Artificial Intelligence im Unternehmenskontext

: Die Identifikation und Integration von AI-Potenzial zur Steigerung der Wettbewerbsfähigkeit

Abstract

The relevance of the topic, “Artificial Intelligence in the Corporate context - Identifying and Integrating AI Potential to increase competitiveness” also provided the motivation for writing this master thesis, as the use of artificial intelligence is much discussed, and people are confronted with new AI applications almost daily in everyday life and in the world of work. Analysts and strategy consultancies are also forecasting a significant increase in annual sales for companies over the next few years using AI. The aim of this master's thesis is to work out the current state of research on AI and to show with practical examples how companies in the chemical industry are using AI applications along their supply chain in the current state of research, thus positively influencing their competitiveness. For the content of this thesis, literature research is used as the methodology for chapters 1 - 4 and desk research is also used for chapters 4 - 6 to identify practical examples. The master thesis begins with an introduction in which the problem, the objective and the structure of the thesis are defined. This is followed by a definition of the term artificial intelligence, in which the development of AI over time is presented and, building on this, the current state of research is explained. Strategic supply chain management is then discussed in more detail. The terms supply chain, supply chain management and supply chain strategy are described, and the generic supply chain strategy types are talked about in further detail. In the next chapter, strategic information planning is described specifically and the definitions of information systems, IS management, strategic information system planning, IS strategy and IT strategy are elaborated and differentiated from one another. Building on this, Chapter 5 first defines the term business-IT alignment and then links the two terms supply chain management and AI. To this end, areas of application for AI in supply chain management are presented and illustrated using general, practical examples. The last chapter serves to substantiate the theoretical input with practical examples of AI applications from the chemical industry and thus demonstrate the current state of AI applications in the chemical industry. The result of this work is an overview of the current state of the use of AI in the supply chain of the chemical industry. The use of artificial intelligence can create an automated infrastructure for companies in general and thus improve the flow of information. As a result, business processes can be optimized and made more efficient, and future decisions can be predicted more accurately. The practical examples from the chemical industry have shown that the use of AI is already in full swing and that companies in a wide variety of areas are aligning their business processes with an AI-supported solution. It can be deduced from this that the use of artificial intelligence can improve the day-to-day work and processes of a company, as personnel, energy, costs, and resources in general can be saved and processes can be designed efficiently.

Date of Award	2024
Original language	German (Austria)
Supervisor	Gerold Wagner (Supervisor)