(Dis)Integration of AI & Sustainability: A Case Study of Organizational Meaning Creation

Abstract

This thesis explores how the contemporary strategic domains of sustainability and AI are organizationally understood, prioritized, and potentially brought into relation. It examines how meaning is constructed around these domains, how they are framed, and how these frames influence their (dis)integration. Anchored in a social constructionist and interpretivist research philosophy, the study uses a single case of a Danish multinational organization where both domains hold strategic relevance. Through a qualitative multi-method design, data was collected via seven semi-structured interviews with domain experts, supported by secondary sources such as industry and company reports, strengthening the empirical foundation. Through abductive analysis, our findings reveal a pronounced asymmetry in how sustainability and AI are framed. Sustainability is constructed as a deeply embedded organizational value, rooted in legacy, reinforced by symbolic communication and external validation. In contrast, AI is framed as a strategically promising yet fragmented domain, shaped by top-down ambitions but enacted through dispersed initiatives. These divergent framings create siloed structures, incompatible knowledge infrastructures, and separate discourses that hinder cross-domain integration. A strategic tension emerges: while there is growing recognition that AI must align with sustainability goals, raising such concerns prematurely risks derailing innovation, revealing a delicate balancing act between sustainability involvement and AI ambitions. Furthermore, despite AI’s perceived value for sustainability, varying levels in digital maturity, ambiguity around ownership and limited managerial attention reinforce organizational inertia. The lack of shared meaning, governance mechanisms, and external devices, such as regulations or benchmarks, prevents a unified narrative from forming. Ultimately, the thesis shows that the barrier to integration is not technical, but caused by the lack of coherent, shared meaning across domains, leaving sustainability and AI to continue on separate organizational tracks.