The Role of Artificial Intelligence Shopping Assistants in Shaping Consumer Engagement and Purchase Intent in Online Retail

Abstract

The growing proliferation of artificial intelligence (AI) in e-commerce has introduced AI-based shopping assistants, fundamentally changing how consumers find, compare, and buy products online. This study develops and empirically tests a structural model grounded in the Stimulus-Organism-Response (S-O-R) framework, Source Credibility Theory, and the Elaboration Likelihood Model (ELM). The proposed framework conceptualizes that informational value, entertainment value, visual attractiveness, human-likeness, and credibility are important factors of AI shopping assistants that drive consumer engagement and purchase intention. Drawing on survey data from 412 online retail consumers and employing structural equation modelling (SEM), findings reveal that human-likeness and entertainment value are the strongest drivers of consumer engagement, while credibility and human-likeness exert the most substantial direct effects on purchase intention. Consumer engagement functions as a significant mediating pathway between AI characteristics and purchase intention. These results offer important theoretical and practical implications for understanding how AI-based shopping assistants influence consumers in digitally mediated retail environments.