How artificial intelligence recommendation tags shape advertising attitude

Artificial intelligence (AI) recommendation tags are increasingly common in newsfeed advertising but limited research has explored how the degree of information disclosure influences consumers' responses. We proposed a moderated mediation model grounded in self-congruity theory and conducted three experiments. The results showed that explicit AI recommendation tags enhanced consumers' perceived personalization, which, in turn, led to a more positive attitude toward the advertising. In addition, this effect depended on the fit of the recommendation tag and privacy concerns: When the fit was good, explicit versus implicit AI recommendation tags did not differ significantly in their effect on perceived personalization, whereas when privacy concerns were high, the positive effect of perceived personalization on advertising attitude became weaker. These findings highlight the importance of designing AI recommendation tags that balance personalization and privacy.