Course for Masters of Science in Information Systems, Masters of Science in Management & Master’s Degree in Law, Crime and Security of Information Technology every spring semester
General Description
This course explores the strategic, managerial, and organizational implications of AI in today’s business landscape. It aims to provide a comprehensive understanding of how AI technologies transform organizational processes, decision-making, and competitive dynamics. Through theoretical lectures, business cases and guest lecturers, the course equips students with the tools to critically assess and effectively manage AI initiatives within diverse organizational contexts.
Goals
Last two decades have seen rapid adoption of Artificial Intelligence (AI) algorithms in organizations. AI algorithms have the potential to benefit businesses by reducing coordinating costs and enhancing decision-making accuracy. At the same time, management and adoption of AI in organizations create new challenges. This course explores the integration of AI in Management within business organizations.
At the end of the course, students should be able to:
1. Understand implications of AI in management.
2. Identify opportunities for AI projects and structure a team around it.
3. Identify problems in AI adoption, propose a feasible solution in resolving them and structure and explain its reasoning.
4. Identify opportunities within management for applying AI applications and structuring and organizing such applications.
5. Understand implications of augmenting managerial decision-making with AI.
Contents
The course will be divided into various modules and will cover the following topics:
- Technical Foundations
- AI and business models
- AI and Strategy
- AI and Innovation
- AI and Decision making
- Managing AI
- Algorithmic Management
- AI Risks & Governance
- Prompt Engineering for Managers
This course comprises of three components:
1. In-class theoretical lectures: In-class theory lectures are aimed to build a fundamental knowledge of implications of intersection of AI and management.
2. Group work on business cases: Business cases are designed to help students critically examine application of AI in management as well as managing AI projects.
3. Guest lecturers: We will invite guests from industries who are already managing AI or using AI in management.