About this Course
As AI systems become more powerful and embedded across industries, the need for effective governance is no longer optional – it’s essential. This course explores how organisations can ensure that AI tools are not only effective but also safe, fair, and accountable throughout their lifecycle. You’ll learn to identify key risks such as bias, misalignment, and overreliance, and explore why even well-intentioned AI systems can fail. From ethical frameworks to incident response plans, this course provides practical tools to embed trust into every stage of AI development and deployment. Using real-world scenarios and governance models like the Trustworthy AI Cycle, you’ll examine how principles such as transparency, oversight, and explainability can be operationalised in business settings. Whether you're selecting vendors, building internal systems, or crafting policy, this course equips you to lead AI implementation with integrity. With case studies, strategic frameworks, and implementation guidance, you’ll leave with a roadmap for aligning AI systems with legal, ethical, and societal expectations. This is the third course in the AI Foundations for Business Professionals specialisation. To get the most out of this course, we recommend completing AI Essentials and Generative and Agentic AI beforehand to build both the technical understanding and applied context for responsible AI leadership
What You'll Learn
- Apply governance frameworks to ensure transparency and accountability
- Analyze risks such as bias and overreliance
- Design incident response plans for AI systems
- Operationalize trustworthy AI principles in business settings
Prerequisites
- Basic understanding of AI concepts
- Interest in policy, risk, or strategic deployment
Instructors
Matthias Holweg