Change-Management Aktivitäten bei der Einführung von KI-Systemen in Organisationen

Abstract

Artificial Intelligence (AI) has already transformed various sectors of the world, both in private and professional contexts, and it currently does not seem like this will stop any time soon. Due to the benefits of using AI in organizations, such as process and quality improvements or automation, many organizations aim to implement this technology. However, effective AI implementation requires not only identifying suitable application areas but also addressing additional factors to fully realize AI's potential within organizations. One of these factors is the appropriate management of the change associated with the introduction of an AI system, commonly known as change management. Change management seeks to support the implementation of an AI system by preparing the organization and its employees for the new technology and facilitating its acceptance. To understand which activities organizations, undertake in practice to support such implementation, this master's thesis aims to identify the relevant change management activities. The research question of this thesis is: "Which change management activities are conducted during the implementation of AI systems in organizations?" Broad categories of change management activities were derived from the literature, which are carried out during AI implementations. This theoretical background was also used to create a guide for semi-structured expert interviews on this topic. Eight interviews were conducted with experts and were analyzed using Mayring's qualitative content analysis. Categories of change management activities identified from the literature served as the basis for category formation, which were then refined and adjusted inductively from the interview text material. The research findings indicate that change management activities during the implementation of AI systems in organizations fall into the categories of "Conducting communication," "Engaging stakeholders," "Utilizing supportive roles," "Building knowledge," and "Setting usage incentives." The identified change management activities include: communicating the added value of the AI system; addressing expectations of AI; using symbols and metaphors in communication; communicating fundamental information about AI, the system, and the project; promoting general collaboration with stakeholders; jointly developing use cases; gathering feedback and addressing questions; clarifying professional changes; winning and utilizing sponsors and leaders; establishing and utilizing change networks, champions, and agents; explaining the system's functionality; building fundamental knowledge about AI; recognizing exceptional performance; and setting structural incentives.

Date of Award	2024
Original language	German (Austria)
Awarding Institution	Johannes Kepler University Linz
Supervisor	Thomas Michael Fischer (Supervisor)