Managing AI School of Business and Economics for Professionals

Managing AI beyond the hype

This course equips you to make informed, responsible decisions about AI with confidence and impact. It guides you through the full spectrum of managing AI: from strategy development and evaluating trade-offs in tools and technologies, to overseeing development and implementation, and finally to addressing the ethical and longer term questions that AI raises.

Participants who successfully complete this course, will:

Understand the role of data as strategic asset for diverse business applications
understand what AI technologies are, including the latest generative AI tools, and how they differ from other related technologies
understand what AI technologies can and cannot do and be able to make informed decisions on the development, implementation and use of AI
have sufficient knowledge to ask the right questions to the development team and other organizational stakeholders
gain in-depth insights into concrete use cases for developing, implementing, and using AI systems in organizations
collect a set of best practices for managing AI development and implementation
reflect on intended outcomes of AI technologies and potential pitfalls, ripple effects, and ethical concerns

The Managing AI programme addresses the complex challenges of AI adoption and governance. It combines cutting-edge academic research with real-world case studies, ensuring participants gain practical, actionable insights. Throughout the programme, you will work on an assignment that connects directly to your organisational context. You will also benefit from structured opportunities for discussion, peer learning, and feedback. This ensures the learning is directly relevant and immediately applicable.

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Introduction & Module 1
Module 2
Module 3
Module 4
Module 5 and Module 6

Introduction & Module 1: Strategizing for AI and defining effective AI use-cases

Strategizing for AI and defining effective AI use-cases

Focus points Introduction & Module 1:

Defining strategic opportunities in relation to AI
Defining and aligning AI business models
Establishing and orchestrating data/AI governance and ecosystem

Module 2: All you need to learn about AI as a manager

All you need to learn about AI as a manager

Focus points Module 2:

Foundations of AI
Understanding the different forms of algorithmic technologies: rule-based, predictive, generative, and agentic AI
Exploring, articulating, and evaluating AI use cases

Module 3: Managing AI lifecycle within organizations

Managing AI lifecycle within organizations

Focus points Module 3:

Managing AI development process: from in-house development to co-creation
Managing AI implementation into the existing workflow and systems
Managing AI adoption and organizational transformation

Module 4: Managing AI at work

Managing AI at work

Focus points Module 4:

Working with AI as a manager: augmenting your work and practices
Fostering performance, creativity, and coordination through AI
Stimulating continuous learning at work around AI

Module 5: Managing AI ethically, legally, and responsibly Module 6: Integration and roadmap

Managing AI ethically, legally, and responsibly/Integration and roadmap

Focus points Module 5&6:

Module 5

Ethical and legal considerations, practices, and frameworks
Sustainable adoption and use of AI at work
Establishing guardrails for managing risks and unintended consequences of AI

Module 6

Integrating all the elements into an AI roadmap for your initiatives
Peer feedback and individual mentoring on the roadmap
Presentation of the roadmap with feedback from AI experts

Introduction & Module 1
Introduction & Module 1: Strategizing for AI and defining effective AI use-cases

Strategizing for AI and defining effective AI use-cases

Focus points Introduction & Module 1:
Defining strategic opportunities in relation to AI

Defining and aligning AI business models

Establishing and orchestrating data/AI governance and ecosystem
Module 2
Module 2: All you need to learn about AI as a manager

All you need to learn about AI as a manager

Focus points Module 2:
Foundations of AI

Understanding the different forms of algorithmic technologies: rule-based, predictive, generative, and agentic AI

Exploring, articulating, and evaluating AI use cases
Module 3
Module 3: Managing AI lifecycle within organizations

Managing AI lifecycle within organizations

Focus points Module 3:
Managing AI development process: from in-house development to co-creation

Managing AI implementation into the existing workflow and systems

Managing AI adoption and organizational transformation
Module 4
Module 4: Managing AI at work

Managing AI at work

Focus points Module 4:
Working with AI as a manager: augmenting your work and practices

Fostering performance, creativity, and coordination through AI

Stimulating continuous learning at work around AI
Module 5 and Module 6
Module 5: Managing AI ethically, legally, and responsibly Module 6: Integration and roadmap

Managing AI ethically, legally, and responsibly/Integration and roadmap

Focus points Module 5&6:
Module 5

Ethical and legal considerations, practices, and frameworks

Sustainable adoption and use of AI at work

Establishing guardrails for managing risks and unintended consequences of AI

Module 6

Integrating all the elements into an AI roadmap for your initiatives

Peer feedback and individual mentoring on the roadmap

Presentation of the roadmap with feedback from AI experts

Managing AI

Participants who successfully complete this course, will:

Introduction & Module 1

Focus points Introduction & Module 1:

Module 2

Focus points Module 2:

Module 3

Focus points Module 3:

Module 4

Focus points Module 4:

Module 5 and Module 6

Focus points Module 5&6:

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