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2026/2027  MA-MMBDV2601U  Future Tech for Business

English Title
Future Tech for Business

Course information

Language English
Course ECTS 5 ECTS
Type Elective
Level Part Time Master
Duration One Semester
Start time of the course Spring, Autumn
Timetable Course schedule will be posted at calendar.cbs.dk
Min. participants 0
Max. participants 40
Study board
Study Board for Master i forretningsudvikling
Programme Master of Business Development
Course coordinator
  • Michel Avital - Department of Digitalisation (DIGI)
Main academic disciplines
  • Information technology
Teaching methods
  • Face-to-face teaching
Last updated on 18-06-2026

Relevant links

Learning objectives
  • Identify and explain the concepts and methodologies that relate to the use of emerging digital technologies in business and organizational contexts.
  • Apply emerging digital technologies to develop new business models that can drive business innovation and digital transformation
  • Evaluate and critically reflect upon technology-driven business models and discuss how they may contribute to a business unit or case organization
Examination
Future Tech for Business:
Exam ECTS 5
Examination form Home assignment - written product
Individual or group exam Individual exam
Size of written product Max. 10 pages
Assignment type Case based assignment
Release of assignment An assigned subject is released in class
Duration Written product to be submitted on specified date and time.
Grading scale 7-point grading scale
Examiner(s) One internal examiner
Exam period Summer and Winter
Make-up exam/re-exam
Same examination form as the ordinary exam
'The use of AI tools for the written product is permitted provided it adheres to the guidelines outlined on the course page in Canvas and CBS rules.'
Description of the exam procedure

'The use of AI tools for the written product is permitted provided it adheres to the guidelines outlined on the course page in Canvas and CBS rules.'

Course content, structure and pedagogical approach

This course focuses on leveraging future technologies such as artificial intelligence, blockchain, robotics, and quantum computing to drive digital transformation and business innovation. You will learn how these technologies can be applied to create new business models, improve decision-making, automate processes, and optimise data management. The course provides insights into how organisations can prepare for the future by understanding and implementing the most relevant and optimal technologies in their business environment. The goal is to enhance the organisation’s ability to handle uncertainty, anticipate changes, and create value through a digital strategy. 

 

Your benefits

  • Understand new digital technologies in business contexts.
  • Develop new business models driven by digital innovation.
  • Critically reflect on technology-driven business models.
  • Tools to create and implement a digital strategy. 

 

Themes

  • Technology-based solutions for business innovation.
  • New business models for DeFi and future technologies.
  • Human-machine configurations (e.g., ChatGPT, chatbots, robots, smart contracts).
  • AI-driven decision-making.
  • Blockchain-driven decentralised platforms.
  • Large-scale automation with robots and algorithms.
  • Quantum computing-driven innovation. 

 

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
  • Models
Research-like activities
  • Development of research questions
  • Data collection
  • Analysis
  • Discussion, critical reflection, modelling
  • Activities that contribute to new or existing research projects
Description of the teaching methods
This interactive course includes a mesh of presentations on core topics by the instructors and hands-on workshops during which the participants practice the application of the newly acquired knowledge. Assigned reading material will prepare the participants for taking an active part in the class interactions.
Feedback during the teaching period
Feedback during class as well as efter examination.
Student workload
Teaching 28 hours
Preparation and exam 109,5 hours
Last updated on 18-06-2026