This thesis investigates the cultural prerequisites for successful organizational adoption of artificial intelligence (AI), emphasizing employee training and trust, data and IT infrastructure, and leadership and organizational structure. Drawing on mixed-methods research, the study integrates open- and close-ended survey data from 76 professionals across diverse industries. The analysis reveals persistent gaps between managerial and employee perspectives: while managers often frame AI readiness through formal programs and oversight, employees emphasize the need for hands-on training, transparent data practices, and participatory communication. Results indicate that cross-functional teams and policy clarity are significantly associated with higher perceived success of AI initiatives, particularly among managerial respondents, yet do not uniformly predict satisfaction with adoption processes. The findings highlight that technical readiness alone is insufficient; fostering trust, transparency, and organizational agility is equally critical to effective and ethical AI integration. These insights extend existing AI adoption frameworks and underscore the value of qualitative perspectives in understanding cultural dynamics that shape technology implementation.
Paper
The full text of this publication is not hosted on 44B due to licensing.
Read it at OpenAlex