Digital Transformation & Artificial Intelligence 3: Business, Governance & Policy in the Digital Age
Niveau
Second cycle, master's
Learning outcomes of the courses/module
The participants:
• understand and correctly classify key concepts of digital transformation and AI.
• develop digital strategies for sustainable and responsible corporate governance.
• are able to analyze practice-oriented case studies and formulate their own recommendations for action for digital business models.
• recognize the challenges of digital transformation and AI in practice and discuss them critically.
• understand and correctly classify key concepts of digital transformation and AI.
• develop digital strategies for sustainable and responsible corporate governance.
• are able to analyze practice-oriented case studies and formulate their own recommendations for action for digital business models.
• recognize the challenges of digital transformation and AI in practice and discuss them critically.
Prerequisites for the course
-
Course content
• Fundamentals of digital transformation and artificial intelligence
• Digital business models and innovation strategies
• Impact of digital transformation and AI on companies, the economy and governance structures
• Strategic, regulatory and ethical challenges
• Digital initiatives of the European Union (e.g., EU Industrial Strategy for a digital Europe, EU Chips Act, Digital Services and Digital Markets Acts, etc.)
• Digital business models and innovation strategies
• Impact of digital transformation and AI on companies, the economy and governance structures
• Strategic, regulatory and ethical challenges
• Digital initiatives of the European Union (e.g., EU Industrial Strategy for a digital Europe, EU Chips Act, Digital Services and Digital Markets Acts, etc.)
Recommended specialist literature
Laudon, K.C., & Laudon, J.P.: Management Information Systems: Managing the Digital Firm, Pearson (latest edition)
Assessment methods and criteria
Portfolio assessment
Language
English
Number of ECTS credits awarded
4
Semester hours per week
Planned teaching and learning method
Blended Learning
Semester/trimester in which the course/module is offered
3