2347 Artificial Intelligence in the Consumer Experience
Dr. Melanie Clegg
Contact details
Weekly hours
Language of instruction
09/14/22 to 09/18/22
Registration via LPIS
Notes to the course
This class is only offered in winter semesters.
Day Date Time Room
Tuesday 11/22/22 09:00 AM - 10:30 AM D2.0.392
Tuesday 11/29/22 09:00 AM - 12:00 PM D2.0.392
Tuesday 12/06/22 09:00 AM - 12:00 PM D2.0.392
Tuesday 12/13/22 09:00 AM - 12:00 PM D2.0.392
Friday 12/16/22 09:00 AM - 12:00 PM TC.4.16
Tuesday 12/20/22 09:00 AM - 12:00 PM D2.0.392
Tuesday 01/10/23 09:00 AM - 12:00 PM TC.3.11
Tuesday 01/17/23 09:00 AM - 12:00 PM D2.0.038


From ranking of news media and social media content to the communication via voice assistants and chat bots - artificial intelligence (AI) is ubiquitous. Considering the huge potential of artificial intelligence, business leaders and marketing scholars need to attain a deeper understanding of chances and challenges of AI, and its multiple implications on consumers.

This course is designed to provide participants with a deeper understanding about the applications of AI in consumer and marketing contexts, as well as psychological mechanisms and ethical considerations that influence consumer experiences with different aspects of AI (e.g., data collection, classification, task delegation, decision making, social and communication).

Although we cover the theory of the technology behind AI (no coding required), the main focus is its application in marketing and consumer contexts. The course will start with foundations and a definition of AI. It will then dive into different applications of AI in the consumer experience by analyzing and discussing cutting-edge research and practical examples. Based on this theoretical foundation and enriched by guest lectures, students will develop an own business problem or research question related to the successful implementation of AI in a marketing or consumer context.

In particular, in this course you will

  1.        acquire a fundamental overview of applications of AI on the one hand, and insights into psychological mechanisms that drive consumer experiences with AI on the other hand. The course particularly draws on several psychological concepts and biases that explain how we perceive AI, and how AI changes our ways of thinking, decision making, and behavior.
  2.        evaluate and discuss cutting-edge research articles in this timely domain. Students shall be ready to prepare and discuss current research articles as a discussion foundation for the course lecture.
  3.        apply the theoretical concepts to a relevant and current case in a group project. You will work together with international students on a self-selected case. The case can either be a specific research question or a concrete business problem related to the application of AI in a consumer context. Either way, the question should be very specific (e.g., develop design principles for a service bot, or develop a solution for data collection concerns of a voice assistant). In a final session, you present your case, followed by a joint discussion. You are required to hand in a critical reflection of your group project as an essay after the course (individual work).

Learning outcomes

The aim of the course is to provide participants with knowledge about individuals’ technology adoption relevant for corporate purposes, as well as train them in critical thinking regarding behavioral science. By the end of the course, participants should be able

  •        to understand psychological aspects and fundamental ethical concerns regarding the application of AI in consumer contexts
  •        to understand and reflect critically on current research articles
  •        to be able to leverage scientific insights about e.g., psychological mechanisms in order to develop promising business strategies or research projects
  •        communicate more effectively in their own argumentation and presentation of results

In addition you will have developed your professional skills regarding practical business applications of AI, creative and critical scientific thinking, and working in teams.

Attendance requirements

Participation in all sessions is mandatory. You may miss up to max. 20% of lecture hours, but please note that content is build-up in a modular way. Thus, absences should be minimized to ensure your optimal learning outcomes.

Teaching/learning method(s)

  •        Self-study (reading of scientific articles and own researches of articles to prepare group project topic)
  •        In-class discussions in lectures
  •        Team presentation of group project
  •        Critical reflection of group project


Your grade will be the sum of the following components (max. 100 points)

  • Final project presentations: 50 pts
  • Essay with critical reflection on own group project (e.g., ethical reflections): 30 pts
  • Peer evaluation of group work: 10 pts
  • Participation in discussion during lectures: 10 pts

The project presentation is graded at group level, while the written group project is graded at the individual level. The peer review is used to assess the individual contribution of each group member to the group project.

Grades are as follows: 90 pts or more: 1 (= excellent), 80 pts or more: 2 (= good), 70 pts or more: 3 (=satisfactory), 60 pts or more: 4 (= sufficient), 59 pts or less: 5 (= fail).

Last edited: 2022-06-02