The Integration of AI and Involved Humans into Decision-Making Structures: A Multiple-Case Study

Abstract

The growing significance of artificial intelligence in global industries is evident and accelerates each year. This progression is visible in the doubling of private investments to $93.5 billion in 2021 from the previous year. The specific research problem of this study is that there is a lack of understanding of the perceptions of top- and middle-management leaders about the integration of AI and involved humans into their decision-making structures. The purpose of this qualitative multiple case study is to explore the perceptions of top- and middle-management leaders about the integration of AI and involved humans into their decision-making structures in the automotive industry in 2024 in Germany. By conducting a qualitative multiple-case study grounded on a comprehensive literature review and the actor-network theory as a conceptual framework, the study has derived a process to successfully integrate humans and AI in decision-making processes supported by best practices to further increase the acceptance level of human users. The process consists of 5 major fields, which are connected: Current challenges in decision-making processes, potential of AI to improve decision-making processes, concerns and risks on AI integration in decision-making processes, influence on human and human involvement, and initial process recommendation and areas for successful AI integration. Practical implications include the changing role of stakeholders and the evolving decision-making process by the introduction of AI. The results further provide theoretical expansions of knowledge of AI and humans in decision-making processes. Further research should focus on quantitative studies based on my results to validate the emerged theories further.