Digital Influence, Creator Economies and Communication Ethics: A Conceptual Model of Persuasion, Disclosure and Accountability in AI-Augmented Social Media Marketing

Authors

  • Ogah Sunday Ogbo Veristzon Global Research Lab Author
  • Nwogboji Emmanuel Usulor Veristzon Global Research Lab Author

DOI:

https://doi.org/10.68854/xfjsw056

Keywords:

influencer marketing, creator economy, persuasion, disclosure, communication ethics, virtual influencers, artificial intelligence, advertising regulation, consumer protection, Nigeria

Abstract

The creator economy has become a primary channel of commercial and political persuasion. Artificial intelligence is now changing it from two directions. Creators use generative tools to produce content at a scale and speed no human team could match, while brands deploy synthetic influencers who never existed and AI systems that can match persuasive messages to individual psychological profiles. This conceptual, non-empirical paper develops a model of communication ethics for AI-augmented influence. It draws on persuasion theory and advertising ethics, on the influencer-marketing and creator-economy literatures, and on peer-reviewed research published between 2023 and 2026 on virtual influencers, AI-generated advertising and algorithmic and psychological targeting. Every source was checked against its Crossref record and screened for retractions and corrections. The paper identifies three requirements that persuasion must meet to be ethically legitimate. The audience must be able to recognise it as persuasion, must be able to identify who is persuading, and must keep the capacity to evaluate the claim. AI augmentation threatens each requirement. Generated content blurs the boundary between commercial and organic material, synthetic personas obscure the persuader, and psychological targeting and persuasive generation at scale weaken evaluation. From this recognition–identification–evaluation framework, the paper derives six propositions on the conditions under which AI-augmented influence remains ethically legitimate and legally compliant. It argues that disclosure rules designed for human influencers are necessary but inadequate, because they address recognition while leaving identification and evaluation largely unprotected. Using Nigeria's fast-growing influencer market and its advertising, consumer-protection and data-protection regimes as the anchoring case, the paper proposes a layered framework of obligations for regulators, platforms, brands and agencies, and creators.

References

Ademiluyi, D. D., Sodiya, O. M., Animasahun, M. O., Oyewunmi, B. T., Ogunniyi, A. E., Salaudeen, O. A., Olubiyi, E. D., Ojo-Adalumo, A. R., Ajayi, P. M., Egbeniyi, T. O., & Oyeneye, O. A. (2026). Digital diets and adolescent nutrition in Nigeria and the influence of social media on emerging noncommunicable disease risks. Discover Public Health, 23(1), 1533. https://doi.org/10.1186/s12982-026-02687-3

Altay, S., & Gilardi, F. (2024). People are skeptical of headlines labeled as AI-generated, even if true or human-made, because they assume full AI automation. PNAS Nexus, 3(10), pgae403. https://doi.org/10.1093/pnasnexus/pgae403

Cao, Z., & Belo, R. (2024). Effects of explicit sponsorship disclosure on user engagement in social media influencer marketing. MIS Quarterly, 48(1), 375–392. https://doi.org/10.25300/MISQ/2023/17944

Chen, J., & Haley, E. (2026). Disclosure in AI-generated advertising: How source credibility affects consumer purchase intention. Journal of Current Issues & Research in Advertising. Advance online publication. https://doi.org/10.1080/10641734.2026.2711967

Effoduh, J. O. (2025). Digital colonialism and the role of local intermediaries: Examining Big Tech’s impact on data sovereignty and human rights in Africa. Business and Human Rights Journal, 10(2–3), 301–317. https://doi.org/10.1017/bhj.2025.10021

Hackenburg, K., & Margetts, H. (2024). Evaluating the persuasive influence of political microtargeting with large language models. Proceedings of the National Academy of Sciences, 121(24), e2403116121. https://doi.org/10.1073/pnas.2403116121

Huang, H., Fu, R., & Ghose, A. (2026). Generative AI, platform stances, and content creator behavior. Information Systems Research. Advance online publication. https://doi.org/10.1287/isre.2025.2155

Ibrahim, A. A., & Ekdale, B. (2026). Political campaign responses to information disorder: A case study of the 2023 Nigerian presidential elections. The International Journal of Press/Politics, 31(3), 595–615. https://doi.org/10.1177/19401612251324985

Kerckaert, J. (2023). #NoFilter? The application of the Unfair Commercial Practices Directive and the role of soft law in the context of influencer marketing. European Review of Private Law, 31(2/3), 519–556. https://doi.org/10.54648/erpl2023017

