Journal of Intelligent Marketing Management

Journal of Intelligent Marketing Management

The Bibliometric Analysis of the Interaction Between Artificial Intelligence and Customer Experience: Identifying Knowledge Structure and Future Trends

Document Type : Excerpt from doctoral thesis

Authors
Amir Khanlari 1
Reza Abdolhoseini 2
1 Associate Prof., Faculty of Business Management, University of Tehran, Tehran, Iran.
2 Ph.D. Candidate in Marketing Management, Kish International Campus, University of Tehran, Tehran, Iran.
JABM.3.2.15564.350878.36792
Abstract
Objective: The interaction between Artificial Intelligence (AI) and Customer Experience (CX) has become a significant and multifaceted domain in marketing and management research. The rapid evolution of AI technologies has transformed customer engagement, enabling unprecedented levels of personalization, data-driven decision-making, and operational efficiency. This study conducts a bibliometric analysis to systematically examine the relationship between AI and CX. It identifies key trends, challenges, thematic clusters, and opportunities, highlighting AI's transformative role in optimizing customer experiences. Additionally, it explores how organizations can integrate AI into customer-centric strategies to achieve sustainable competitive advantages and long-term growth.
Methodology: A bibliometric methodology was applied using Web of Science data. From 6,827 articles, 881 were selected based on publication year, relevance, and document type. Tools like VOSviewer and Bibliometrix analyzed conceptual frameworks, social networks, and key term co-occurrence. Temporal trends, influential authors, and international collaboration patterns were reviewed to map AI-CX research. This approach provided a detailed exploration of AI’s conceptual, social, and practical implications for customer experience.
Findings: The analysis identified China, the U.S., India, and the U.K. as key contributors to AI-CX research based on publication volume and impact. Co-occurrence analysis highlighted three themes: customer interaction personalization, marketing optimization, and AI-related ethical challenges. Social network analysis revealed three research clusters: sentiment analysis, predictive marketing models, and AI's ethical implications in decision-making. These clusters show the shift from technological advancements to practical AI applications in customer engagement. The study also noted an increasing convergence of technology with customer experience strategies.
Conclusion: The findings demonstrate that AI is essential for enhancing customer satisfaction, loyalty, and personalized interactions. AI-driven tools, such as chatbots and predictive analytics, improve service speed, efficiency, and accuracy. However, ethical challenges, including data privacy, algorithmic transparency, and biases, require urgent attention. Balancing technological efficiency with ethical responsibility ensures sustainable AI adoption. Aligning AI with organizational goals transforms customer experiences and drives business success. Addressing challenges and leveraging opportunities unlock AI’s potential for innovation. The study highlights the need for interdisciplinary collaboration and innovative strategies to meet evolving digital consumer demands in an AI-driven world.
Keywords
Artificial Intelligence
Bibliometric Analysis
Customer Experience
Knowledge Structure

Subjects

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Journal of Intelligent Marketing Management
Volume 6, Issue 2 - Serial Number 28
Summer 2025
Pages 171-205

  • Receive Date 21 January 2025
  • Revise Date 25 February 2025
  • Accept Date 26 March 2025