Utmaningarna med att införa chattbot: En fallstudie kring vilka kritiska framgångsfaktorer som kan ha betydelse för implementering av AI-baserade chattbotar i en organisations kundsupport

Sammanfattning: Previous studies highlight the major technological advances in artificial intelligence (AI) and the benefits of introducing artificial intelligence systems in the form of chatbots in, among other things, customer support. They also describe the impact of chatbots on organizations. Artificial intelligence technology provides computers with the ability to display human-like traits, such as reasoning, creativity, learning and planning. The advantages of artificial intelligence-based chatbots can be, for example, improved processes in customer support, reduced costs and less burden on employees regarding monotonous tasks. It is important beforehand, and also during the course of the project, to have a well-functioning operation from an organizational and technical perspective. If there are problems within the business that are not addressed, this can have consequences. It is therefore not only the implementation of the chatbot that should be focused on in order to succeed with the change, but also organizational and technical parts of the business that will very likely be affected by the implementation. About 87% of artificial intelligence system implementation projects fail. This is because several factors relating to the project or to the product implemented have not been taken into account. Therefore, this study investigates the research question: What critical success factors need to be considered when implementing chatbots in customer support? The purpose of this research question is to identify which critical success factors (CSFs) are most necessary for decision makers to be aware of. This is to have better conditions to succeed with the implementation and use of artificial intelligence-based chatbots in customer support. To answer this question, a qualitative study has been carried out in the form of a case study with interviews as a data collection method. Respondents relevant to the research area have been interviewed. In conducting this study, thematic analysis has been used as a data analysis method to identify, analyze and report patterns in the collected data. These have then been used to answer our question. The result generated 3 themes, 15 categories and 45 codes. The categories are divided according to critical success factors from previous studies identified using the codes extracted from the interviews. These critical success factors are in turn divided into three different themes that represent the different characteristic features among the factors, these are organizational, technical and resource factors. The critical success factors that are included in the theme organizational factors are: Lack of benefits visibility, Change management, Organizational culture, Organizational structure, Resistance and Ambiguous strategic vision. In the technical factors: Ethics issues, Insuf icient quantity of data, Integration complexity, Low data quality, Data governance issues, Security and confidentiality and Scalable and flexible system. The theme resource factors include: Selection of vendors and High cost of AI. The conclusion of this study suggests that there are a variety of critical success factors of organizational, technical, and resource-related nature that are important to consider when implementing chatbots in customer support. Those considered to be of the highest priority are the technical factors. Next in line are the organizational factors Organizational culture, Organizational structure and Resistance, followed by the rest of the factors in the same theme. The factors considered to be of the lowest priority are the ones included in the theme resource factors. There are also critical success factors from previous studies, that this study builds upon, that are considered not important enough to take into account. The critical success factors generated in this investigation are discussed regarding how the data extracted has a connection to a certain critical success factor. In the discussion, critical success factors generated are compared with the critical success factors from previous studies. Since this is a case study containing a limited number of respondents, there is of course a likelihood that there are more critical success factors affecting customer support chatbot implementation projects. However, the critical success factors that this study resulted in are considered to be of higher priority and can therefore have the greatest impact on such a project.