Einsatzmöglichkeiten von Künstlicher Intelligenz im Controlling zur Verbesserung des Forecasting-Prozesses

Abstract

The increasing complexity of economic decisions requires precise, efficient, and flexible management accounting processes. Artificial Intelligence (AI) offers the possibility to fundamentally optimise traditional forecasting methods in management accounting. This optimisation affects both the effectiveness of the processes and the role of employees. The motivation for this work lies in the fact that AI technologies can transform traditional forecasting processes so that agile decision-making processes receive timely and accurate information. This work is divided into several chapters that gradually explain the basics of AI, discuss its application in forecasting, and illuminate the resulting impacts on processes and employees. It begins with a theoretical foundation for AI, management accounting and the forecasting process, followed by a presentation of current research findings and existing AI applications in forecasting. In the practical part, it examines how AI can be used in forecasting, particularly in terms of automation through machine learning and neural networks. The methodological foundation of this work consists of comprehensive literature research and qualitative analyses of studies, practical examples, and use-cases that investigate the application of AI in real business environments. This work suggests that AI can significantly accelerate the forecasting process through the use of automation techniques and improved data analysis. This leads to a significant increase in efficiency. Furthermore, it becomes apparent that the role of employees in management accounting is changing: there is an increased need for skills in handling technological tools and data analysis. AI enables controllers to relieve themselves from repetitive tasks and instead focus on more challenging and productive activities. The results of this study emphasise the transformative effect of AI in management accounting. It points out that adjusting employee training and continuous qualification are essential to fully exploit the potential of Artificial Intelligence.

Date of Award	2024
Original language	German (Austria)
Supervisor	Christa Hangl (Supervisor)