to improve the work on the project, SMEs’ average levels, on the other hand, were all below 4. SMEs in particular may lag in incorporating AI into various project activities due to several factors such as resource constraints, limited access to AI expertise, or risk aversion. Conclusions: The results underscore the need for targeted strategies to enhance AI adoption in SMEs and leverage its benefits for successful project implementation and strengthen the company’s competitiveness.

The purpose of the paper is to develop a multidimensional model of the new work environment in the digital age to increase a company’s performance and competitiveness in VUCA (volatility, uncertainty, complexity, and ambiguity) business environment. The multidimensional model covers the implementation of an agile work environment through the prism of using artificial intelligence technology to increase company’s performance and competitiveness. Researched determined multidimensional aspects for successful implementation of work environment in the digital age are, therefore (1) drivers for shifting towards agility, (2) implementation of agile leadership, (3) implementation of an agile work environment, (4) implementation of AI technology in work environment, (5) company’s performance, (6) competitiveness. The main survey involved randomly selected 473 medium-sized and large companies in Slovenia. Structural equation modelling was used for statistical data analysis. The results show that drivers for shifting towards agility have a positive effect on implementation of agile leadership. Also, results show that implementation of agile leadership and implementation of AI technology in work environment have a positive effect on implementation of an agile work environment. Moreover, results show that implementation of an agile work environment has positive effect on company’s performance and competitiveness. The paper highlights the important multidimensional aspects of the successful implementation of an agile work environment to increase the company’s performance and competitiveness. Also, our results will contribute to the proper implementation of the work environment in the digital age and give owners or top managers a broad insight into the various aspects that must be considered in their business governance in today’s rapidly changing business environment.

This article presents the findings of a survey conducted in Slovenia, encompassing a random sample of 275 enterprises, to analyze the factors influencing the transition to an agile approach, the AI-supported organizational culture, AI-enabled workload reduction, and AI-enabled performance enhancement in small and large enterprises. The study investigates whether there are statistically significant differences between small and large enterprises in Slovenia regarding these aspects. These findings provide valuable insights into the distinct perspectives and priorities of small and large enterprises in Slovenia regarding agility and the adoption of AI technologies. The results highlight areas where small businesses may need additional support or targeted strategies to fully leverage the benefits of agility and AI. Policymakers and industry leaders can utilize these findings to promote tailored approaches that enhance agility and facilitate effective AI integration in both small and large enterprises, ultimately contributing to the growth and competitiveness of the Slovenian business landscape.

This study investigates artificial intelligence (AI) literacy among university students from Slovenia, Croatia, and India, focusing on variations in their understanding of AI concepts and applications across different educational systems. The sample comprised 471 students from the business studies programmes in Slovenia, Croatia and India. Data were collected through a structured online questionnaire, and statistical analyses utilized descriptive statistics and independent samples proportions to identify significant differences in AI literacy levels across the three countries. The findings reveal substantial disparities in AI literacy. Croatian students demonstrated foundational and practical knowledge of AI, reflecting well-developed educational frameworks. Indian students excelled in interdisciplinary and applied aspects of AI, though their understanding of theoretical concepts revealed notable gaps. Slovenian students showed the greatest need for improvement, particularly in foundational knowledge, practical applications, and ethical considerations. The results also highlight universal challenges, such as gaps in understanding AI’s ethical and legal implications, underscoring the need for all educational systems to incorporate discussions on accountability and societal impacts into their curricula. These findings offer actionable recommendations for educational policy and curriculum design to enhance AI literacy globally and prepare students for the challenges and opportunities of an AI-driven world. This study contributes to the literature by enhancing the understanding of how AI literacy manifests across diverse educational systems, providing comparative insights to support globally relevant curriculum development and digital skills advancement.