KI-generierte Texte im Marketing oberösterreichischer Industrieunternehmen: Anwendung und Herausforderungen

Abstract

In recent years, artificial intelligence has increasingly found its way into corporate processes – particularly in the field of text generation. Marketing departments, in particular, are now faced with the question of how these new technologies can be used effectively without compromising content quality, legal compliance, or brand identity. This thesis therefore addresses the question: "How do marketing departments of industrial companies in Upper Austria use AI-generated texts?" The aim is to examine how companies apply AI-based text tools, which goals they pursue, and what challenges arise from their use. The structure of this thesis is divided into two main parts. The first part outlines the theoretical foundation, focusing on artificial intelligence. This includes definitions, historical milestones, and technical explanations, as well as an overview of relevant providers of generative AI platforms. The second theoretical section explores the role of AI in a marketing context, covering fundamental marketing concepts, potential applications, and associated challenges. The empirical part of the study is based on six expert interviews with marketing professionals from Upper Austrian industrial companies. The analysis shows that generative AI tools are already in use across all interviewed companies. Perceived challenges and potentials vary and are addressed in detail throughout the analysis. In the final part of the thesis, the defined research questions are answered. Based on the empirical findings, a future outlook is provided along with practical recommendations for action. This thesis thus offers not only a snapshot of the current status but also provides practice-oriented impulses for the future use of generative AI tools in industrial marketing.

Date of Award	2025
Original language	German (Austria)
Supervisor	Michael Kaufmann (Supervisor)