From Recommendation to Purchase: AI Personalization, Trust, and Privacy in E-Commerce

Tvisha Ahuja

From Recommendation to Purchase: AI Personalization, Trust, and Privacy in E-Commerce

Author(s)	Tvisha Ahuja
Country	India
Abstract	AI-driven recommendation systems increasingly shape online purchasing decisions, yet the extent to which trust, privacy concern, and age influence consumers’ willingness to act on these recommendations remains unclear. Using survey data from 151 online shoppers- a sample skewing older, with 74.8% aged 35 and above - this study tested three hypotheses: that trust predicts purchase intention (H1), that privacy concern predicts purchase intention (H2), and that attitude toward personalization differs by age group (H3). H1 was supported: trust was significantly and positively associated with purchase intention (r = .332, p < .001) and remained a significant independent predictor when entered alongside privacy concern, F(2, 148) = 9.29, H2 was not supported; privacy concern showed only a weak negative association that did not reach significance (r = −.156, p = .056). H3 was not supported either, with no significant difference in attitude toward personalization between younger and older respondents (Welch's t(64.19) = 1.43, p = .157). Despite being the highest-rated construct overall, privacy concern did not exhibit a significant direct relationship with purchase intention. These findings suggest that the personalization–privacy trade-off may be better understood through the lens of consumer trust, highlighting trust as a potentially more important factor in translating AI-driven personalization into purchasing intentions.
Keywords	Social and Behavioral Science, Consumer Behavior, E-Commerce, AI-Driven Personalization, Consumer Trust
Field	Mathematics > Economy / Commerce
Published In	Volume 8, Issue 5, September-October 2026
Published On	2026-10-21

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From Recommendation to Purchase: AI Personalization, Trust, and Privacy in E-Commerce

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