Anthropomorphic Ai Language and Its Psychological Influence on Consumer Trust And Decision Intention

Abstract

Advances in conversational artificial intelligence have intensified interest in how users psychologically interpret machine-generated language. Unlike system-styled communication, anthropomorphic language enables AI to convey human warmth, intention and social presence, which may alter how consumers evaluate information and form decisions. This study examines how human-like linguistic cues in AI systems shape consumer trust and subsequently influence decision intention. Drawing on anthropomorphism theory, social presence theory, and trust formation models, the research establishes trust as a psychological mediator in consumer–AI interaction. A between-subjects experimental design was employed, exposing participants to either anthropomorphic or non-anthroporphic AI recommendation messages. Measures of perceived trust and decision intention were analysed using descriptive statistics, correlation analysis and regression-based mediation testing. Findings indicate that anthropomorphic AI evokes emotional connection, reduces uncertainty and increases perceived credibility, significantly enhancing decision intention as compared to objective system language. The study concludes that communication tone functions as a persuasive mechanism within AI interfaces, and strategic anthropomorphism offers a pathway to optimise user acceptance and decision-making outcomes.