EconPapers    
Economics at your fingertips  
 

Artificial Intelligence and Influencer Marketing: Mapping the Field of Knowledge

Pilelienė Lina (), Bakanauskas Arvydas Petras () and Bendaravičienė Rita ()
Additional contact information
Pilelienė Lina: Prof. Vytautas Magnus University, K. Donelaičio str. 58, Kaunas, Lithuania
Bakanauskas Arvydas Petras: Prof. Vytautas Magnus University, K. Donelaičio str. 58, Kaunas, Lithuania
Bendaravičienė Rita: Prof. Vytautas Magnus University, K. Donelaičio str. 58, Kaunas, Lithuania

Management Theory and Studies for Rural Business and Infrastructure Development, 2025, vol. 47, issue 3, 370-388

Abstract: Purpose: This review aims to map the current body of knowledge on AI in influencer marketing by outlining the theoretical and methodological backgrounds and contexts and identifying key areas for further exploration in this field. Method: A systematic literature review of 188 articles published on the Scopus database on AI and influencer marketing was conducted to identify recent research trends in the field. The review was performed based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol guidelines and the TCM organizing framework encompassing theory, context, and methodology analyses. Findings: The domain of AI in influencer marketing was found to be in its infancy stage; however, the number of articles published on AI and influencer marketing has been exponentially growing since 2017. The main term used by the authors to name the influencers generated using AI was found to be ‘virtual influencer’ and is constantly gaining its position. The most followed theories were found to be the Source Credibility Theory, Mind Perception Theory, Parasocial Interaction Theory, Construal Level Theory, and Trust Transfer Theory. Five main research contexts were identified: sender-focused, source-focused, message-focused, receiver-focused, and context-focused. The research methods used in the field of AI in influencer marketing have been identified as three principal approaches: quantitative, experimental, and qualitative. Contributions/implications: This paper is among the first review papers mapping the innovative and complex domain of AI and its intersections with influencer marketing. By mapping the existing research scope, it identifies the main theoretical, methodological, and contextual backgrounds of the domain.

Keywords: AI influencer; Artificial intelligence influencer; Computer-generated influencer; CGI; Digital influencer; Influencer marketing; Virtual influencer (search for similar items in EconPapers)
JEL-codes: M31 M37 O32 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.15544/mts.2025.30 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:vrs:mtrbid:v:47:y:2025:i:3:p:370-388:n:1005

DOI: 10.15544/mts.2025.30

Access Statistics for this article

Management Theory and Studies for Rural Business and Infrastructure Development is currently edited by Rasa Pakeltienė

More articles in Management Theory and Studies for Rural Business and Infrastructure Development from Sciendo
Bibliographic data for series maintained by Peter Golla ().

 
Page updated 2025-10-21
Handle: RePEc:vrs:mtrbid:v:47:y:2025:i:3:p:370-388:n:1005