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.