Kulturelle und organisationale Voraussetzungen für den Einsatz künstlicher Intelligenz zur Entscheidungsunterstützung

Abstract

Artificial intelligence (AI) is becoming increasingly important and is changing fundamental workflows, structures and decision-making processes in organisations. Despite technological progress, there are considerable differences in the actual integration and utilisation of AI systems in practice. In particular, cultural and structural framework conditions are considered essential factors for the successful implementation of AI in companies. Current studies show that the challenges in the use of AI are not exclusively on a technical level, but rather due to organisational deficits. In the Germanspeaking EU region, strict data protection guidelines, hierarchical structures and a lack of willingness to change on the part of many companies also make the successful integration of AI systems more difficult. The aim of this master's thesis is therefore to identify cultural and organisational prerequisites that enable companies to use AI sustainably for decision support and to derive practical recommendations for action. This thesis is divided into a theoretical and an empirical part. In the theoretical section, relevant basics on AI, maturity models as well as corporate culture and structure are analysed. Based on this, a category system is created, which forms the basis for the empirical study. Ten semi-structured interviews with experts from various companies were conducted to collect data. The aim was to gain a comprehensive understanding of the current practice of cultural and structural factors to promote AI maturity. The research results confirm a high level of agreement between theory and practice. Agile and innovative ways of thinking and methods, effective change management, interdisciplinary collaboration and the targeted development of expertise and knowledge were identified as key cultural prerequisites. At a structural level, the strategic anchoring of AI, the provision of financial resources, regulatory requirements and the integration of AI into existing processes are particularly relevant. In addition, the hierarchical embedding of AI as well as defined roles and responsibilities contribute significantly to a successful AI implementation. In addition, practice-relevant factors were identified that have been insufficiently considered in existing maturity models. These include company-specific differences, such as company size or industry, as well as different requirements depending on the target group addressed. Moreover, the highly dynamic nature of AI systems, in particular their speed of development, poses a challenge for their introduction in companies. Another result shows the different significance of AI at an operational and strategic level. While AI is already being used more widely at an operational level, it has so far only played a supporting role at a strategic level. The results underscore that successful AI integration requires a continuous adaptation process that considers both technological developments and organisational conditions. This study therefore makes a practical contribution to the development of future-proof companies while also providing a solid basis for future research on the organisational prerequisites for AI adoption.

Date of Award	2025
Original language	German (Austria)
Supervisor	Patrick Brandtner (Supervisor)