The AI-Enhanced Manager

Introduction

Please note that this is a preliminary course description. The final version will be published in June 2027.

In an era of rapid technological disruption, evolving customer expectations, and the transformative impact of artificial intelligence, marketing has become a central driver of strategic advantage and organizational growth. In this course, students will learn how to design and execute marketing strategies by harnessing data-driven insights into customer experiences, emerging needs, and long-term value creation for customers, partners, and the organization.

This course challenges students to think entrepreneurially and creatively about how AI-powered insights, customer and competitor data, and human-centred marketing strategy integrate to build brands, foster customer loyalty, and drive sustainable business growth. Grounded in the belief that marketing must directly enhance business relevance and impact, the course emphasizes action-based, experiential learning combined with rigorous in-class discussion of cases supported by empirical evidence from practice. Students will integrate diverse elements of marketing strategy and apply them directly by analysing quantitative data from case studies and real-world examples, developing solutions to a broad range of strategic marketing challenges.

Course content

The topics selected for this course are designed to deepen students’ understanding of the complex strategic marketing issues that drive firm performance. The course focuses in particular on the role of marketing strategy and the integration of diverse marketing elements in shaping business outcomes.

As the course progresses, students will develop a deeper appreciation of the trade-offs among different marketing activities and their impact on a firm’s bottom-line performance. Beyond addressing the pressing challenges marketing managers face today, the course emphasizes the importance of quantifying the financial impact of strategic marketing decisions, equipping students to build stronger, evidence-based business cases for marketing initiatives.

Tentative topics:

1. Understanding markets and consumers (Segmentation and Targeting)
2. Exploring competitive strengths and weaknesses, the market share-profitability (Positioning)
3. Customer-centric new product development (Conjoint and Willingness to Pay)
4. Forecasting growth and adoption (forecasting and Bass adoption model)
5. Marketing-mix trade offs
6. Predicting choice and spending amounts (Logit/Tobit regression models)
7. Resource allocation across channels and salespeople
8. Return on social media investments (panel regression)
9. AI and marketing strategy (synthetic samples, GenAI applications)