Year: 2026
Type: dissertation
Abstract: Generative AI diffuses rapidly at the individual level, yet organizations struggle to convert pilots into routinized, scalable value. Prior research and practitioner discourse largely frame generative AI adoption as a technical or managerial challenge, offering limited insight into how generative AI behaves within the socio-technical work system — even though many of the difficulties practitioners encounter are fundamentally socio-technical in origin. This thesis examines how established Finnish organizations build capabilities for generative-AI–enabled value creation, drawing on socio-technical systems theory and dynamic capabilities. The study employs an interpretive, abductive research design and the Gioia methodology, based on ten semi-structured interviews with firms across industrial, healthcare, and digital service domains. The findings show that generative AI functions not as a conventional tool but as a socio-technical actor whose performance depends on how well the surrounding system provides relevant knowledge, workflow integration, and iterative feedback. As a result, organizations face a structural adoption–scaling friction: while use cases emerge easily, turning them into stable capability requires (1) proximity between technical, business, and knowledge-capital capabilities, (2) continuous experimentation and iteration, and (3) feedback loops to upstream data and organizational knowledge systems. These requirements systematically push organizations toward hybrid structures and distributed sensing, seizing, and reconfiguring activities. The thesis contributes a conceptualization of generative AI capability as a socio-technical configuration that mediates between existing capabilities and AI-enabled outcomes. It advances mainly socio-technical theory by explaining why generative AI is difficult to routinize and by identifying the structural conditions under which scaling becomes possible. Practical implications highlight how organizations can design governance, workflows, and knowledge-capital development to enable sustained value realization.
Source: Aaltodoc (Aalto University)
Author: Takala, Elias
Language: English
Subfield: Management Information Systems
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7134999814