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2026/2027  KAN-CFSAO1008U  Business Project

English Title
Business Project

Course information
Language English
Course ECTS 7.5 ECTS
Type Mandatory
Level Full Degree Master
Duration One Semester
Start time of the course Spring
Timetable Course schedule will be posted at calendar.cbs.dk
Study board
Study Board for Finance, Economics & Mathematics
Programme MSc in Economics and Business Administration - Finance and Strategic Management (FSM)
Course coordinator
  • Ali Mohammadi - Department of Strategy and Innovation (SI)
Main academic disciplines
  • Corporate governance
  • Finance
  • Strategy
Teaching methods
  • Blended learning
Last updated on 21-10-2026

Relevant links
Learning objectives
The purpose of the AI Research Project is for students to carry out and communicate a problem-oriented piece of scholarly work in which AI is used as a central tool in the research process. The project is intended to develop students' ability to formulate research questions, design and conduct investigations, analyze and discuss results, and apply AI in an academically and methodologically sound manner.
The project is based on a problem statement chosen from a range of topics made available by the course coordinator at the start of the project.

The grade of 12 is given when students, in an outstanding manner, i.e. with no or only a few minor shortcomings, demonstrate that they are able to:
  • Apply concepts and analytical skills acquired during the first year of graduate study to a specific problem
  • Refine the broad problem statement made available at the start of the examination period and formulate one or more clear research questions.
  • Formulate, design, and carry out a research project based on a well-defined problem statement and relevant research questions.
  • Design and document an AI-supported research workflow that significantly expands the project's analytical possibilities, data foundation, or knowledge synthesis compared with traditional working methods.
  • Document the use of AI and critically evaluate the quality of AI-generated output, as well as identify and address potential sources of error, bias, hallucinations, and other limitations
  • Communicate the project's content, methodological choices, and results clearly and concisely in an academic report produced within a limited timeframe and through teamwork.
Examination
Business Project:
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 Oral group exam based on written group product
Number of people in the group 3-4
Size of written product Max. 15 pages
Assignment type Project
Release of assignment An assigned subject is released in class
Duration
Written product to be submitted on specified date and time.
15 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 Spring, Written product to be submitted on specified date and time. The oral examination is based on the written product.
Make-up exam/re-exam
Same examination form as the ordinary exam
* if a whole group fails the exam they must hand in a new product for the re-take.
* if one student in the group fails the exam the examiner chooses whether the student will have the re-take on the basis of a new or a revised project.
Description of the exam procedure

Guidelines regarding release of assignment:

Research topics are provided by faculty members at the beginning of the project period. Students select a topic and develop a specific research question within the selected topic.

 

The project is conducted in groups over a period of approximately one month.

 

Faculty members provide research topics within finance, economics, corporate governance and/or strategy. Students form groups and select among the available topics.

Within the selected topic, the group refines the broad problem statement into one or more clear research questions and conducts an independent research project.

 

Supervision is organized in research clusters. Groups working on related research topics are supervised together by a faculty member. Cluster supervision gives students the opportunity to receive feedback on their own project while also learning from the questions, methods and challenges discussed by other groups in the same research area.

 

The final written product may not exceed 15 pages and forms the basis for the oral group examination. During the oral examination, each student is assessed individually on their understanding of the project, including the research question, methodology, analysis, findings, and use of AI.
Course content, structure and pedagogical approach

The course is a foundation course and complementary to all courses taught in the first year of the FSM concentration.

 

Students work in groups on a faculty-provided research topic and conduct a problem-oriented research project. The course combines common workshops, cluster supervision and independent group work.

 

Common workshops

  • Course introduction: The course director explains the course design and rationale, presents the requirements and answers students' questions.
  • AI workshop: A workshop on the use of AI tools and AI agents in the research process.

 

Cluster supervision

Groups with related research topics are organized into research clusters. Each cluster is associated with a faculty supervisor. Supervision takes place in a group setting so that students can learn from both direct feedback on their own work and discussion of other projects in the cluster.

 

Independent group work

Students develop the research questions, conduct the investigation, analyze the results and prepare the written product. AI is used as a central tool in the research process, and its use is documented as part of the project. Students must critically evaluate AI outputs and remain fully responsible for the accuracy, logic, originality, and quality of their work. Submitting work, they do not understand or relying on AI in place of developing and analysing their own arguments is unacceptable.

 
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
  • Methodology
Research-like activities
  • Development of research questions
  • Data collection
  • Analysis
  • Discussion, critical reflection, modelling
Description of the teaching methods
The course combines student group work with two common workshops and a cluster-based academic supervision. Faculty members provide research topics connected to their research areas, and groups working on related topics are placed in research clusters.
Feedback during the teaching period
Students obtain feedback on their work in progress through cluster supervision. The cluster format allows students to receive feedback on their own project and to learn from feedback and discussion related to other projects within the same research topic area.
Student workload
Class workshops and cluster supervision 10 hours
Project work and exam 196 hours
Expected literature

All of the literature in the FSM concentration's first-year curricula. Additional literature and methodological material depend on the research topic selected by the group.
Last updated on 21-10-2026