Syllabus

Title
2290 Artificial Intelligence in Marketing B
Instructors
Univ.Prof. Dr. Siham El Kihal
Contact details
Type
PI
Weekly hours
2
Language of instruction
Englisch
Registration
09/06/24 to 09/27/24
Registration via LPIS
Notes to the course
This class is only offered in winter semesters.
Subject(s) Master Programs
Dates
Day Date Time Room
Wednesday 12/04/24 03:30 PM - 06:30 PM TC.2.01
Wednesday 12/11/24 03:30 PM - 06:30 PM TC.0.04
Wednesday 12/18/24 03:30 PM - 06:30 PM TC.0.02
Wednesday 01/08/25 10:00 AM - 01:00 PM EA.6.026
Wednesday 01/15/25 10:00 AM - 01:00 PM TC.3.01
Wednesday 01/22/25 10:00 AM - 01:00 PM TC.3.01
Wednesday 01/29/25 10:00 AM - 01:00 PM TC.3.01
Contents

By 2024, the marketing world will have 8.4 billion AI-powered voice assistants at its fingertips, ready to answer every question and command[1]. No wonder the global AI adoption rate is increasing with more businesses hopping on board every day. The AI market in marketing was valued at $15.84 billion in 2021, with experts projecting it to soar to over $107.5 billion by 2028[2]! That's a giant leap in just a few years, showing that businesses everywhere are jumping on the AI bandwagon to enhance their marketing efforts.

 

Already today, marketing is embracing AI in various areas, such as text and image analytics, content creation, recommender systems and AI-based personalization. AI is helping marketing with personalized virtual assistants, customized savings plans, and futuristic service-free shops and independent stores.

 

The purpose of this course is to provide students with comprehensive understanding of these recent developments in AI through an introduction of fundamental AI concepts and practical applications of these concepts in marketing.


[1] https://www.statista.com/statistics/973815/worldwide-digital-voice-assistant-in-use/

[2] https://www.statista.com/statistics/1293758/ai-marketing-revenue-worldwide/

Learning outcomes

This course explores the intersection of AI and marketing. It provides students with an understanding of how AI is revolutionizing marketing strategies and tactics and empowers them with the knowledge and skills to effectively leverage AI tools and techniques. The course  on practical applications of AI in marketing, supported by real-world case studies and hands-on projects.

 

  • Understand the fundamental concepts and techniques of AI in the context of marketing.
  • Identify the potential applications of AI in various marketing domains.
  • Analyze and evaluate the ethical considerations and challenges associated with AI in marketing.
  • Develop practical skills in leveraging AI tools and platforms for marketing purposes.
  • Critically assess AI‘s social implications.
Attendance requirements

According to WU rules, you must attend 80% of the sessions in this course (corresponds to approximately one absence). Please drop us an email as early as possible in case you must miss a class. We will take attendance at the start of each class. Anyone who arrives after we finish taking attendance will be marked as “late”. You may have up to one “late” during the term. After that, we will deduct 0.5 points for each “late” from your individual assignment points. 

Teaching/learning method(s)

Students will acquire knowledge through a combination of class lectures, class discussions, case studies, assigned readings, and hands-on practical experience.

  • Students will be assigned relevant readings ranging from case studies and industry reports to recent scientific articles from top journals.

  • Students will study how Artificial Intelligence is used in practical business setting by analyzing recent business cases. We will discuss the following case this year:

“THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence”, by J. Avery, A. Israel, E. von Maur, Harvard Business School, March 2021.

  • Students will be able to work on a group project that uses marketing insights with modern AI technologies, for efficient and data-driven marketing strategies.

Note:

This is a tentative agenda and adjustments might be introduced throughout the semester.

Assessment

Group Project

45%

Individual Assignments

40%

Case Study

15%

Readings

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 readinglists@wu.ac.at.

Last edited: 2024-05-16



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