AI Governance and Consumer Trust in Digital Business: The Mediating Role of Perceived Fairness and Moderating Role of Algorithmic Transparency

Abstract

Artificial Intelligence (AI) has become foundational for dynamic pricing, personalized curation, and algorithmic credit scoring in digital platforms. However, the black-box nature of algorithmic decision-making frequently triggers consumer anxiety regarding systemic bias and unfairness. This study investigates the impact of AI governance on consumer digital trust, examines the mediating mechanism of perceived fairness, and evaluates the moderating effect of algorithmic transparency. Utilizing an explanatory quantitative survey, empirical data were collected from 280 active users of e-commerce platforms and fintech applications in Indonesia. Data were evaluated using Partial Least Squares Structural Equation Modeling (PLS-SEM) in SmartPLS 4.0. Empirical findings confirm that: (1) AI governance positively and significantly influences perceived fairness (β = 0.482; p < 0.001) and consumer trust (β = 0.215; p < 0.001); (2) perceived fairness strongly enhances consumer trust (β = 0.514; p < 0.001); (3) perceived fairness significantly mediates the relationship between AI governance and consumer trust (indirect effect β = 0.248; p < 0.001); and (4) algorithmic transparency positively moderates the impact of AI governance on perceived fairness (β = 0.195; p < 0.001). The model explains 61.8% of the variance in consumer trust (R² = 0.618). This research concludes that robust AI governance, bolstered by explicit algorithmic explainability, fosters perceived procedural and distributive fairness, which fundamentally underpins long-term consumer trust.