AdobeStock.Prostock-studio
AI in strategic management
level of course unit
1. Zyklus MasterLearning outcomes of course unit
The participants:
• have a basic understanding of Generative AI and LLM and can assess how Generative AI works.
• can identify potential areas of application for Generative AI in strategic management.
• have basic knowledge of different generative models and can assess their areas of application and functionality.
• are aware of the ethical aspects of dealing with generative models and are able to reflect on the potential effects of their application.
• are able to identify various possible applications of generative AI in strategic management.
• develop an understanding of how generative models enable efficiency increases and innovation potential in companies.
• are able to assess which (management) tasks in companies can be automated using Generative AI.
• understand how Generative AI can be used to improve customer interaction and personalization.
• have a basic understanding of Generative AI and LLM and can assess how Generative AI works.
• can identify potential areas of application for Generative AI in strategic management.
• have basic knowledge of different generative models and can assess their areas of application and functionality.
• are aware of the ethical aspects of dealing with generative models and are able to reflect on the potential effects of their application.
• are able to identify various possible applications of generative AI in strategic management.
• develop an understanding of how generative models enable efficiency increases and innovation potential in companies.
• are able to assess which (management) tasks in companies can be automated using Generative AI.
• understand how Generative AI can be used to improve customer interaction and personalization.
prerequisites and co-requisites
none
course contents
• Überblick über Generative KI und ihre Anwendungsbereiche
• Einführung in Large Language Models (LLM)
• Anwendung von Generativen KI-Modellen in der Bild- und Textgenerierung
• Ethische Überlegungen im Umgang mit Generativen Modellen
• Automatisierung von (Management-)Aufgaben und Geschäftsprozessen
• Kundeninteraktion und Personalisierung
• Prognosen und Analytik zur Nutzung von KI im strategischen Management
• Einführung in Large Language Models (LLM)
• Anwendung von Generativen KI-Modellen in der Bild- und Textgenerierung
• Ethische Überlegungen im Umgang mit Generativen Modellen
• Automatisierung von (Management-)Aufgaben und Geschäftsprozessen
• Kundeninteraktion und Personalisierung
• Prognosen und Analytik zur Nutzung von KI im strategischen Management
recommended or required reading
• Foster, D. (2019): Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play
• Goodfellow, I., Bengio, Y., Courville A. (2016): Deep Learning
• Teik Toe, T., Yu Jin, G. (2023): Artificial Intelligence in Business Management
• Goodfellow, I., Bengio, Y., Courville A. (2016): Deep Learning
• Teik Toe, T., Yu Jin, G. (2023): Artificial Intelligence in Business Management
assessment methods and criteria
Portfolio
language of instruction
Germannumber of ECTS credits allocated
6eLearning quota in percent
35course-hours-per-week (chw)
3planned learning activities and teaching methods
ILV
