Familiarity with a brand makes customers more sensitive to AI - generated marketing content: insights from Destination Marketing and Framing Theory
Existing literature has highlighted the lower performance of artificial intelligence (AI)-generated marketing content in conveying affective messaging. Affective messaging is especially important in tourism and destination marketing. While recent literature highlights increasing human involvement in content creation potential solution, we argue that this approach aligns with framing theory, as both seek to enhance content presentation to effectively influence consumer information processing and decision-making. Framing theory emphasises consumers’ subject familiarity as a critical factor; however, this dimension has not been considered a boundary condition in current research on AI-driven marketing content creation. Using an online quasi-experiment with one destination marketing brand, we compared three content sources: human-created content, AI-generated content, and AI-generated content with increased human involvement. Based on a sample of university staff and students, the results show that audiences with low brand familiarity were less sensitive to AI-generated marketing content than familiar audiences. Meanwhile, increasing human involvement in content creation diminished negative attitudes toward AI use. These results highlight consumers’ subject familiarity as a significant factor affecting perceptions of AI-generated marketing content. The findings contribute to the existing literature on factors shaping perceptions of AI-generated marketing content, while also advancing framing theory and research on human involvement in marketing communications.
Authors
- Sasu Tuominen (ORCID: https://orcid.org/0000-0001-5908-573X)
- Netta Konttinen
- Jani Holopainen
- Juho Pesonen
Institutions
- University of Eastern Finland (FI)
- Finland University (FI)
Publication Details
- Journal
- Current Issues in Tourism
- Published
- 2026-09-05
- DOI
- https://doi.org/10.1080/13683500.2026.2728074
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00