Uncovering the determinants of adopting generative artificial intelligence
Sarah Maria Granig · University of Klagenfurt
This master’s thesis investigates the factors influencing the adoption of generative artificial intelli-gence within the field of business administration. The study aims to provide a comprehensive under-standing of the determinants shaping individuals’ intentions to use generative artificial intelligence technologies, focusing on the context of the University of Klagenfurt. The research methodology employed a mixed-methods approach, combining quantitative analysis of survey data with qualitative insights gathered through semi-standardized interviews with students. By integrating these research methods, the thesis offers a nuanced exploration of the factors driving the adoption of generative AI among individuals. The theoretical framework of the study establishes clear definitions of artificial intelligence and generative artificial intelligence, drawing on established theories of technology adoption such as the Unified Theory of Acceptance and Use of Technology. Through literature review and empirical analysis, the research identifies key determinants that influence the intention to use generative AI technologies. The study reveals that Performance Expectancy significantly influences individuals’ willingness to adopt AI technologies, emphasizing the importance of perceived effectiveness and benefits. However, factors such as Effort Expectancy, Social Influence, Hedonic Motivation, and Ethical Concerns do not demonstrate statistically significant influence on the adoption decision.