Anthropomorphic AI traits and roles in customer journeys: a systematic review and the interaction–activation–outcome framework
系统综述122篇文献，识别拟人化AI的五大特征（社交、思考、情感、自主、负责）和两类角色（功能、关系），提出互动-激活-结果框架，解释其如何影响消费者认知、情感和社会反应，并调节顾客旅程结果。
Purpose Although artificial intelligence (AI) has been studied in marketing for over two decades, the field still lacks an integrative framework that explains how anthropomorphic AI influences consumer perceptions and behaviors. This article presents a systematic review to identify key traits and roles of anthropomorphic AI and how they shape consumer responses and outcomes through the customer journey lens. Design/methodology/approach Using a systematic review methodology, this article analyzes 122 articles through thematic coding. The analysis identifies seven aggregate dimensions, focusing on anthropomorphic AI traits and roles, their associated consumer response mechanisms, and outcomes across diverse interaction contexts. Findings Our analysis reveals four key findings: (1) anthropomorphic AI exhibits distinct traits (social, thinking, emotional, autonomous, and responsible) and roles (functional and relational), which (2) activate consumer response mechanisms (cognitive, affective, and social); (3) influence consumer journey outcomes (behavioral, hedonic, utilitarian, and sustainable); and (4) are moderated by consumer journey conditions (individual differences, interaction contexts, and interaction structures). Originality/value This article introduces a novel, three-stage Interaction–Activation–Outcome framework that explains how interactions with anthropomorphic AI, when its traits and roles are aligned, activate consumer response mechanisms and journey outcomes, with effects being moderated by journey conditions. It also proposes a 2 × 2 matrix illustrating how the intersections between anthropomorphic AI traits (single vs. multiple) and roles (functional vs. relational) necessitate different strategic approaches, offering practical managerial insights. The article concludes by outlining future research directions, including examination of human–AI collaborative journeys, and AI applications in sustainable and base-of-the-pyramid markets.