Gen Z Consumers’ Attitudes Toward AI Influencers vs. Human Influencers: Exploring Authenticity, Trustworthiness, and Parasocial Interaction

Tassawut Aungsajjapong; Supriya Thukral

Authors

Tassawut Aungsajjapong Independent Researcher, MSc Digital Marketing & OmniChannel Strategy Student, MBS School of Business, France
Supriya Thukral Independent Researcher, MSc Digital Marketing & OmniChannel Strategy Student, MBS School of Business, France

Keywords:

AI, Artificial Intelligence, Influencers, Gen Z

Abstract

This study examines how Generation Z (Gen Z) evaluates AI-generated (“virtual”) influencers relative to human influencers across three established constructs: perceived authenticity, trustworthiness, and parasocial interaction (PSI). Using a cross-sectional, within-subject survey of Gen Z social media users (N = 100; ages 18–27) recruited via purposive sampling, respondents viewed examples of profiles and posts made by human and AI influencers and completed validated multi-item scales (α ≈ 0.90–0.96).

Paired-samples t-tests revealed significantly higher observed ratings for human influencers than AI influencers on authenticity, trustworthiness, and PSI (all ps < .001). ANCOVA analyses confirmed these differences remained significant after controlling for prior familiarity with each influencer type (all ps < .001, η² = 0.13–0.15), indicating the human-AI gap reflects genuine perceptual differences rather than exposure effects. Within the AI subset, Pearson correlations indicated strong positive associations between authenticity and trust (r = 0.741) and between PSI and trust (r = 0.669), with authenticity and PSI also moderately correlated (r = 0.595). Multiple regression identified authenticity (β = 0.531, p < .001) and PSI (β = 0.353, p < .001) as concurrent predictors of trust in AI influencers (R² = 0.63), suggesting complementary credibility and relational pathways.

Interpretation is bounded by non-probability sampling, cross-sectional self-report data, potential common-method bias, exposure asymmetries favoring human influencers, and the absence of factor-invariance tests or experimental manipulations (e.g., disclosure frames, degree of human-likeness, product category).

The findings contribute a comparative, construct-valid portrait of Gen Z responses to synthetic sources and clarify conditions under which AI influencers may earn trust. Managerially, results imply that virtual influencers are best positioned as complements to, rather than substitutes for, human creators when trust and relational depth are central objectives.

References

Abidin, C. (2016). “Aren’t These Just Young, Rich Women Doing Vain Things Online?”: Influencer Selfies as Subversive Frivolity. Social Media + Society, 2(2). https://doi.org/10.1177/2056305116641342

Artificial Intelligence+. (2025). Gen Z's growing distrust of AI. Retrieved from https://www.aiplusinfo.com/gen-zs-growing-distrust-of-ai/

Audrezet, A., de Kerviler, G., & Moulard, J. G. (2020). Authenticity under threat: When social media influencers need to go beyond self-presentation. Journal of Business Research, 117, 557–569. https://doi.org/10.1016/j.jbusres.2018.07.008

Baghel, D. (2023). The role of influencer authenticity and brand trust in shaping consumer behavior: Strategies to engage Generation Z. ShodhKosh: Journal of Visual and Performing Arts, 4(1). https://doi.org/10.29121/shodhkosh.v4.i1.2023.3327

Cascio Rizzo, G. L., Berger, J., & Villarroel, F. (2023). What drives virtual influencer’s impact? arXiv. https://doi.org/10.48550/arXiv.2301.09874

Carrasco, J.-A., & Lucas, K. (2016). Measuring attitudes: quantitative and qualitative methods. Transportation Research Procedia, 11, 165–171. https://doi.org/10.1016/j.trpro.2015.12.014

Center for News, Technology & Innovation. (2025). Synthetic media & deepfakes. Retrieved from https://cnti.org/issue-primers/synthetic-media-deepfakes/

Chen, Y., Xue, T., Tuomi, A., & Wang, Z. (2022). Hotel robots: An exploratory study of Generation Z customers in China. Tourism Review, 77(5), 1262–1275. https://doi.org/10.1108/TR-02-2022-0095

Committee of Advertising Practice & Advertising Standards Authority. (2023). Influencers’ guide to making clear that ads are ads (3rd ed.). ASA & CAP. https://www.asa.org.uk/resource/influencers-guide.html

