Explore our knowledge

MSc in Business Administration and Information Systems

Build­ing AI Busi­ness Ven­tures in Di­git­al Eco­sys­tems

About the course

Subjects
Entrepreneurship IT Innovation

Course content

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.

See course description in course catalogue

What you will learn

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

Facts

Level
Master
Type
Elective
ECTS
7.5
Code
CINTV2601U
Teaching periods
Autumn – semester
Academic year
2026/2027
Status
Available places
Teaching language
English
Teaching Format
Hybrid
Exams
  • Written assignment and oral exam on campus
    Individual exam, winter
Assessment type
  • 7 point grading scale