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2026/2027  KAN-CMIAV2601U  AI, Strategy, and Innovation (AISI)

English Title
AI, Strategy, and Innovation (AISI)

Course information
Language English
Course ECTS 7.5 ECTS
Type Elective
Level Full Degree Master
Duration One Quarter
Start time of the course First Quarter
Timetable Course schedule will be posted at calendar.cbs.dk
Max. participants 60
Study board
Study Board for Markets & Innovation
Programme MSc in Economics and Business Administration - Management of Innovation and Business Development (MIB)
Course coordinator
  • Lars Bo Jeppesen - Department of Strategy and Innovation (SI)
Main academic disciplines
  • Innovation
  • Organisation
  • Strategy
Teaching methods
  • Blended learning
Last updated on 27-01-2026

Relevant links
Learning objectives
After successfully completing the course, the student should be able to:
  • Explain how core AI and generative AI technologies reshape, innovation, strategy and business models
  • Discuss relevant theories, explain their assumptions, and present empirical evidence from the literature
  • Assess the role of AI-centric strategies, describe how they align innovation and strategy in organizations, and specify success and failure factors
  • Discuss ethical issues of AI and demonstrate knowledge of ethical safeguards and responsible governance in the era of AI
  • Critically assess emerging AI technologies and continuously update their knowledge and methods to keep pace with the field’s rapid evolution.
Examination
AI, Strategy, and Innovation (AISI):
Exam ECTS 7,5
Examination form Written sit-in exam on CBS' computers
Individual or group exam Individual exam
Assignment type Written assignment
Duration 2 hours
Grading scale 7-point grading scale
Examiner(s) One internal examiner
Exam period Winter and Winter
Aids Limited aids, see the list below:
The student is allowed to bring
  • USB key for uploading of notes, books and compendiums in a non-executable format (no applications, application fragments, IT tools etc.)
  • In Paper format: Books (including translation dictionaries), compendiums and notes
The student will have access to
  • Basic IT application package
  • Canvas
Make-up exam/re-exam
Same examination form as the ordinary exam
The number of registered candidates for the make-up examination/re-take examination may warrant that it most appropriately be held as an oral examination. The programme office will inform the students if the make-up examination/re-take examination instead is held as an oral examination including a second examiner or external examiner.
Course content, structure and pedagogical approach

Modern enterprises depend on AI for everyday efficiency, breakthrough innovation, and long-term strategic advantage. AI, Strategy, and Innovation (AISI) is built for master’s students of any background, providing the knowledge, judgment, and experiential learning required to manage in this AI-driven environment. The curriculum combines business fundamentals with the latest advances in generative AI, AI platforms, and the organization of “AI factories,” while consistently emphasizing responsible AI governance.

The teaching approach is case-centric: real-world examples such as Moderna, Videa Health, and Procter & Gamble illustrate strategic AI initiatives and motivate critical discussion. The course employs a blend of lectures, interactive case-based sessions, hands-on exercises, and guest lectures. It focuses on decision-making and innovation strategy around challenges faced by companies in digital transformation, strategy, innovation, and AI. Cases must be prepared for in-class discussion.
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
  • New theory
  • Teacher’s own research
Research-like activities
  • Discussion, critical reflection, modelling
Description of the teaching methods
The course will employ a variety of teaching forms, including lectures, interactive case based sessions, and hands-on exercises. Some sessions will be face-to-face and some will be online.
Feedback during the teaching period
During sessions there will be an opportunity for feedback from professors and peers.
Student workload
Lectures (7) 30 hours
Preparation 93 hours
Exam and preparation for exam 83 hours
Total 206 hours
Expected literature

Boudreau, K. & Jeppesen, L.B. & Miric, M., Artificial Intelligence as a Platform Technology: Strategic Implications of Competing on Top of an AI Platform (July 12, 2025).  https:/​/​ssrn.com/​abstract=5349634

 

Boussioux, Léonard, Jacqueline N. Lane, Miaomiao Zhang, Vladimir Jacimovic, Karim R. Lakhani (2024) The Crowdless Future? Generative AI and Creative Problem-Solving. Organization Sciencehttps:/​/​doi.org/​10.1287/​orsc.2023.18430 

 

Dell’Aquca et al. 2023. Navigating the jagged technological frontier: Field experimental evidence of the effects of AI on knowledge worker productivity and quality; Harvard Business School Technology & Operations Mgt. Unit Working Paper, 24-013

 

Iansiti, M., & Lakhani, K. (2020): Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World. Boston: Harvard Business Review Press, 2020

 

Case: Pernod Ricard: Uncorking Digital Transformation." Harvard Business School Case 624-095, May 2024.  Bojinov, Iavor, Edward McFowland III, François Candelon, Nikolina Jonsson, and Emer Moloney

 

Case: Building an AI Factory at Procter & Gamble. Harvard Business School Case 625-015, March 2025. Bojinov, Iavor I., Karim R. Lakhani, and Alexis Lefort.

 

Case: Moderna (A). Harvard Business School Case 621-032, September 2020,  Iansiti, Marco, Karim R. Lakhani, Hannah Mayer, and Kerry Herman.

 

VideaHealth: Building the AI Factory. Harvard Business School Case 621-021, March 2021. Karim R., and Amy Klopfenstein

 
Last updated on 27-01-2026