AI som effektivisering eller ersättning? En kvalitativ studie om hur ett stort internationellt SaaS-bolag inom ekonomisektorn hanterar AI-implementering organisatoriskt

Sammanfattning

This study examines how a large international SaaS-company within the financial sector approaches AI implementation at an organizational level. The aim is to develop a deeper understanding of how AI as an idea is interpreted, adapted, and translated into practice, as well as the role played by legitimacy and institutional expectations in these processes. The study employs a qualitative method, using semi-structured interviews with 15 respondents from different organizational levels and functions within the company. The theoretical framework draws on perspectives of organizational change, legitimacy, translation of management ideas, and complex organizational problems. The findings show that AI is understood both as a tool for efficiency and as a strategic necessity for the organization to be perceived as modern, competitive, and relevant. AI implementation is therefore driven by both internal needs, such as increased productivity and resource optimization, and external expectations from customers, competitors, and the broader market. The study also demonstrates that AI is not implemented as a fixed and uniform solution, but is translated and adapted differently depending on organizational level, function, and context. On strategic levels, AI is framed as a question of competitiveness and future positioning, while on operational levels it is experienced as a more limited support tool where practical benefits are not yet fully realized. The study further shows that AI is primarily described as a complement to human work, while simultaneously changing work roles, competence requirements, and ways of organizing work. The implementation process is characterized by a tension between rapid strategic ambitions and slower practical integration, creating what can be understood as an organizational shift rather than a purely technological implementation. The study contributes to a nuanced understanding of how AI functions as a complex organizational problem that requires continuous interpretation, local adaptation, andbalancing between internal efficiency and external legitimacy.