Browsing by Subject "mixed methods"
Now showing 1 - 1 of 1
Results Per Page
Sort Options
Publication Restricted The Role of AI in Business Process Management and a comparative study of AI adoption among Business Process Professionals.(2025) Vinecká Vanda; Koc Hasan; Data Science and Business (BA); Berlin International University of Applied SciencesAs Artificial Intelligence (AI) technologies rapidly evolve, business process professionals are increasingly expected to integrate AI into workflows and decision-making. This thesis explores how AI is adopted in Business Process Management (BPM), what tools are used, what benefits are observed, and which barriers are encountered. Using a mixed-methods approach, the study combines ten semi-structured interviews with a follow-up survey of 55 respondents from various industries. Thematic analysis of the interviews revealed five key themes: (1) AI use cases and tools (such as automation, decision support, and process modeling), (2) role-based perceptions of AI, (3) organizational factors influencing adoption, (4) experienced benefits, and (5) common challenges and limitations. Quantitative analysis tested seven hypotheses based on the qualitative themes. The results showed significant positive correlations between digital maturity, top-management support, and overall AI readiness with both perceived benefits and levels of AI adoption. The findings suggest that successful AI adoption in BPM depends less on structural factors like company size, and more on cultural readiness, leadership engagement, and the quality of underlying data and processes. This thesis highlights the importance of not only technical tools but also emotional and organizational dynamics in shaping digital transformation outcomes.