This course shows how artificial intelligence is changing marketing—from data, creativity, and customer understanding to sales, security, and professional competencies.

Use the course program below to explore the role of AI in contemporary marketing and develop the knowledge and practical skills needed to work with it critically, creatively, and responsibly.

What will you learn?

By the end of the course, you will be able to:

• explain how AI and generative AI are transforming marketing;
• describe how data, CRM systems, and AI tools support marketing decisions;
• use AI in customer analysis, segmentation, content creation, and sales-related tasks;
• critically evaluate and improve AI-generated outputs;
• identify ethical, privacy, security, and reliability risks associated with AI;
• use AI creatively and responsibly while maintaining human judgment.

Course program

Module 1

Marketing 6.0

You will learn how marketing evolves toward intelligent, immersive, and human-centered systems, and how the role of the marketer changes in Marketing 6.0.

Module 2

Machine learning and deep learning for marketing

You will understand how machine learning and deep learning work, how models are developed, and why these technologies matter for marketing.

Module 3

Generative AI in marketing

You will learn what generative AI is, how it works, how it is used in marketing, and how to design better prompts.

Module 4

Data for AI in marketing

You will learn what data means in the AI context, what makes a dataset useful, and how preprocessing supports AI-based marketing analysis.

Module 5

Collaborating with IT people

You will learn how marketers can collaborate with IT teams on AI projects, including data literacy, project readiness, and shared ethical responsibility.

Module 6

Creative work with AI (1)

You will explore creativity, idea generation, and practical human–AI collaboration in creative marketing work.

Module 7

Creative work with AI (2)

You will examine what research says about AI and creativity, including augmentation, replacement, paradoxes, and changing human roles.

Module 8

Building critical skills for the AI age

You will learn what critical thinking is, which cognitive skills support it, and how to question AI through prompts, data, and professional judgment.

Module 9

Critical thinking when using AI in marketing

You will learn where AI can mislead marketers, including analytical pitfalls, weak reasoning, ethical risks, and decision-making errors.

Module 10

Creating and testing synthetic personas with AI

You will create, enrich, and test synthetic personas based on customer data and evaluate their usefulness for marketing thinking.

Module 11

Critical evaluation of synthetic personas

You will learn how to detect hallucinations, check grounding, recognize AI sycophancy, and turn AI into a critical reviewer.

Module 12

Competencies to work with AI in marketing

You will explore AI marketing competencies, assess your own level, and create a personal development plan.

Module 13

Security

You will learn how AI changes digital threats, including phishing, deepfakes, data leaks, prompt injection, and password security.

Module 14

Sales and marketing synergy

You will learn how AI supports the sales funnel, CRM systems, lead management, conversion analysis, and marketing–sales alignment.

Additional module 15

Building AI agents with Claude Code

You will build reusable Claude Code skills and subagents, organize them with progressive disclosure, and test them against a baseline.

Requirements

To start this course, you need intermediate knowledge of marketing, equivalent to the first year of a master’s program.

How to earn a certificate?

To complete the course, study all required materials and pass the final test. Each module takes approximately 45 minutes and includes practical exercises, case-based activities, and reflection questions.

Short tests at the end of each module help you check your understanding. They are intended for self-assessment only, are not graded, and do not affect your final result.

The final test consists of 30 questions. To pass the course and receive a certificate, you need to answer at least 75% of the questions correctly. After you achieve the required result, the certificate will be available to download from the Results section.

