Leitfaden zum Einführen von KI-Technologien in Produktionsunternehmen

Abstract

Artificial intelligence (AI) has become a key technology in today's world and offers enormous potential for innovation to increase efficiency and productivity in production companies. For instance, routine and time-consuming tasks can be automated by using AI, so that employees can focus entirely on other tasks. However, identifying possible potential for the use of artificial intelligence in companies is a major challenge due to the variety of business processes taking place, which makes automated or centralised investigations of this potential difficult. In addition, a corporate culture that does not sufficiently promote change or innovation in new technologies can be problematic. This lack of willingness to change means that AI initiatives are not sufficiently communicated, visualised or trained internally. This paper therefore addresses key aspects of the introduction of AI technologies in manufacturing companies and proposes solutions. The thesis is divided into seven main chapters, starting with an introduction to the topic and an extensive literature review. Here, basic models are discussed, and process models are compared with each other. Based on this literature research, success factors are elaborated that are essential for a sustainable introduction of AI technologies. Subsequently, the sum of results from the literature research was transferred to an operational context using the literature-practice transfer approach and a practical guideline for the introduction of AI technologies was developed. The results of the practical implementation in chapter 6 show a structured procedure for the processing of AI projects. With the help of key questions in combination with an evaluation scheme, potential processes can be categorised in a matrix. The categorisation forms the basis for decision-making for further processing. In order to be able to make qualified decisions, an interdisciplinary team of specialists from different company departments is proposed. This procedure is supported by standard software such as Microsoft Forms and Microsoft Power BI.

Date of Award	2024
Original language	German (Austria)
Supervisor	Sonja Straßer (Supervisor)