The rapid diffusion of AI-enabled conversational agents has transformed how firms design digital marketing interfaces and customer engagement strategies. Over the past five years, research has increasingly examined the role of anthropomorphism in shaping consumer responses to chatbots, particularly concerning attribution processes, trust formation, and loyalty-related behaviors. However, empirical findings remain inconsistent due to variation in theoretical foundations, operational definitions, and methodological approaches. This systematic literature review synthesizes peer-reviewed studies published between 2022 and 2025 across marketing, information systems, communication, psychology, and human–AI interaction. Following PRISMA 2020 guidelines, this study analyzed 118 eligible articles from Scopus, Web of Science, and ScienceDirect using a multi-stage screening protocol, thematic coding, and qualitative meta-synthesis. The review reveals three dominant theoretical clusters—computers-are-social-actors (CASA), social presence theory, and agency-attribution theory—each producing different predictions about how anthropomorphic cues influence trust and loyalty outcomes. The findings highlight that perceived agency and perceived humanness function as dual-route mechanisms in consumer evaluation, while trust operates as a central mediator linking chatbot design to behavioral intentions. Despite growing interest, several gaps remain, including limited longitudinal evidence, fragmented methodological designs, and weak integration of cross-cultural perspectives. This SLR proposes an integrative conceptual model and outlines future research directions for AI-based customer experience management.