Course team

This course is managed by Piotr Gaczek and Grzegorz Leszczyński from Poznań University of Economics and Business (PUEB). Its content was provided by researchers and practitioners from Austria, Croatia, France, Italy, Poland, and Spain:

• Alessandra Cioli – PhD Student at Università Politecnica delle Marche. Her main research interests focus on digital transformation, particularly generative AI adoption in organizations and human–AI collaboration. She is also a member of the Artificial Intelligence for Management Observatory at the Department of Management.
• Krzysztof Durczak – Assistant Professor at PUEB, Department of Sociology and Business Ethics. His main research interests focus on organizational anthropology, legal professions, regulation, and digital technologies, including the intersections between these fields. He is a board member of the Code for Poznań Association and one of the local AI experts at PUEB.
• Piotr Gaczek – Assistant Professor at PUEB, Human-Digital Nexus Research Center. His main research interests focus on decision science, artificial intelligence, and organizational behavior. He has led research projects, participated in national and international research consortia, and has extensive experience in designing and conducting research in collaboration with industry partners.
• Jesús García de Madariaga – Full Professor of Marketing at Complutense University, Head of the University Research Team “Markco2,” and Visiting Research Fellow at California Polytechnic University. His research interests include customer value management, neuromarketing, human–AI collaboration, and corporate social responsibility. He also serves on the Board of Directors of Insights + Analytics España.
• Natalia Gluza – Assistant Professor at PUEB. Her research interests focus on artificial intelligence in marketing and education, consumer behavior, persuasive communication, and psychological aspects of consumer decision-making. She is a member of the Wielkopolska Region Council on Artificial Intelligence and the Polish Scientific Marketing Association, and one of the AI experts at PUEB.
• Alicja Koperska – Assistant Professor at PUEB. Her main research interests focus on neurodiversity at work, the use of generative AI as assistive technology by employees with ADHD, and the motivational and well-being consequences of such use, grounded in work and organizational psychology and management. She combines quantitative and qualitative methods, including organizational ethnography. She also works as a consultant on the evaluation of social innovations for inclusion-oriented social services.
• Piotr Kwiatek – FH-Professor, Deputy Head, and Pedagogical Coordinator at the Global Business Department at the University of Applied Sciences Upper Austria. He is Vice President of the Global Sales Science Institute and a member of the Industrial Marketing and Purchasing Group (IMP). His research focuses on business customer relationship management, sales interactions, and digitally transformed relationships.
• Grzegorz Leszczyński – Full Professor at PUEB and Head of the Human-Digital Nexus Research Center. His main research interests focus on human–AI collaboration, B2B relationships, and value co-creation. He is a member of the Industrial Marketing and Purchasing Group (IMP) and the Wielkopolska Region Council on Artificial Intelligence.
• Maciej Ławrynowicz – Associate Professor at PUEB, Department of Labour and Social Policy, and a member of the Human-Digital Nexus Research Center. His research interests include human–AI collaboration, organizational identity, AI competencies in marketing and HRM, remote work, and digital nomadism. He is a member of the Academy of Management.
• Amira Mouakher – Associate Professor at UMR Espace-Dev, University of Perpignan Via Domitia, France. Her research focuses on artificial intelligence, explainable AI, large language models, and generative AI, with applications in marketing, human–AI collaboration, smart environments, and precision agriculture. She also works on knowledge graphs and data-driven approaches to knowledge discovery and representation.
• Anna Proch – Founder, investor, and builder at the intersection of AI, XR, and deep tech.
• Anna Rogala – Assistant Professor at PUEB. Her main research interests focus on how digitalization reshapes food markets from both consumer and firm perspectives, with particular emphasis on sustainable marketing and consumption enabled by communication technologies, as well as the design of behavioral interventions that foster sustainability transitions and enhance well-being. She is a board member of the Polish Scientific Marketing Association and a member of EMAC and EBES.
• Dubravka Sinčić – Full Professor of Marketing at the University of Zagreb Faculty of Economics & Business. She is Head of the English-taught Bachelor Degree in Business program and Head of the English-taught Master Degree in Business (Marketing) program. Her interests include B2B marketing, sustainability marketing, resilience and marketing flexibility, employer branding, and AI in marketing. She has extensive consultancy experience, particularly as a moderator and facilitator of organizational processes in companies. She is a member of the Industrial Marketing and Purchasing Group (IMP) and the Croatian Marketing Association CROMAR.