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2025/2026  KAN-CGMAA5001U  Applications of Artificial Intelligence in Marketing

English Title
Applications of Artificial Intelligence in Marketing

Course information
Language English
Course ECTS 3 ECTS
Type Elective
Level Full Degree Master
Duration Summer
Start time of the course Summer
Timetable Course schedule will be posted at calendar.cbs.dk
Min. participants 30
Max. participants 60
Study board
Study Board for Governance, Law, Accounting & Management Analytics
Programme Master of Science (MSc) in Economics and Business Administration - General Management and Analytics (GMA)
Course coordinator
  • Johannes Hattula - Department of Marketing (Marketing)
Main academic disciplines
  • Information technology
  • Marketing
Teaching methods
  • Face-to-face teaching
Last updated on 03/11/2025

Relevant links
Learning objectives
On completion of this course, students should:
  • Gain a comprehensive understanding of artificial intelligence, its role in revolutionizing marketing activities, and its significance for business growth and competitiveness
  • Understand how to apply artificial intelligence to real-world marketing scenarios
  • Develop an understanding how artificial intelligence creates value for both organizations and consumers
  • Develop awareness of ethical considerations related to AI-driven marketing
Examination
Applications of Artificial Intelligence in Marketing:
Exam ECTS 3
Examination form Active participation

The completion of this course is based on active student participation in class. The course will be considered as passed if the students participation - based on an overall assessment - in the class activities fulfill the learning objectives of the course. The individual student’s participation is assessed by the teacher.
The student must participate in Assignment(s)
Individual or group exam Individual exam
Grading scale Pass / Fail
Examiner(s) Assessed solely by the teacher
Exam period Summer
Make-up exam/re-exam Oral exam based on written product
In order to participate in the oral exam, the written product must be handed in before the oral exam; by the set deadline. The grade is based on an overall assessment of the written product and the individual oral performance.
Size of written product: Max. 5 pages
Assignment type: Essay
Duration: 20 min. per student, including examiners' discussion of grade, and informing plus explaining the grade
Examiner(s): If it is an internal examination, there will be a second internal examiner at the re-exam. If it is an external examination, there will be an external examiner.
Description of activities
Assignment(s): Students are expected to participate in the class discussions, exercises and in-class presentations.

In addition the student must participate in minimum 80 % of the scheduled teaching.
Course content, structure and pedagogical approach

What is the main purpose of this course?

This 2-week course provides an in-depth exploration of how advances in artificial intelligence (AI) can be harnessed to revolutionize marketing activities. Participants will gain a comprehensive understanding of how AI technologies (including generative AI and increasingly agentic AI) are transforming the field of marketing and can support business growth. Through practical examples and case studies(e.g., Amazon, Netflix, Starbucks), students will gain the knowledge and skills needed to apply AI effectively in the marketing domain, and they will learn how to leverage AI for various marketing activities, from data collection and processes to customer segmentation to the marketing mix decisions (product management, pricing, communication management, sales).

 

This course is not about programming AI tools or statistical issues behind AI; the course takes a more practical approach and looks at how and where AI can be applied in today's marketing.

 

Why is this course relevant?

This course is highly relevant due to the transformative impact of AI on the business world. Many C-suite executives recognize the importance of scaling AI in their organizations to achieve growth objectives. However, they often struggle with implementation, as many business reports indicate. Furthermore, marketing is identified as the functional area where AI can provide the most value. Therefore, understanding how and where AI can be applied in marketing is essential for businesses to remain competitive and deliver substantial benefits to both companies and consumers. This course is designed to provide such understanding and help students to apply AI effectively in marketing contexts.

 

What topics will be discussed in this course?

The course demonstrates the impact AI has on today's marketing to create value for both organizations and consumers. For example, the followiong topics will be covered:

  • Understanding the basics of AI
  • Overview of AI applications in marketing
  • Applying AI in the contexts of:
    • Marketing research (e.g., collecting and processing data, synthetic respondents)
    • Customer segmentation
    • Innovation and product management (e.g., improving fit of product offering and consumer preferences)
    • Pricing (e.g., dynamic and intelligent pricing decisions)
    • Communication management (e.g., automated social media campaigns, virtual and AI influencers)
    • Customer relationships and service marketing (e.g., chatbots for customer support)
  • Ethical considerations of AI-driven marketing (e.g., biases, privacy concerns, environmental impact of AI)

 
Research-based teaching
CBS’ programmes and teaching are research-based. The following types of research-based knowledge and research-like activities are included in this course:
Research-based knowledge
  • Classic and basic theory
  • New theory
  • Teacher’s own research
  • Methodology
  • Models
Research-like activities
  • Development of research questions
  • Data collection
  • Analysis
  • Discussion, critical reflection, modelling
  • Activities that contribute to new or existing research projects
Description of the teaching methods
The course is designed to be highly interactive and build upon principles of active learning. Students are expected to contribute to discussions about the impact of AI and they are invited to do group exercises throughout the course.
Feedback during the teaching period
Feedback will be provided from the teacher and through group work.
Student workload
Class teaching 18 hours
Reading and preparation 66 hours
Further Information

2-week course that cannot be combined with other courses.

Expected literature

Selected readings include:

  • Grewal, Satornino, Davenport, and Guha (2025): How Generative AI Is Shaping the Future of Marketing, Journal of the Academy of Marketing Science, 53, 702-722.
  • Purdy (2025): What is Agentic AI, and How Will it Change Work? Harvard Business Review (online). 
  • Korst, Puntoni, and Toubia (2025): How GenAI is Transforming Market Research, Harvard Business Review, May-June 2025, 91-99.
  • Arora, Chakraborty, and Nishimura (2025): AI–Human Hybrids for Marketing Research: Leveraging Large Language Models (LLMs) as Collaborators, Journal of Marketing, 89 (2), 43-70.
  • Palumbo and Edelman (2023): What Smart Companies Know About Integrating AI, Harvard Business Review, 101(4), 116-125.
  • Huang and Rust (2021): A Strategic Framework for Artificial Intelligence in Marketing, Journal of the Academy of Marketing Science, 49, 30-50.
  • Kozinets and Gretzel (2021): Commentary: Artificial Intelligence: The Marketer’s Dilemma, Journal of Marketing, 85(1), 156-159.

 

Specific reading instructions will be given at the beginning of and throughout the course on Canvas.
Last updated on 03/11/2025