De Veirman, M., Cauberghe, V., & Hudders, L. (2017). Marketing through Instagram influencers: the impact of number of followers and product divergence on brand attitude. International Journal of Advertising, 36(5), 798–828.

https://doi.org/10.1080/02650487.2017.1348035

Djafarova, E., & Trofimenko, O. (2019). ‘Instafamous’–credibility and self-presentation of micro-celebrities on social media. Information, Communication & Society, 22(10), 1432–1446. https://doi.org/10.1080/1369118X.2018.1438491

European Commission. (2023). Influencer Legal Hub: Resources on influencer transparency and enforcement actions. European Commission. https://commission.europa.eu/live-work-travel-eu/consumer-rights-and-complaints/influencer-legal-hub_en

Federal Trade Commission. (2023). FTC’s Endorsement Guides: What People Are Asking. Federal Trade Commission. https://www.ftc.gov/business-guidance/advertising-marketing/endorsements-influencers-reviews

Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th ed.). SAGE Publications.

Fu, M., Fraser, B., & Arcodia, C. (2024). Digital natives on the rise: A systematic literature review on Generation Z’s engagement with RAISA technologies in hospitality services. International Journal of Hospitality Management, 122, Article 103885. https://doi.org/10.1016/j.ijhm.2024.103885

Glikson, E., & Woolley, A. W. (2020). Human trust in artificial intelligence: Review of empirical research. Academy of Management Annals, 14(2), 627–660. https://doi.org/10.5465/annals.2018.0057

Gulan, M., Feng, Y., Mvondo, G. F. N., & Niu, B. (2025). How Do Virtual Influencers Affect Consumer Brand Evangelism in the Metaverse? The Effects of Virtual Influencers’ Marketing Efforts, Perceived Coolness, and Anthropomorphism. Journal of Theoretical and Applied Electronic Commerce Research, 20(1), 36. https://doi.org/10.3390/jtaer20010036

Horton, D., & Wohl, R. R. (1956). Mass communication and para-social interaction: Observations on intimacy at a distance. Psychiatry, 19(3), 215–229. https://doi.org/10.1080/00332747.1956.11023049

Jayatissa Dimani. (2023). Generation Z – A new lifeline: A systematic literature review. Sri Lanka Journal of Social Sciences and Humanities, 3(2), 179–186. https://doi.org/10.4038/sljssh.v3i2.110

Jin, S. A. A., & Phua, J. (2014). Following Celebrities’ Tweets About Brands: The Impact of Twitter-Based Electronic Word-of-Mouth on Consumers’ Source Credibility Perception, Buying Intention, and Social Identification With Celebrities. Journal of Advertising, 43(2), 181–195. https://doi.org/10.1080/00913367.2013.827606

Joshi, Y., Lim, W.M., Jagani, Kumar, S. (2025). Social media influencer marketing: foundations, trends, and ways forward. Electron Commer Res 25, 1199–1253. https://doi.org/10.1007/s10660-023-09719-z

Ju, N., Kim, T. & Im, H. (2024). Fake human but real influencer: the interplay of authenticity and humanlikeness in Virtual Influencer communication?. Fash Text 11, 16. https://doi.org/10.1186/s40691-024-00380-0

Karunasingha, A., & Abeysekera, N. (2022). The mediating effect of trust on consumer behavior in social media marketing environments. South Asian Journal of Marketing, 3(2), 135–149. https://doi.org/10.1108/SAJM-10-2021-0126

Lankton, N. K., McKnight, D. H., & Tripp, J. (2015). Technology, humanness, and trust: Rethinking trust in technology. Journal of the Association for Information Systems, 16(10), 880–918. https://doi.org/10.17705/1jais.00411

Lao, Y., Hirvonen, N., & Larsson, S. (2025). Everyday encounters with deepfakes: Young people's media and information literacy practices with AI-generated media. Journal of Documentation, 81(7), 216–235. https://doi.org/10.1108/JD-01-2025-0007

Lou, C., & Kim, H. K. (2019). Fancying the new rich and famous? Explicating the roles of influencer content, credibility, and parental mediation in adolescents’ parasocial relationship, materialism, and purchase intentions. Frontiers in Psychology, 10, 2567. https://doi.org/10.3389/fpsyg.2019.02567

Marwick, A. E. (2013). Status update: Celebrity, publicity, and branding in the social media age. Yale University Press.

