Assessing Consumer Willingness to Adopt Ai-Based Personal Shopping Assistants

Abstract

Artificial Intelligence (AI)–based personal shopping assistants (APSAs) are rapidly emerging as innovative tools in online retail and mobile commerce. By simulating human-like guidance through chatbots, recommendation engines, and personalized conversational agents, APSAs aim to enhance shopping convenience, decision-making efficiency, and overall satisfaction. This study investigates Indian consumers’ willingness to adopt AI-based personal shopping assistants (WTA-APSA) and explores the factors that influence adoption, such as perceived usefulness (PU), perceived ease of use (PEOU), trust (TR), and privacy concerns (PC). Using a survey-based approach, responses were collected from 420 online shoppers across metropolitan, Tier-II, and Tier-III cities in India. Structural Equation Modeling (SEM) was employed to test hypothesized relationships. Results reveal that PU, PEOU, and trust significantly influence willingness to adopt, while privacy concerns exert a negative effect. Findings contribute to adoption theory extensions in AI retail contexts and provide practical implications for e-commerce platforms seeking to integrate APSAs effectively.