Research Information System
AVRASYA 15th INTERNATIONAL CONFERENCE ON SOCIAL SCIENCES , Tbilisi, Georgia, 13 - 15 March 2026, pp.574-589, (Full Text)
Conversational interfaces have become a central point of contact in brand-consumer interactions, yet their growing use raises a persistent design tension. While transparency requirements increasingly require firms to disclose their AI use, such disclosures may also weaken trust and reduce engagement. This study examines how AI disclosure design and anthropomorphic chatbot cues jointly shape conversational marketing outcomes in a leadgeneration context. The proposed model positions perceived legitimacy as the key mechanism linking disclosure design to brand trust and downstream behavioral response. A randomized 2 × 2 between-subjects online experiment manipulates AI disclosure granularity (minimal vs. detailed) and anthropomorphic design cues (low vs. high) in a simulated retail chatbot interaction. The study tests whether detailed disclosure enhances perceived legitimacy, whether legitimacy strengthens brand trust, and whether trust predicts lead acceptance in a contact-based follow-up step. It also examines whether anthropomorphic design directly increases trust and moderates the effect of disclosure on legitimacy. Preliminary findings indicate that detailed disclosure is associated with higher perceived legitimacy, that legitimacy is positively related to brand trust, and that brand trust is the strongest immediate predictor of lead acceptance. The interaction pattern further suggests that anthropomorphic cues may strengthen the positive effect of detailed disclosure on legitimacy. The study contributes to conversational marketing research by treating AI disclosure as a relational design signal rather than a purely legal requirement. It offers practical guidance for firms seeking to remain transparent without weakening user trust and engagement.