IJ
IJCRM
International Journal of Contemporary Research in Multidisciplinary
ISSN: 2583-7397
Open Access • Peer Reviewed
Impact Factor: 5.67

International Journal of Contemporary Research In Multidisciplinary, 2026;5(1):403-416

Data Privacy Concerns, Platform Trust and Purchase Intentions in AI-Driven E-Commerce

Author Name: Niranjan Behara;  

1. Department of Commerce, Dr Gour Mohan Roy College, Purba Bardhaman, West Bengal, India

Abstract

The proliferation of artificial intelligence in electronic commerce has fundamentally transformed consumer shopping experiences while simultaneously raising critical concerns regarding data privacy and platform trustworthiness. This comprehensive research paper examines the intricate relationships between data privacy concerns, platform trust, and purchase intentions within AI-driven e-commerce environments through an extensive analysis of secondary data from academic publications, industry reports, and contemporary research. Drawing upon established theoretical frameworks, including privacy calculus theory, technology acceptance model, and trust theory, this investigation synthesises empirical findings from diverse scholarly sources to elucidate the complex dynamics shaping consumer behaviour in digitally mediated marketplaces. The analysis reveals that while AI-powered personalisation significantly enhances customer engagement and conversion rates, with leading organisations achieving revenue growth rates approximately ten percentage points higher than laggards, consumers demonstrate heightened privacy consciousness, with only forty-seven per cent expressing trust in AI companies to protect personal data. The study identifies platform trust as a critical mediating variable between privacy concerns and purchase intentions, with satisfaction serving as a significant pathway to conversion. Regulatory developments, particularly the General Data Protection Regulation and California Consumer Privacy Act, have established new compliance imperatives that profoundly influence organisational strategies and consumer expectations. The findings indicate that successful e-commerce platforms must navigate the personalisation-privacy paradox by implementing transparent data practices, robust security measures, and ethical AI governance frameworks while delivering tangible value propositions that justify information disclosure. This research contributes to theoretical understanding by integrating multiple conceptual frameworks and provides practical implications for e-commerce practitioners seeking to build sustainable competitive advantage through responsible AI implementation and trust-based customer relationships.

Keywords

AI-Driven E-Commerce, Data Privacy Concerns, Platform Trust, Consumer Purchase Intention, Artificial Intelligence in Retail.