The Influence of AI-Driven Personalization on Consumer Trust and Purchase Intention in Online Shopping

Abstract

The increasing integration of artificial intelligence (AI) in digital marketing has transformed how businesses interact with consumers, particularly through personalized content and recommendation systems. This study examines the influence of AI-driven personalization on consumer purchase intention in the Indian e-commerce context, with a specific focus on the mediating role of consumer trust. Grounded in the Stimulus-Organism-Response (S-O-R) framework, the research conceptualizes AI personalization as the stimulus, consumer trust as the organism-level mediating state, and purchase intention as the behavioural response. A quantitative cross-sectional survey was administered to 150 respondents, of whom 108 valid responses were retained after systematic data cleaning. Statistical analyses including descriptive statistics, Cronbach’s alpha reliability testing, Pearson correlation, multiple regression, bootstrapped mediation, one-way ANOVA, chi-square, and exploratory factor analysis were conducted using Python. Descriptive findings reveal that Indian online shoppers hold pronounced privacy concerns (M = 4.023), maintain moderate purchase intention (M =  3.727), and exhibit a meaningful trust deficit relative to their perceived personalization quality (Trust M = 3.245 vs.  Personalization M = 3.609). While inferential results were inconclusive due to measurement quality limitations, the study provides a theoretically coherent pilot-level contribution, reinforces the personalization-privacy paradox in the Indian regulatory environment, and establishes a robust empirical foundation for future confirmatory investigation using Partial Least Squares Structural Equation Modelling (PLS-SEM).