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2026/2027  KAN-CINTV2601U  Building AI Business Ventures in Digital Ecosystems

English Title
Building AI Business Ventures in Digital Ecosystems

Course information
Language English
Course ECTS 7.5 ECTS
Type Elective
Level Full Degree Master
Duration One Semester
Start time of the course Autumn
Timetable Course schedule will be posted at calendar.cbs.dk
Max. participants 100
Study board
Study Board for Digitalisation, Technology and Communication
Programme MSc in Business Administration and Information Systems
Course coordinator
  • Ioanna Constantiou - Department of Digitalisation (DIGI)
Main academic disciplines
  • Entrepreneurship
  • Information technology
  • Innovation
Teaching methods
  • Blended learning
Last updated on 19-01-2026

Relevant links
Learning objectives
To achieve the grade 12, students should meet the following learning objectives with no or only minor mistakes or errors:
  • Identify, select and combine key theoretical concepts from the course, and apply them to describe an AI business venture
  • Analyze competition in the global digital arena where the new, AI business venture is positioned
  • Propose a business strategy for the new, AI venture and explain the main components
  • Explain how the AI digital venture can grow and expand exploiting user-generated data
  • Propose an evolutionary trajectory of the AI venture and identify its main components
Examination
Building AI Business Ventures in Digital Ecosystems:
Exam ECTS 7,5
Examination form Oral exam based on written product

In order to participate in the oral exam, the written product must be handed in before the oral exam; by the set deadline. The grade is based on an overall assessment of the written product and the individual oral performance, see also the rules about examination forms in the programme regulations.
Individual or group exam Individual exam
Size of written product Max. 5 pages
Assignment type Synopsis
Release of assignment Subject chosen by students themselves, see guidelines if any
Duration
Written product to be submitted on specified date and time.
20 min. per student, including examiners' discussion of grade, and informing plus explaining the grade
Grading scale 7-point grading scale
Examiner(s) Internal examiner and second internal examiner
Exam period Winter
Make-up exam/re-exam
Same examination form as the ordinary exam
Course content, structure and pedagogical approach

The course portrays digtial ecosystems as exciting competitive arenas with a number of global digital platforms, such as Apple, Facebook and Google, providing digital goods and services. There are numerous business opportunities to develop innovative digital products and services. Focusing on AI business ventures, students will be taught c oncepts, models, and economic principles that are useful in analyzing digital ecosystems, creating an AI business venture and developing a sustainable strategy. The special characteristics of the AI enabled  products and services in specific industries will be integrated in order to build sustainable strategies for the AI business ventures in the light of competitive dynamics in the international digital arena.

The course includes topics such as data network effects, positive feedback in creating the installed customer base, multi-sided networks etc., value capture and value creation strategies, internationalization strategies for digital platforms and global competitive dynamics. Specific topics of interest for AI digital business ventures will be covered, such as, data foundation, data goverenance and algorithms for value capture and value creation activities of the new venture.
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
Description of the teaching methods
The course combines online teaching activities with class teaching activities and discussions. In addition, students will apply the above topics through group discussions and presentations based on contemporary cases.
Feedback during the teaching period
During the first session the students will be prompt to decide on the business idea for the project they prepare for the synopsis. In the following sessions the students will be provided feedback on how the topics of each session could relate to their project through a set of questions presented in the slides that would be discussed in the corresponding session. The option of in person meetings for the preparation of tte synopsis will be offered.as well.
Student workload
Lectures online & physical 20 hours
Exercices/discussions online or physical 10 hours
Preparations for discussions in the class 10 hours
Preparation for the lectures-course literature 110 hours
Written project for the exam 56 hours
Total 206 hours
Expected literature

The literature can be changed before the semester starts. Students are advised to find the final literature on Canvas before buying any books.

 

Jarrahi, M.H., Monahan, K. & Leonardi, P. (2023). What Will Working with AI Really Require?. Harvard Business Review. 1-8

 

Leonardi, P. M., & Neeley, T. (2022). The digital mindset: What it really takes to thrive in the age of data, algorithms, and AI. Harvard Business Review Press

 

Reeves, M., Lotan, H., Legrand, J., & Jacobides, M. G. (2019). How business ecosystems rise (and often fall). MIT Sloan Management Review, 60(4), 1-6.

 

Ruokonen, M., & Ritala, P. (2024). How to succeed with an AI-first strategy?. Journal of Business Strategy, 45(6), 396-404.



 
Last updated on 19-01-2026