The rapid expansion of influencer marketing has transformed digital branding, with authenticity becoming a cornerstone of consumer trust, particularly among Gen Z and Millennial audiences who prioritize sustainability. However, issues such as unclear disclosures, greenwashing, and algorithmic manipulation have heightened skepticism towards influencer–brand partnerships. This study identifies and models ten interconnected determinants of authenticity—disclosure clarity, value congruence, greenwashing perception, social validation, algorithmic bias, diversity representation, carbon awareness, storytelling authenticity, price perception, and regulatory frameworks—using Interpretive Structural Modeling (ISM) and MICMAC analysis. Drawing on Source Credibility, Signaling, and Legitimacy Theories, it conceptualizes authenticity as a structural and systemic result of ethical alignment, transparent communication, and institutional governance. Expert validation and hierarchical modeling highlight regulatory frameworks and disclosure clarity as foundational drivers, with value congruence and storytelling authenticity serving as crucial mediators of trust. The study enhances theoretical understanding by integrating micro-level influencer credibility with macro-level governance mechanisms and offers actionable insights for building credible, responsible, and sustainability-focused digital ecosystems. By reframing authenticity as both a moral and strategic imperative, this research contributes to the evolving discourse on sustainable influencer marketing.