AI-Driven Hyper-Personalization for E-Commerce: Technologies, Value, and Ethical Challenges

05 November 2026, Version 1
This content is an early or alternative research output and has not been peer-reviewed by Cambridge University Press at the time of posting.

Abstract

Marketing have accelerated the rise and implementation of the AI tolls. The AI tools are saping themselves in accordance with the directive of the marketing and markets. The personalization has been another such accelerator in the contemporary marketing practices. The Ethics and Challenges are the simultaneous elements that are seeking space in the modern marketing line. Online retailers have moved from broad market segmentation toward experiences that adapt in real time to each shopper. This assignment examines AI-driven hyper-personalization in e-commerce: how it differs from earlier personalization, which technologies power it, and how it is applied across the customer journey. It reviews the evidence on business value and then critically assesses the privacy, fairness, autonomy, and pricing risks that accompany it. The analysis argues that hyper-personalization creates durable advantage only when technical sophistication is matched by transparent data practices, rigorous measurement, and respect for customer agency. The assignment closes with practical recommendations and directions for future research.

Keywords

e-commerce
recommender systems
data privacy
algorithmic fairness
hyper-personalization
artificial intelligence

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