This study primarily investigates five major constructs—organizational culture, AI-enabled leadership, AI-supported employee training, team performance, and employee engagement—focusing on their interrelations through the framework of artificial intelligence within medium and large Slovenian enterprises. A secondary goal is to evaluate the suggested conceptual model using two statistical methodologies within the domain of structural equation modeling (SEM): one assessing linear connections (PLS-SEM) and the other non-linear relations (CB-SEM). The empirical analysis included responses from 437 Slovenian companies, where either the CEO or owner took part. The findings from both analytical approaches indicate that organizational culture did not significantly influence AI-based employee training, yet it did have an effect on AI-enabled leadership. The link between AI-driven leadership and AI-assisted training of employees was confirmed only within the PLS-SEM framework. Moreover, AI-enabled leadership showed a positive association with team outcomes, whereas its influence on business-related teams was found to be insignificant. In both instances, AI-oriented training exhibited a strong and positive impact on teams. Additionally, employee engagement had a significant positive relationship with team performance in both PLS-SEM and CB-SEM models. This study offers critical insights for firms aiming to integrate artificial intelligence effectively in their daily operations. It highlights the pivotal role of AI-driven leadership in fostering outcomes such as enhanced employee learning and superior team performance. Businesses should therefore focus on cultivating leaders adept at employing AI tools to build highly skilled and motivated workforces. Embracing data-centered decision processes and drawing on SEM results can aid organizations in crafting robust AI adoption strategies. These findings contribute to refining human resource management practices and advancing successful AI implementation across enterprises. Ultimately, this research extends the understanding of AI integration in organizations and outlines the HR areas that require improvement for smoother technological adoption.