Mori, M. (1970). The uncanny valley. Energy, 7(4), 33–35. (Translated from Japanese).

Morning Consult. (2025). Gen Z and AI: Why Brands Must Tread Carefully. Retrieved from https://pro.morningconsult.com/analysis/genz-ai-trust-privacy-research

Mrad, M., Ramadan, Z. and Nasr, L.I. (2022), "Computer-generated influencers: the rise of digital personalities", Marketing Intelligence & Planning, Vol. 40 No. 5, pp. 589-603. https://doi.org/10.1108/MIP-12-2021-0423

Muniz, F., Stewart, K., & Magalhães, L. (2023). Are they humans or are they robots? The effect of virtual influencer disclosure on brand trust. Journal of Consumer Behaviour, 22(4), 567–580. https://doi.org/10.1002/cb.2271

Naffi, N. (2025, October 1). Deepfakes and the crisis of knowing. UNESCO. Retrieved from https://www.unesco.org/en/articles/deepfakes-and-crisis-knowing

Neufeld-Wall, Maya Elizabeth, "Being Real: Gen-Z, Self-Presentation, and Authenticity on Social Media" (2023). Communication Honors Theses. 26. ttps://digitalcommons.trinity.edu/comm_honors/26

Ohanian, R. (1990). Construction and validation of a scale to measure celebrity endorsers’ perceived expertise, trustworthiness, and attractiveness. Journal of Advertising, 19(3), 39–52. https://doi.org/10.1080/00913367.1990.10673191

Omeish, F., Shaheen, A., Alharthi, S., & Alfaiza, A. (2025). Between human and AI influencers: Parasocial relationships, credibility, and social capital formation in a collectivist market: A study of TikTok users in the Middle East. Discover Sustainability, 6, Article 116. https://doi.org/10.1007/s43621-025-00891-w

Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias and how to control it. Annual Review of Psychology, 63, 539–569.

Powell, L., Rebman, C., & Wimmer, H. (2025). Exploration of AI synthetic media and deepfake: Understanding the technologies, detection software, legislation, initiatives, and curriculum. Issues in Information Systems, 26(4), 183–194. https://doi.org/10.48009/4_iis_2025_116

Rubin, A. M., Perse, E. M., & Powell, R. A. (1985). Loneliness, parasocial interaction, and local television news viewing. Human Communication Research, 12(2), 155–180. https://doi.org/10.1111/j.1468-2958.1985.tb00071.x

Sokolova, K., & Kefi, H. (2020). Instagram and YouTube bloggers promote it, why should I buy? How credibility and parasocial interaction influence purchase intentions. Journal of Retailing and Consumer Services, 53, 101742. https://doi.org/10.1016/j.jretconser.2019.01.011

Subramanian, K. R. (2015). Advertising clutter and consumer apathy. GE–International Journal of Management Research, 3(6), 309–322.

Teixeira, T. S. (2014). The rising cost of consumer attention: Why you should care, and what you can do about it (HBS Working Paper No. 14-055). Harvard Business School.

Tirocchi, S. (2024). Generation Z, values, and media: From influencers to BeReal, between visibility and authenticity. Frontiers in Sociology, 8. https://doi.org/10.3389/fsoc.2023.1304093

Tsumura T, Yamada S (2023) Influence of agent’s self-disclosure on human empathy. PLoS ONE 18(5): e0283955. https://doi.org/10.1371/journal.pone.0283955

Turner, A. (2015). Generation Z: Technology and social interest. The Journal of Individual Psychology, 71(2), 103–113. https://doi.org/10.1353/jip.2015.0021

Usercentrics. (2025). Privacy as personal branding: Gen Z's digital citizenship. Retrieved from https://usercentrics.com/magazine/articles/privacy-as-personal-brand-genzs-digital-citizenship/

van Driel, L., & Dumitrica, D. (2020). Selling brands while staying “authentic”: The professionalization of Instagram influencers. Convergence: The International Journal of Research into New Media Technologies, 27(1), 66–84.

CL Foundation. (2025). Online identity for Gen Z: Who do we think we are online? Retrieved from https://www.3cl.org/who-do-we-think-we-are-online-rethinking-digital-identity-for-gen-z/