When Artificial Intelligence (AI) Becomes Part of the Message: AI Disclosure and the Signaling Value of Social Media Influencer Reputation

Abstract

The increasing use of AI in influencer marketing is changing how consumers interpret established credibility cues. This study examines whether AI disclosure alters the signaling value of social media influencer reputation (SMIR) in shaping consumer responses towards online private label brands (OPLBs). Drawing on signaling theory, the study conceptualizes SMIR as a source-based credibility signal and consumer trust as the receiver-side mechanism through which this signal influences subsequent behavioral intentions. A 2 × 2 between-subjects experiment was conducted with 252 social media users, who were randomly exposed to a simulated Instagram post featuring either high or low SMIR and either disclosed or undisclosed AI involvement. The findings show that SMIR significantly enhances consumer trust in OPLBs, and that consumer trust, in turn, positively influences both purchase and recommendation intentions. Consumer trust also significantly mediates the relationship between SMIR and both behavioral intentions. Importantly, the significant interaction between SMIR and AI disclosure demonstrates that AI disclosure weakens the positive signaling effect of high SMIR on consumer trust in OPLBs. The study extends signaling theory by showing that AI disclosure changes the interpretive context in which established human-based credibility signals are evaluated. In practice, the findings suggest that OPLBs should carefully manage AI disclosure in influencer campaigns to preserve the credibility of influencers' reputations and encourage favorable consumer responses.