Factors affecting changes in the customer journey with generative AI shopping agents: aspects of purchase decision-making

This study investigated the effects of upcoming generative artificial intelligence shopping agents (GAISA) on changes in consumer behaviour and the customer journey by applying behavioural reasoning theory (BRT) and trust transfer theory. Contextual relevance, time/effort saving, usefulness of advice, and perceived informativeness were identified as reasons for adopting GAISA, while perceived complexity, traditional barriers, privacy concerns, and perceived irritation were identified as reasons against. Purchase intention was found to form through trust transfer from GAISA to recommended goods, with customers’ tendencies towards algorithm use and recommendation target types acting as boundary conditions. This study extends BRT and customer journey theory by showing that GAISA replace customers’ roles in early journey stages, and by positioning contextual relevance as a privacy-preserving alternative to preference-based personalisation.