The MBA elective AI: Foundations and Applications provides a comprehensive overview of current AI developments and their business implications.

You will gain insight into core technologies, the strategic role of data, and the organisational, strategic, and regulatory frameworks required for responsible and value-creating AI deployment.

This course is designed for those who want to move AI from hype to action — and make informed decisions regarding investments, implementation, and governance.

What You Will Learn

Drawing on state-of-the-art AI technologies and real-world application cases, you will learn how to analyse and assess how AI can create value in your organisation.

You will gain, among other things:
• An overview of the AI landscape and key technological trends
• An understanding of data as a strategic resource
• Hands-on experience working with Large Language Models (LLMs)
• The ability to evaluate business opportunities and risks
• Insight into regulatory and ethical frameworks

How the Course Creates Value for Your Organisation

By working with your own organisational challenges and cases, your organisation will be able to:
• Identify and prioritise relevant AI initiatives
• Establish appropriate frameworks and governance structures for AI use
• Make informed technology decisions
• Navigate compliance requirements related to the AI Act and GDPR

Participant Profile

The course is designed for managers and decision-makers in private companies and public organisations who seek:
• A strategic understanding of AI’s business potential
• Insight into technological opportunities and limitations
• A solid foundation for leading AI initiatives within their organisation
Technical specialist expertise is not required; however, curiosity and a strategic interest in technology and data are essential.

Content and Structure

The course is structured around five key perspectives on organisational AI application:
1. The global AI landscape and technological developments
2. AI technologies and their application domains
3. Data as a prerequisite for AI
4. AI in the organisation – including LLMs and concrete use cases
5. Regulation, ethics, and responsible implementation

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