How AI-Driven Marketing Communication Shapes Consumer Attitudes and Purchase Intentions: Evidence from Social Media Users in Romania

Abstract

Artificial intelligence has fundamentally altered how brands create, personalize, and deliver communication on social media, raising important questions about how these technological features shape consumer responses. This study investigates how two AI communication features (AI content optimization and AI transparency) influence brand attitude and purchase intention, with trust and perceived usefulness examined as mediating mechanisms. Drawing on the Stimulus–Organism–Response (S-O-R) framework, a process-oriented model is tested using survey data from 497 Romanian social media users and analyzed with Structural Equation Modeling. Results show that AI content optimization significantly strengthens both perceived usefulness and trust, while AI transparency contributes primarily to trust, with a more limited and context-dependent effect on brand attitude. Trust emerges as the most central mechanism, influencing perceived usefulness, brand attitude, and purchase intention, and mediating key relationships between AI features and consumer responses. Perceived usefulness and brand attitude further translate these internal evaluations into behavioral intentions. Brands should therefore prioritize relevant, well-timed AI-generated content and invest in trust through consistent communication. Theoretically, this study maps the indirect psychological pathways through which AI communication features reach consumer behavior. Empirically, it contributes evidence from an emerging European market that remains underrepresented in this literature.