Artificial Intelligence Personalization and Customer Engagement: A Systematic Review

Abstract

The emergence of artificial intelligence (AI) has become a vocal strategy in digital marketing and has no doubt been receiving huge attention and adoption. Firms now channel individualized services and marketing communication to its customers using machine learning algorithms, predictive analytics, and large-scale consumer data from purchase or engagement history to provide highly personalized offerings. Despite this, the relationship between AI personalization and customer engagement is inconsistent across different digital environment. Thus, the need to evaluate existing literatures. This study addresses this gap by conducting a systematic review of literatures from year 2022 to 2026, synthesizing evidence from 84 peer reviewed studies on AI personalization and customer engagement in the e-commerce environment. It found out the dominant research themes, patterns, methodological approaches, and key determinants influencing engagement outcomes. The result established that engagement comes from perceived usefulness and relevance of a firms’ offering, however, concerns regarding privacy, algorithmic transparency and intrusiveness remains key challenges affecting consumers which may undermine trust and limits the effectiveness of personalization strategies. The use of AI personalization reduces consumers’ information overload and improves its overall digital experiences. From the managerial perspective, the adoption of ethical frameworks and customer-centric personalization will enable firms to enjoy high engagement leading to positive responses and the policy aspect employs government to step in and tackle the growing concern of privacy and intrusiveness from the use of personalization by establishing clear regulatory frameworks and data protection laws for its citizens because the use of AI personalization is shaping the business environment.