PhD Defence: Dijana Aleksic

Abstract

While technologies have long reshaped organisational workflows, the dynamic nature of Artificial Intelligence (AI) leads us to question not only what it can do, but how work, relationships, and experiences are reshaped. This dissertation explores employees’ experiences of broad-application AI, embedded in everyday work through initiatives led by HR, Learning & Development, or IT. Adopting a relational approach, the dissertation’s three studies demonstrate that AI systems are not merely sets of functionalities, but are inseparable from the context in which they are situated, shaping and being shaped by employees, work practices, and organisational environments. Across different settings, the findings show that conversational AI (chatbots) can reduce work complexity in employee self-service and enhance employee motivation; that employees proactively combine organisational AI with externally available AI (including unendorsed “shadow AI”), reshaping tasks, relationships, and the meaning of work; and that generative AI opens new possibilities for creative actions and experiences, even in roles not traditionally considered creative. Overall, this dissertation offers scholars and practitioners insights into the relational dynamics of AI at work. It shows that the experience and value of AI are not predetermined by AI functionalities but emerge through its entanglement in work practices. The findings therefore reframe how we think about AI at work, inviting us to shift our focus from predominantly short-term efficiency gains towards long-term opportunities to build new relationships, create richer experiences, and achieve more meaningful outcomes for employees and organisations in AI-inclusive work.