This study aims to examine the effect of artificial intelligence (AI) system quality on electronic word-of-mouth (e-WOM) and to reveal the determinant and mediating role of brand trust in this process. With the increasing digitalization, AI-powered systems have become an integral part of customer interactions, and the quality of these systems has emerged as a key factor shaping consumer experience. However, the underlying mechanisms through which this effect occurs remain relatively underexplored in literature. Accordingly, the relationships among AI system quality, brand trust, and e-WOM are examined within an integrated research model. In this model, AI system quality is positioned as the independent variable, brand trust as the mediating variable, and e-WOM as the dependent variable. A quantitative research design was employed, and the data were analyzed using structural equation modeling. The findings indicate that AI system quality has a direct and positive effect on e-WOM, while also exerting an indirect effect through brand trust. In addition, brand trust is found to be a strong predictor of e-WOM and plays a partial mediating role in the relationship between AI system quality and e-WOM. These results suggest that consumers are more likely to engage in positive online sharing behaviors not only when systems perform well technically, but also when they trust the brand behind these systems. This study contributes to the literature by providing an integrated perspective on the relationships among AI system quality, brand trust, and e-WOM, and highlights the importance of building trust in AI-driven applications from a managerial standpoint.