Generative AI tools such as ChatGPT for texts, DALL·E for images or Sora for videos are rapidly reshaping how marketing content is produced. Brands increasingly rely on AI systems to create images, social-media posts, product descriptions, and advertising materials. While these tools offer efficiency and creative possibilities, they also raise an important question: 

How do consumers respond when they learn that an advertisement was created with AI?

Interest in this topic is rising among practitioners and academics alike, as regulators and digital platforms move toward mandatory transparency rules for AI-generated content (e.g., EU AI Act; “Made with AI” labels on major social-media platforms). As a result, marketers will increasingly need to disclose when AI has been used, making it crucial to understand how such disclosures shape consumer reactions.

Recent marketing campaigns show that the use of AI in advertising can provoke substantial public backlash, for example due to uncanny visuals or concerns about AI replacing human labor. Existing research consistently shows that AI-generated marketing content can trigger more negative responses when consumers perceive it as less authentic or less trustworthy. Across product categories and media formats, studies find a robust pattern: disclosing that advertising content was created by AI tends to lower consumer attitudes, intentions, and engagement – a phenomenon often referred to as the “AI-disclosure effect.”

This project aims to advance understanding of how consumers perceive and evaluate AI-generated marketing content when AI usage is disclosed. 

Specifically, it examines 

• how AI-disclosure messages can be designed most effectively
• which contextual and communication-design factors moderate the negative impact of AI disclosure
• how heterogeneity in consumer, brand, and situational characteristics shapes receptiveness or resistance to AI-disclosed content

In sum, this research addresses a central challenge for marketing practice: 
how to meaningfully comply with mandatory AI-disclosure requirements without sacrificing advertising effectiveness.

This project is a collaboration between the Northeastern University (NEU), Boston, Massachusetts (https://www.northeastern.edu/) and the Nuremberg Institute for Market Decisions (NIM).