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AI-Capable Relationship Marketing: Shaping the Future of Customer Relationships

Roy, Sanjit; Tehrani, Ali; Pandit, Ameet; Apostolidis, Chrysostomos; Ray, Subhasis

Authors

Sanjit Roy

Ali Tehrani

Ameet Pandit

Subhasis Ray



Abstract

This study explores the interlinkages between artificial intelligence (AI), dynamic capabilities, and relationship marketing (RM) outcomes. Drawing upon insights from dynamic capabilities and RM theory, this study delineates the strategies and initiatives organizations can adopt using machine learning (ML) and AI to enhance their adaptability to changing market dynamics and customer preferences, in order to develop and maintain stronger relationships with their customers. Based on qualitative data from 67 interviews with managers in different organizations in India, this study contributes to existing theoretical knowledge and managerial practices, as it proposes a comprehensive research framework that demonstrates how AI technologies can enhance customer relationships throughout the entire customer journey. More specifically, it adopts a dynamic capabilities lens to extend our understanding of the marketing applications of AI by conceptualizing the dual role of AI as (a) a distinct organizational capability and (b) an enabler of dynamic capabilities, improving firms’ position to sense, seize, and transform organizational resources and fortify customer relationships. Our findings also highlight several facilitators and barriers to the adoption of AI, both as a dynamic capability and as an enabler for RM.

Citation

Roy, S., