Artificiell Intelligens och Target Costing : En fallstudie om användningen av AI inom Target Costing-processen

Sammanfattning

Background: Target Costing (TC) is a cost management method that sets cost targets early in the product development process. Widely adopted in manufacturing industries, TC requires cross-functional collaboration and access to customer data. Artificial Intelligence (AI) can enhance TC by automating data collection and supporting decision-making. However, challenges related to trust, data security, and system integration make AI a complex yet relevant area of research in the context of TC. Purpose: The purpose of this study is to describe and analyze how AI is used within the different processes of TC, as well as how these processes are affected by AI. Particular emphasis is placed on identifying the types of AI tools applied in each stage of the process. In addition, the study aims to highlight the technological, organizational, and cultural barriers that influence the use of AI in TC, and to explore the future potential of its application within the process. Method: The study uses a qualitative approach to investigate people's experiences and perceptions of AI in TC-processes, based on semi-structured interviews with employees from different departments. The theoretical framework and research questions were developed iteratively through an abductive approach. Primary data was collected through interviews, and secondary data from previous research. The data was analyzed through thematic coding to identify connections between AI and TC processes. Conclusion: The study shows that AI has the greatest impact in the initial and final stages of the TC process, where it streamlines data collection and improvement efforts. However, the use of AI is more limited within core processes such as cost calculation and goal setting, often due to established routines and technical barriers. Factors such as data quality, information security, and organizational culture have limited implementation, but there is strong future potential if these barriers are overcome.