2031 Artificial Intelligence in the Consumer Experience
Dr. Melanie Clegg
Contact details
Weekly hours
Language of instruction
09/13/23 to 09/17/23
Registration via LPIS
Notes to the course
This class is only offered in winter semesters.
Day Date Time Room
Tuesday 10/03/23 09:00 AM - 12:00 PM TC.4.12
Tuesday 10/10/23 09:00 AM - 12:00 PM TC.4.12
Tuesday 10/17/23 09:00 AM - 12:00 PM TC.4.12
Tuesday 11/07/23 08:30 AM - 01:00 PM TC.4.12
Tuesday 11/14/23 09:00 AM - 12:00 PM TC.4.12
Tuesday 12/05/23 08:00 AM - 02:00 PM TC.4.12

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 research. Particularly, it will focus on and discuss 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 research (i.e., cover behavioral sciences). 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 investigating consumer reactions directed towards AI. Based on this theoretical foundation and enriched by guest lectures, students will work on a project covering a research question (or a business problem) related to the successful implementation of AI in a consumer context.

In particular, in this course you will

  1. acquire a fundamental overview of research insights on consumer experiences with AI. The course particularly draws on several psychological mechanisms that explain how we perceive AI, and how AI influences consumer 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 is preferably a specific research question, but may also be a 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 group report of your project after the course.
Learning outcomes

The aim of the course is to provide participants with knowledge about individuals’ technology adoption, as well as train them in critical thinking regarding behavioral science. Overall, the course is focused on developing and conducting behavioral research and scientific approaches related to AI applications. 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 research insights on  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 points
  • Group report with critical reflection on own group project (e.g., ethical reflections): 30 points
  • Peer evaluation of group work: 10 points
  • Participation in discussion during lectures: 10 points

The project presentation and group report are graded at group level. The peer review is used to assess the individual contribution of each group member to the group project. Participation grades depend on active participation in in-class discussions on scientific articles that need to be prepared for each session.

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

Prerequisites for participation and waiting lists

This course is part of the elective pool "Current Challenges in Digital Marketing" of the MSc Marketing at WU.

MSc Marketing students can only register if they have successfully completed the following mandatory courses from the 1st year:

  • Management by Experiments (5 ECTS)
  • Marketing Analytics (7.5 ECTS)
  • Digital Marketing (5 ECTS)

Please log in with your WU account to use all functionalities of read!t. For off-campus access to our licensed electronic resources, remember to activate your VPN connection connection. In case you encounter any technical problems or have questions regarding read!t, please feel free to contact the library at

Last edited: 2023-06-06