The course is conducted as an intensive teaching module with four subsequent full days, a total of 32 hours, supported by structured preparation in pre-class group work and post-class project work. The course aims to provide immediate value by connecting concepts to participants’ work experience and by using learning by doing. The course follows Fink’s taxonomy through a progression from foundational concepts to application, integration across functions, reflective learning to learn, and practical capability building.

The course is based on Design Thinking and uses a “flipped classroom” model. Students prepare by means of short readings, videos, and guided, case-based pre-tasks. Class time is used for alignment of theory and tools by means of structured discussion, interpretation, and application through in-class mini-cases. 

It uses Miro as the learning platform throughout, emphasizing collaborative learning within case groups as well as for the course paper. The use of the Miro platform serves several purposes: (1) to promote conceptual thinking and the critical evaluation of causal relationships, i.e., how the multidisciplinary learning material is understood , (2) to introduce critical thinking by means of collaborative learning and peer-to-peer sense-making, i.e., educational value is created in the groupwork processes, (3) to overcome barriers of interpretation and language through visualisation, (4) to develop the insight that AI-augmented knowledge networks are the digital era's organisation design, i.e., to enhance students’ employability and career progression.

AI is used primarily for learning-to-learn. Students use Miro’s embedded AI to support sense making, structure arguments, test alternatives, and improve clarity of visual models. Students will be provided with a set of workflow documents that show how to use the AI tools on the Miro platform. Students will be required to obtain the Miro badge “essential skills” as part of the course pre-work and to have the appropriate skills to work on Miro visual collaboration platform.

AI use must be transparent and evidence-based through a sequential prompt log and iteration trail on the Miro board. Cognitive offloading, meaning unexamined AI output, copy-paste answers, or AI replacing the student’s reasoning, is treated as poor academic practice and will reduce grade quality. Candidates may be cold-called in class to verify authorship and reasoning.