Khalfallah, D., & Keller, V. (2025). Authenticity, ethics, and transparency in virtual influencer marketing: A cross-cultural analysis of consumer trust and engagement: A systematic literature review. Acta Psychologica, 260, 105573. https://doi.org/10.1016/j.actpsy.2025.105573

Kim, E., Shoenberger, H., Kim, D., Thorson, E., & E, Z. (2025). Novelty vs. trust in virtual influencers: Exploring the effectiveness of human-like virtual influencers and anime-like virtual influencers. International Journal of Advertising, 44(3), 453– 483. https://doi.org/10.1080/02650487.2024.2386916

Klenk, M. (2024). Ethics of generative AI and manipulation: A design-oriented research agenda. Ethics and Information Technology, 26(1), 9. https://doi.org/10.1007/s10676-024-09745-x

Liu, X., & Zhao, H. (2025). A meta-analysis of the effects of sponsorship disclosure in influencer marketing. Marketing Letters, 36(3), 519–532. https://doi.org/10.1007/s11002-024-09757-z

Looi, J., Kim, E., & E, Z. (2025). Sponsorship disclosure in virtual influencer marketing: Assessing users’ sentiment and engagement toward virtual influencer endorsements. Journal of Advertising Research, 65(3), 321–343. https://doi.org/10.1080/00218499.2025.2464300

Luo, J., & Li, C. (2026). The authenticity penalty: Why AI-enhanced performance diminishes relational value in the creator economy. Electronic Markets, 36(1), 74. https://doi.org/10.1007/s12525-026-00930-y

Matz, S. C., Teeny, J. D., Vaid, S. S., Peters, H., Harari, G. M., & Cerf, M. (2024). The potential of generative AI for personalized persuasion at scale. Scientific Reports, 14(1), 4692. https://doi.org/10.1038/s41598-024-53755-0

Nair, A. J., & Manohar, S. (2026). AI influencers and consumer well-being: The roles of parasocial interaction, trust and authenticity. Journal of Consumer Behaviour. Advance online publication. https://doi.org/10.1002/cb.70242

Owens-Ibie, N., Nnabuihe, O. E., & Aondover, E. M. (2026). New minority marginalisations and the social media ecosystem in Nigeria. African Identities. Advance online publication. https://doi.org/10.1080/14725843.2026.2672423

Oyeniyi, B. A. (2026). The afterlives of propaganda: Media archeology, everyday labor, and postcolonial statecraft in Nigeria’s 2023 election. African Identities. Advance online publication. https://doi.org/10.1080/14725843.2026.2724899

Pigac, T., & Huang, A. (2026). How consumers negotiate trust and responsibility towards AI-generated virtual influencers. Journal of Consumer Behaviour. Advance online publication. https://doi.org/10.1002/cb.70266

Rangaswamy, P., & Sivakumar, K. (2026). Artificial intelligence and the creator economy: Conceptualization and research propositions. Customer Needs and Solutions, 13(1), 7. https://doi.org/10.1007/s40547-026-00167-y

Schilke, O., & Reimann, M. (2025). The transparency dilemma: How AI disclosure erodes trust. Organizational Behavior and Human Decision Processes, 188, 104405. https://doi.org/10.1016/j.obhdp.2025.104405

Simchon, A., Edwards, M., & Lewandowsky, S. (2024). The persuasive effects of political microtargeting in the age of generative artificial intelligence. PNAS Nexus, 3(2), pgae035. https://doi.org/10.1093/pnasnexus/pgae035

Tang, J., Yu, X., Wikström, P., & Pappalardo, K. (2026). Behind the “AI slop”: Exploring the AI-generated viral short video production in China. AI & Society. Advance online publication. https://doi.org/10.1007/s00146-026-03254-9

Toff, B., & Simon, F. M. (2025). “Or they could just not use it?”: The dilemma of AI disclosure for audience trust in news. The International Journal of Press/Politics, 30(4), 881–903. https://doi.org/10.1177/19401612241308697

Waltenrath, A. (2024). Consumers’ ambiguous perceptions of advertising disclosures in influencer marketing: Disentangling the effects on current and future social media engagement. Electronic Markets, 34(1), 8. https://doi.org/10.1007/s12525-023-00679-8

Weiss, P., Jungbluth, M., & Hogreve, J. (2026). AI advertising-to-service inference: When AI disclosure triggers inferences from ad production to process expectation. Journal of Advertising. Advance online publication. https://doi.org/10.1080/00913367.2026.2720926

Wilson, R. T., Roux, T., & Bright, L. F. (2026). Disclosing AI-generated advertising: Effects on attitudes, purchase intent, and social media engagement. International Journal of Advertising. Advance online publication. https://doi.org/10.1080/02650487.2026.2737583

Published

2026-10-27