THE ROLE OF AI POWERED PERSONALIZATION IN ENHANCING CUSTOMER EXPERIENCE: A CROSS-INDUSTRY ANALYSIS

Authors

  • Chandra Hariandi ASMI Citra Nusantara Banjarmasin, South Kalimantan, Indonesia Author
  • Ali Asrori ASMI Citra Nusantara Banjarmasin, South Kalimantan, Indonesia Author

DOI:

https://doi.org/10.62207/hsq08t49

Keywords:

AI powered Personalization, Customer Experience, Cross Industry Analysis, Digital Transformation, Customer Trust

Abstract

The rapid adoption of Artificial Intelligence (AI) has transformed customer experience (CX) strategies across industries, shifting from generalized approaches to data-driven personalization. While AI-based personalization has shown positive impacts, most existing studies are sector-specific, limiting comprehensive understanding across different industry contexts. This study conducts a narrative review to explore and compare the influence of AI-powered personalization on key CX dimensions—such as satisfaction, trust, engagement, and loyalty—across retail, banking, healthcare, and hospitality sectors. A systematic literature search (2015–2025) was performed using Scopus, Web of Science, and Google Scholar. Findings reveal significant improvements in CX across sectors, particularly through AI-driven recommendation systems, chatbots, and behavioral personalization. However, ethical concerns, data privacy, and algorithmic bias remain persistent challenges, especially in sensitive sectors like healthcare. The study highlights the importance of adopting a contextual and ethically grounded personalization strategy tailored to each industry's characteristics and customer expectations. This review contributes to the theoretical integration of AI personalization and CX literature, and offers practical guidance for developing responsible, sector-specific AI strategies that enhance customer value.

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Published

2025-05-31

How to Cite

THE ROLE OF AI POWERED PERSONALIZATION IN ENHANCING CUSTOMER EXPERIENCE: A CROSS-INDUSTRY ANALYSIS. (2025). Management Studies and Business Journal (PRODUCTIVITY), 2(5), 2511-2525. https://doi.org/10.62207/hsq08t49