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2025/2026  KAN-CGMAA5008U  The Future of Work: Towards Human-AI Collaboration in the Workplace

English Title
The Future of Work: Towards Human-AI Collaboration in the Workplace

Course information
Language English
Course ECTS 3 ECTS
Type Elective
Level Full Degree Master
Duration Summer
Start time of the course Summer
Timetable Course schedule will be posted at calendar.cbs.dk
Min. participants 30
Max. participants 60
Study board
Study Board for Governance, Law, Accounting & Management Analytics
Programme Master of Science (MSc) in Economics and Business Administration - General Management and Analytics (GMA)
Course coordinator
  • Liana Razmerita - Department of Management, Society and Communication (MSC)
This is a course offered by CBS as member of Euridice project. (https:/​/​euridice.eu/​introduction/​)

For academic questions, please contact Liana Razmerita (lra.msc@cbs.dk)
Main academic disciplines
  • Information technology
  • Management
  • Organisation
Teaching methods
  • Blended learning
Last updated on 03/11/2025

Relevant links
Learning objectives
By the end of the course, the participants should be able to:
  • Define and formulate a research problem or a case study around the changing nature and future of work
  • Identify and discuss opportunities and challenges that are brought about by AI integration in digital work practices in the selected case(s)
  • Apply key concepts and theoretical frameworks from the course to analyze the case(s) of human-AI collaboration as type of digital work
  • Reflect critically on your experience and learning process during the course
Course prerequisites
Completed bachelor or master degree or equivalent.
Examination
The Future of Work: Towards Human-AI Collaboration in the Workplace:
Exam ECTS 3
Examination form Active participation

The completion of this course is based on active student participation in class. The course will be considered as passed if the students participation - based on an overall assessment - in the class activities fulfill the learning objectives of the course. The individual student’s participation is assessed by the teacher.
The student must participate in A combination of assignment and presentation
Individual or group exam Individual exam
Grading scale Pass / Fail
Examiner(s) Assessed solely by the teacher
Exam period Summer
Make-up exam/re-exam 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.
Size of written product: Max. 5 pages
Assignment type: Essay
Duration: 20 min. per student, including examiners' discussion of grade, and informing plus explaining the grade
Examiner(s): If it is an internal examination, there will be a second internal examiner at the re-exam. If it is an external examination, there will be an external examiner.
Description of activities
A combination of assignment and presentation: The student must participate in minimum 80% of the scheduled teaching.

The completion of this course is based on active student participation in class. The course will be considered as passed if the students participation based on an overall assessment in the class activities and group presentations in order to fulfill the learning objectives of the course. The individual student’s participation is assessed by the teacher.
Course content, structure and pedagogical approach

Throughout the course, participants are expected to critically reflect on the role of AI in the changing nature and future of work, both in terms of the opportunities and challenges accompanying new digital work practices as well as the potential consequences brought about by AI integration in work practices at different levels of analyses (e.g., at individual, group or organizational level).

 

Knowledge work continues to develop and evolve though widespread adoption of AI. The advent of AI has further accelerated the transition to digital work practices and brought new forms of Human-AI collaboration. By harnessing the capabilities of AI technologies, digital work practices are integrating AI in work processes in multi-faceted ways considering AI even as a co-worker. This is relevant for high-skilled knowledge workers in different fields of activity including creative, financial, and service industries.  

 

This course is targeted at students and professionals interested in learning about the opportunities and challenges associated with the changing nature and future of work empowered by AI. The course focuses on how digital technologies (e.g., artificial intelligence, algorithmic management) are leveraged to support collaboration and innovation within cultural and institutional contexts as well as the consequences, intended or otherwise, stemming from their usage. Additionally, we will deliberate on the role of leadership and its associated strategies for managing the future of work alongside the Sustainable Development Goals (SDGs) being implemented by organizations.

 

The course will offer a fundamental coverage of the following topics:

  • Opportunities and challenges associated with new work practices involving AI
  • Introduction to AI and the role of AI as a digital technology in facilitating or hindering knowledge work
  • Implication of new work practices on knowledge flows, group work and innovation
  • Dynamics of managing digital work practices using AI for collaboration, competitiveness and/or innovation
  • Influence of leadership and cultural conditions on adoption of AI enhanced work practices  
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
  • Development of research questions
  • Data collection
  • Discussion, critical reflection, modelling
  • Students conduct independent research-like activities under supervision
Description of the teaching methods
This course embraces a blended learning structure that comprises a mix of in-class lectures and workshops combined with online activities. Students, in groups or individually, will build on theoretical concepts and case studies covered during in-class lectures and workshops to construct a mini project for the examination.
Teaching will take place primarily through traditional face to face learning but will be supplemented with online materials (e.g. videos or podcasts).
Feedback during the teaching period
Participants will receive instructors’ and peer feedback during assignements and workshops.
Student workload
Lectures 12 hours
Workshops 6 hours
Preparation for lectures and workshops 44 hours
Preparation for exam 22 hours
Further Information

This is an intensive 2-weeks course that cannot be combined with any other course.
Expected literature

Some references for the course. The full list of readings will be available on Canvas

 

Gal, U., Jensen, T. B., & Stein, M. K. (2020). Breaking the Vicious Cycle of Algorithmic Management: A Virtue Ethics Approach to People Analytics. Information and Organization, 30(2), 100301.

 

KPMG. (2024). Future of work: Shaping the workforce of the future with AI. https:/​/​kpmg.com/​xx/​en/​our-insights/​ai-and-technology/​future-of-work.html

 

Raisch, S., & Krakowski, S. (2021). Artificial Intelligence and Management: The Automation–Augmentation Paradox. Academy of Management Review, 46(1), 192–210. https:/​/​doi.org/​10.5465/​amr.2018.0072

 

Razmerita, L., Brun, A., & Nabeth, T. (2021). Collaboration in the Machine Age: Trustworthy Human-AI Collaboration in M. Virvou, G. Tsihrintzis, & J. Lakhmi (Eds.), Advances in Selected Artificial Intelligence Areas - World Outstanding Women in Artificial Intelligence (p. 23). Springer Nature.

 

Sarala, R. M., Post, C., Doh, J., & Muzio, D. (2025). Advancing Research on the Future of Work in the Age of Artificial Intelligence (AI). Journal of Management Studies, 62(5), 1863–1884. https:/​/​doi.org/​10.1111/​joms.13195

 

Stefanski, H., Hall, B., Gittleson, J., & Glazer, J. (2025). Development in the Future of Work. https:/​/​www.mckinsey.com/​featured-insights/​people-in-progress/​reimagined-learning-and-development-in-the-future-of-work
Last updated on 03/11/2025