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2025/2026  BA-BHAAV2501U  AI in the Boardroom: Responsible Innovation from Google, NVIDIA, and Microsoft

English Title
AI in the Boardroom: Responsible Innovation from Google, NVIDIA, and Microsoft

Course information
Language English
Course ECTS 7.5 ECTS
Type Elective
Level Bachelor
Duration One Quarter
Start time of the course First Quarter
Timetable Course schedule will be posted at calendar.cbs.dk
Max. participants 100
Study board
Study Board of General Management
Course coordinator
  • Christina Lubinski - Department of Business Humanities and Law (BHL)
  • Siddhesh Rao - Department of Business Humanities and Law (BHL)
Main academic disciplines
  • Entrepreneurship
  • Management
  • Leadership
Teaching methods
  • Blended learning
Last updated on 30-01-2025

Relevant links
Learning objectives
  • Understand the fundamental concepts of AI and how it impacts various business domains, including strategy, leadership, and entrepreneurship.
  • Identify the ethical, societal, and environmental implications of AI use in business.
  • Evaluate AI-driven business opportunities and risks.
  • Develop AI strategies that align with responsible and sustainable business goals.
  • Assess strategies to lead teams effectively in adopting AI, facilitating AI adoption while fostering a culture of responsibility.
  • Create policies and governance frameworks to ensure AI is used in a way that supports transparency, accountability, and inclusivity.
Examination
AI in the Boardroom: Responsible Innovation from Google, NVIDIA, and Microsoft:
Exam ECTS 7,5
Examination form Home assignment - written product
Individual or group exam Individual exam
Size of written product Max. 15 pages
Assignment type Written assignment
Release of assignment The Assignment is released in Digital Exam (DE) at exam start
Duration 72 hours to prepare
Grading scale 7-point grading scale
Examiner(s) One internal examiner
Exam period Autumn, the exam immediately follows the course.
Make-up exam/re-exam
Same examination form as the ordinary exam
The retake is the same as the regular exam. The retake can be conducted as an oral exam, if necessary.
Description of the exam procedure

The exam consists of a case study analysis: Students are given a detailed case where a company faces dilemmas with its AI strategy. They will be asked to develop a strategic response, including ethical considerations, risk assessment, and mitigation strategies. This can include either a discussion of the role of leadership in ensuring responsible AI deployment or the task of developing an AI policy, considering potential pitfalls and governance challenges.
Course content, structure and pedagogical approach

This course explores the intersection of Artificial Intelligence (AI) with responsible business practices. It aims to equip future business leaders, entrepreneurs, and strategists with the skills to understand, implement, and lead AI-driven initiatives responsibly. The focus is on using AI ethically, ensuring that technology aligns with societal values, maintains transparency, and drives sustainable and inclusive business success. Students will examine case studies, engage in practical AI scenarios, and develop strategic frameworks to implement AI responsibly within organizations.
Research-based teaching
CBS’ programmes and teaching are research-based. The following types of research-based knowledge and research-like activities are included in this course:
Research-based knowledge
  • Classic and basic theory
  • New theory
  • Teacher’s own research
Research-like activities
  • Development of research questions
  • Analysis
  • Discussion, critical reflection, modelling
  • Activities that contribute to new or existing research projects
Description of the teaching methods
The teaching approach for this course is designed to create an engaging, dynamic, and practical learning environment that combines theory with real-world applications. A variety of methods will be employed to cater to diverse learning styles, encourage active participation, and ensure that students leave the course with both the conceptual understanding and practical skills to apply responsible AI in business settings.

- Case Method: This course will utilize case studies from real-world business scenarios to illustrate how AI is used successfully and where it has failed ethically or strategically. Each case study will focus on AI’s role in leadership, strategy, or entrepreneurship, exploring both opportunities and challenges.

- Lectures/Flipped Classroom: Lectures will be interactive, combining traditional instruction with multimedia content such as videos, guest presentations, and AI simulation demonstrations. These lectures will provide foundational knowledge on AI concepts, ethical considerations, and business applications. The flipped classroom model will involve students reviewing readings, videos, and foundational content outside of class, freeing up in-class time for practical application, group activities, and deeper discussions.

- Guest Speakers: Industry experts will share their experience with AI in leadership, entrepreneurship, and strategy. These sessions will be interactive, with opportunities for Q&A and discussion.
Feedback during the teaching period
Throughout this course, you will receive a variety of feedback to support your learning, encourage critical thinking, and help you apply responsible AI principles effectively.

- Active participation in class discussions is highly encouraged. During sessions, the instructors will provide real-time feedback on your contributions, recognizing insightful points and correcting misunderstandings. After class, we may follow up with individual comments to reinforce key points or suggest further exploration.

- After quizzes and assignments, we will offer feedback that explains correct answers, addresses common errors, and provides suggestions for improvement.

- We encourage you to attend regular office hours for more personalized feedback on assignments or any aspect of the course. Additionally, we will host "drop-in" virtual feedback sessions for those who prefer a more informal opportunity to discuss their progress and get targeted advice.
Student workload
Preparation 98 hours
Teaching 38 hours
Examination 72 hours
Expected literature

Books

  • Prediction Machines: The Simple Economics of Artificial Intelligence by Ajay Agrawal, Joshua Gans, and Avi Goldfarb.
  • Human Compatible: AI and the Problem of Control by Stuart Russell.
  • Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell.

 

Articles and case studies

  • Harvard Business School cases.
  • "The Business of Artificial Intelligence" by Erik Brynjolfsson and Andrew McAfee (Harvard Business Review).
  • "Why Companies That Wait to Adopt AI May Never Catch Up" (MIT Sloan Management Review).
  • "Building the AI-Powered Organization" by Tim Fountaine, Brian McCarthy, and Tamim Saleh (McKinsey Quarterly).

 

Reports

  • European Commission’s White Paper on Artificial Intelligence - A European Approach to Excellence and Trust.
  • McKinsey Global Institute Report: Notes from the AI Frontier: Insights from Hundreds of Use Cases.
Last updated on 30-01-2025