Tillit till AI-stöd i beslutsprocesser : En kvalitativ studie av hybridintelligens, rationalitet och komplementära kapabiliteter i verksamheter

Sammanfattning

Artificial intelligence (AI) is increasingly being used to support decision-making processes in organizations. This development has created new opportunities to analyze large volumes of data, improve efficiency, and enhance decision support. At the same time, it raises questions regarding trust, human judgment, accountability, and the interaction between humans and technology in organizational decision-making. The purpose of this study is to explore and gain an understanding of how decision-makers experience the interaction between humans and AI when using AI-based decision support systems in organizational decision-making processes. The study focuses particularly on the role of trust, complementary capabilities, and formal and substantive rationality in this interaction. The study adopts a qualitative research approach and is based on semi-structured interviews with eight respondents from different organizations and industries. The empirical material was analyzed using theories of hybrid intelligence, trust in AI, complementary capabilities, and formal and substantive rationality within a sociotechnical perspective. The findings show that AI is primarily used as a tool for information processing, analysis, and efficiency improvement rather than as a replacement for human decision-making. Respondents describe AI as providing speed, structure, and data-driven insights, while humans contribute contextual understanding, experience, and judgment. Trust in AI appears to be context-dependent and is influenced by the nature of the task, users’ experiences, and the ability to review and validate AI-generated recommendations. The study also demonstrates that decision-making processes are shaped by the interaction between AI’s formal rationality and human substantive rationality. The study contributes empirical knowledge regarding how AI-based decision support systems are used and experienced in organizations and highlights the importance of human judgment, trust, and complementary capabilities in AI-supported decision-making processes.