| Abstract [eng] |
Artificial intelligence (AI) is increasingly integrated into business education and organizational practice, creating new opportunities for productivity improvement, decision support, process automation, and value creation. However, the availability of AI technologies does not automatically result in effective adoption or the realization of organizational value. Differences in users’ knowledge, trust, perceived usefulness, ethical awareness, and organizational readiness may influence how AI is perceived and used in different contexts. This study examines attitudes toward AI adoption in business by investigating the relationships among perceived usefulness, AI literacy, trust in AI, ethical concerns, and behavioral intention, while also exploring differences between anticipated AI use among students and experienced AI use among business practitioners. A convergent mixed-methods research design was employed. The quantitative component was based on a structured survey of 140 business students at Vilnius University Business School. Data were collected through Google Forms using a five-point Likert scale and analyzed using descriptive statistics, reliability and validity assessment, and Partial Least Squares Structural Equation Modeling (PLS-SEM). The qualitative component consisted of semi-structured interviews with seven business practitioners who had experience using AI-based technologies in organizational settings. The interviews explored AI use in decision-making, organizational readiness, trust, risk perception, accountability, and changes in work processes. Quantitative and qualitative findings were subsequently integrated through methodological triangulation. The quantitative results indicate that perceived usefulness has a significant positive relationship with behavioral intention to use AI (β = 0.42), while trust in AI also positively influences behavioral intention (β = 0.29). Ethical concerns demonstrate a significant negative relationship with behavioral intention (β = –0.21). AI literacy is positively associated with trust in AI (β = 0.38), while perceived usefulness also contributes positively to trust formation (β = 0.35). The structural model explains 63% of the variance in behavioral intention (R² = 0.63). The qualitative findings complement these results by demonstrating that practitioners assess AI adoption not only in terms of potential benefits but also through organizational readiness, accountability, task characteristics, trust, and implementation constraints. The findings indicate that AI adoption should be understood as a multidimensional socio-technical process in which technological usefulness interacts with human capabilities, trust, ethical considerations, and organizational conditions. The study contributes to the AI adoption literature by connecting individual attitudes with contextual and organizational dimensions of AI use and by comparing anticipated and experienced perspectives on AI adoption. |
