Authorship disclosure and consumer perception of AI-generated graphic design

Ekart, Barbara (author), Ahtik, Jure (author)

The increasing integration of artificial intelligence (AI) into graphic design and advertising has raised pressing questions about the role of authorship, trust and aesthetic judgement. This study examines how consumers perceive AI-generated versus human-created advertising visuals in the context of jewellery advertising. Two online surveys (n = 127) were conducted to compare participants' preferences under the conditions of disclosed and undisclosed authorship. The results show that while AI-generated visuals were sometimes rated favourably when authorship was hidden, human-created content was clearly preferred overall – especially when authorship was disclosed. A gender analysis revealed that female participants were especially sensitive to authorship cues, favouring human-created visuals. Logistic regression further confirmed that authorship disclosure, gender and design features such as human presence and serif typography were significant predictors of preference. Qualitative responses suggest that while AI visuals are technically competent, they lack emotional authenticity and narrative resonance. These findings emphasise the importance of transparency, emotional design and collaboration between humans and AI in visual communication. The study contributes to ongoing debates about machine creativity, aesthetic value and ethical disclosure, and offers practical implications for designers and marketers using AI in emotionally-driven contexts.

• Language: English
• Keywords: artificial intelligence, graphic design, photography, consumer perception, advertising, authorship disclosure
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: NTF - Faculty of Natural Sciences and Engineering
• Publication status: Published
• Publication version: Version of Record
• Year: 2026
• Number of pages: Str. 23-32
• Numbering: Vol. 17, no. 2
• PID: 20.500.12556/RUL-183303
• UDC: 655
• ISSN on article: 2217-379X
• COBISS.SI-ID: 281115651
• Publication date in RUL: 12.06.2026

Record is a part of a journal

• Title: Journal of graphic engineering and design : JGED
• Shortened title: JGED, J. Graph. Eng. Des.
• Publisher: University of Novi Sad, Faculty of Technical Sciences, Department of Graphic Engineering and Design
• ISSN: 2217-379X
• COBISS.SI-ID: 257662727

Licences

• License: CC BY-SA 4.0, Creative Commons Attribution-ShareAlike 4.0 International
• Link: http://creativecommons.org/licenses/by-sa/4.0/
• Description: This Creative Commons license is very similar to the regular Attribution license, but requires the release of all derivative works under this same license.

Secondary language

• Language: Slovenian
• Keywords: umetna inteligenca, grafično oblikovanje, fotografija, percepcija potrošnikov, oglaševanje, razkritje avtorstva

Projects

• Funder: ARIS - Slovenian Research and Innovation Agency
• Project number: P2-0450-2024
• Name: Inovativna grafična tehnologija