Artificial Intelligence in Business: A Case Study

MKT 625 (6250)

Examiner Prof. Dr. Florian Stahl
Performing Lecturer Dr. Dominic Bergers
Assessment Assignment (50%) and Presentation (50%)
Credit Points 2 ECTS
Graded yes
Workload 60h
Semester Spring and Fall
Duration of module 1 semester
Language English
Forms of teaching and learning Seminar
Contact hours 2 SWS
Independent study time 4 SWS
Registration required yes
Accepted Participants M.Sc. MMM, M.Sc. MMOSCM
Schedule Website of the Chair / “Student Portal“

Further Information

  • Brief Description

    The course Business AI for Marketing and Sales introduces students to the strategic application of artificial intelligence in modern business environments. The course is entirely case-based and conducted in close collaboration with partner companies. Depending on the specific challenges and objectives of the partner, the case study may extend beyond marketing and sales to cover the entire value chain.
    Students work in teams on a real-world business case, exploring how digital transformation and AI-driven technologies can create value and support innovation across the organization. The course emphasizes the practical design, development, and evaluation of AI-based solutions in a real business context.
    Important: This course does not include classical lectures or frontal teaching. Instead, students work independently and in groups on the assigned case.

    Learning outcomes
    Upon successful completion of this course, students will be able to:

    • Understand and critically assess the role of AI across marketing, sales, and broader business processes.
    • Analyze and design digital customer journeys and business processes using innovative tools and platforms.
    • Apply AI-driven techniques such as predictive analytics and personalization in real-world business contexts.
    • Collaborate effectively in teams to solve complex, real-world business problems through digital and AI-based innovation strategies.
    • Communicate and present structured, actionable solutions to industry partners.

    Recommended prerequisites
    Basic knowledge of marketing concepts and digital technologies is helpful. Prior experience with data analysis or artificial intelligence is not required. Students should be comfortable working independently, collaboratively, and ina highly practice-oriented, case-driven learning environment.