Arvolähtöisen ja sosioteknisen generatiivisen tekoälyn hyödyntämisen mahdollistaminen kokonaisarkkitehtuurin liiketoimintakyvykkyyksien avulla: Tapaustutkimus korkeakoulusektorilta

Generative artificial intelligence (GenAI), particularly tools based on large language models (LLMs), is increasingly influencing higher education, yet its organizational-level, value-driven utilization considering both business and technological perspectives remains underexplored. This thesis examines GenAI utilization in a higher education case organization by integrating three components: GenAI as a technological change driver, enterprise architecture via the HERM business capability model as a structured map for navigating this change, and sociotechnical systems theory as an interpretative framework for explaining the interconnection between technical and social aspects of the change. To investigate the phenomenon in practice, the study was conducted as a qualitative single-case study using semi-structured interviews with representatives at the tactical level of the core value-generating areas of the case organization, teaching & learning as well as research. The aim was to explore current and perceived future GenAI use cases, as well as identified risks and challenges. The interview data were analyzed using thematic analysis. The findings show that GenAI utilization is most prominent in quite general and knowledge-intensive tasks across both teaching and research, as well as in planning and delivery phases. The results further indicate that GenAI has a more substantial structural impact on teaching and pedagogical practices than on research, which remains more strongly shaped by disciplinary community. In addition, the findings highlight the importance of reducing uncertainty and increasing GenAI literacy through informal, low-threshold training, as well as enabling secure, use-case-specific, and useable GenAI tools while considering usage data quality, suitability, and accessibility. Theoretically, the thesis confirms and extends prior research on the topic as well as applies sociotechnical systems theory to GenAI utilization in higher education, reinforcing the joint-optimization principle and interdependence of sociotechnical dimensions. Practically, the study demonstrates how business capability–based enterprise architecture via the HERM model can be used to map, prioritize, and develop GenAI use cases in the higher education context.