Human-Centric AI-Driven Social Media Intelligence: Linking Consumer Trust, e-WOM, Purchase Intention, and Perceived Business Sustainability

The world of social media marketing is shifting from traditional con-tent delivery to personalized solutions, algorithmic recommendation systems, AI generated content and Automated Customer Service Chat. While these technolo-gies can increase relevance and responsiveness, the consumer impact of AI-powered brand communications is conditional upon perceptions of brand mes-saging as being trustworthy and human-centered, socially meaningful. The study constructs a consumer-behavior framework of the impact of human-centric AI-driven social media intelligence on trust in AI-based brand content, e-WOM, pur-chase intention and perceived sustainability. Situated in the fields of digital mar-keting, social media intelligence and behavioral consumer analytics, this study aims to investigate a quantitative survey conducted among Indonesian social me-dia users who have been exposed to AI-assisted or AI-generated brand commu-nication. Data was analyzed with PLS-SEM with trust being treated as the inner psychological mechanism and e-WOM as the outer social amplification mecha-nism transferring AI-enabled marketing to purchase intention and perception of Sustainability. Moving beyond technological adoption, this research on AI mar-keting highlights customer intelligence, consumer trust construction, online rec-ommendations and responsible digital value creation. In practice, the framework guides firms in designing AI-enabled social media strategies that are persuasive, credible, customer- and sustainability-oriented.