Generative Künstliche Intelligenz als Entscheidungsunterstützung: Perspektiven für das Operations- und Supply Chain Management

Abstract

The present thesis examines the supportive role of generative artificial intelligence in decision-making within operations and supply chain management of manufacturing companies. Due to a lot of predicted impacts of generative language models on businesses in the upcoming years, this thesis analyzes both the potentials and the challenges of this new technology. Empirical data is gathered through case studies and expert interviews to evaluate the practical benefits, ethical implications, and the synergy between humans and AI. The findings indicate that generative AI efficiently processes large amounts of data and generates content, facilitating data-driven and well-informed decisions. At the same time, the thesis emphasizes the necessity of a clear division of roles, with humans remaining responsible for ethical considerations, creative tasks, and final decisions. Generative AI is employed in data collection and analysis, thereby supporting problem-solving and decisionmaking processes. Finally, practical recommendations for the effective use of generative AI are developed, promoting sustainable and responsible integration into business processes. The thesis also provides an outlook on future developments, highlighting the importance of customized language models and continuous training to further optimize the collaboration between humans and AI.

Date of Award	2024
Original language	German (Austria)
Supervisor	Klaus Altendorfer (Supervisor)