Umut Demiriz
"My research focuses on data-driven topics such as quality assurance and processing large data sets (cleaning, transformation, visualisation). I write scientific publications and grant applications and lead data-driven teaching units and projects, especially by developing practical, research-based teaching concepts and materials."

Manuel Holler, PhD
“My research focuses on the valuable applications of emerging technologies, such as artificial intelligence, the industrial metaverse and smart products. My aim is to translate these insights into sustainable products and services.”

Gioia Volkmar, PhD
“My research focuses on psychological decision-making processes, user acceptance of AI systems, and how companies can use artificial intelligence in marketing in a responsible and effective way. I am particularly interested in the connection between psychology, technological innovation, and the regulatory and ethical frameworks surrounding AI.”

Artificial intelligence is fundamentally changing marketing—technologically, strategically, organizationally, and culturally. We examine how companies integrate AI into marketing to gain competitive advantages. The focus is on analyzing structures, assessing AI maturity, and developing scalable, customer-centric roadmaps—scientifically sound and practical.

Specific questions:

• What organizational, cultural, and structural prerequisites promote successful AI transformation in marketing?
• What strategies enable sustainable, value-oriented integration of AI along the customer journey?
   

Generative AI in marketing

We explore how artificial intelligence can be used operationally and creatively in marketing, media, and communication. It automates recurring tasks, enables data-based personalization, and creates new possibilities with generative AI for texts, images, videos, and interactive formats. The opportunities, limitations, and implications of these technologies are at the heart of our analysis.

Specific questions:

• How is AI changing the development of content in marketing, PR, and media?
• What role does AI play in qualitative and/or quantitative market research?
• How does the use of AI influence the emotional experience of brands?
   

Legal orientation: Designing AI in marketing to be legally compliant

Artificial intelligence in marketing must not only be effective, but also legally compliant and transparent. Companies face the challenge of implementing new legal requirements—such as those imposed by the EU AI Act—while at the same time reconciling data protection, copyright, and brand management in the digital age.

Specific questions:

• What new obligations and risks does the EU AI Act create for marketing and communication?
• How can companies reconcile data protection, copyright, and brand management in the AI age?
   

Ethical responsibility and governance: guidelines for fair AI use

In addition to legal aspects, the ethical dimension is also crucial: the use of AI in marketing must not lead to discrimination, lack of transparency, or manipulation. To counteract this, clear ethical guidelines and internal structures are needed to promote responsible use. This is where governance comes in—with values, processes, and controls for fair AI use.

Specific questions:

• What ethical guidelines are needed for the use of generative AI?
• How can companies develop governance structures that systematically anchor responsible AI use?
   

Acceptance and user perspectives

Consumer acceptance of AI is crucial to its success. We examine psychological, sociocultural, and communicative factors that shape perception, trust, and willingness to use AI. Using user research methods, we analyze expectations and barriers to acceptance. This results in AI applications that are not only technically compatible but also socially acceptable.

Specific questions:

• What role do transparency, control, and explainability play in trust in AI systems?
• To what extent do users want explanations for AI decisions – and how should these be presented?
• How do people react emotionally to AI-based communication – e.g., through chatbots or avatars?
• What requirements arise for the design of empathetic, respectful, and socially compatible AI systems?
   

AI and social issues

The use of AI raises key social questions—for example, about fairness, transparency, algorithmic discrimination, and the impact on work, consumer behavior, and social structures. 
We explore these interactions from an interdisciplinary perspective and develop approaches for the responsible, socially acceptable use of AI.

Specific questions:

• To what extent do AI systems change power relations in communication, work, consumption, or education?
• Which social norms and values should be embedded in the development of AI?
   

Our methods: empirically sound, applied in a practical manner