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Unreal influence: leveraging AI in influencer marketing

Sean Sands (Department of Marketing and Management, Swinburne University of Technology, Melbourne, Australia)
Colin L. Campbell (School of Business Administration, University of San Diego, San Diego, California, USA)
Kirk Plangger (King’s Business School, King’s College London, London, UK)
Carla Ferraro (Department of Management and Marketing, Swinburne University of Technology, Melbourne, Australia)

European Journal of Marketing

ISSN: 0309-0566

Article publication date: 18 February 2022

Issue publication date: 7 June 2022

2014

Abstract

Purpose

This paper aims to examine how consumers respond to social media influencers that are created through artificial intelligence (AI) and compares effects to traditional (human) influencers.

Design/methodology/approach

Across two empirical studies, the authors examine the efficacy of AI social media influencers. With Study 1, the authors establish baseline effects for AI influencers and investigate how social-psychological distance impacts consumer perceptions. The authors also investigate the role of an influencer’s agency – being autonomous or externally managed – to test the boundaries of the results and determine the interactive effects between influencer type and influencer agency. Study 2 acts as an extension and validation of Study 1, whereby the authors provide generalisability and overlay the role of need for uniqueness as a moderated mediator.

Findings

The authors show that there are similarities and differences in the ways in which consumers view AI and human influencers. Importantly, the authors find no difference in terms of intention to follow or personalisation. This suggests that consumers are equally open to follow an AI or human influencer, and they perceive the level of personalisation provided by either influencer type as similar. Furthermore, while an AI influencer is generally perceived as having lower source trust, they are more likely to evoke word-of-mouth intentions. In understanding these effects, the authors show that social distance mediates the relationship between influencer type and the outcomes the authors investigate. Results also show that AI influencers can have a greater effect on consumers who have a high need for uniqueness. Finally, the authors find that a lack of influencer agency has a detrimental effect.

Research limitations/implications

The studies investigate consumers’ general response to AI influencers within the context of Instagram, however, future research might examine consumers’ response to posts promoting specific products across a variety of category contexts and within different social media platforms.

Practical implications

The authors find that in some ways, an AI influencer can be as effective as a human influencer. Indeed, the authors suggest that there may be a spill-over effect from consumer experiences with other AI recommendation systems, meaning that consumers are open to AI influencer recommendations. However, the authors find consistent evidence that AI influencers are trusted less than traditional influencers, hence the authors caution brands from rushing to replace human influencers with their AI counterparts.

Originality/value

This paper offers novel insight into the increasingly prominent phenomenon of the AI influencer. Specifically, it takes initial steps towards developing understanding as to how consumers respond to AI influencers and contrast these effects with human influencers.

Keywords

Citation

Sands, S., Campbell, C.L., Plangger, K. and Ferraro, C. (2022), "Unreal influence: leveraging AI in influencer marketing", European Journal of Marketing, Vol. 56 No. 6, pp. 1721-1747. https://doi.org/10.1108/EJM-12-2019-0949

Publisher

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Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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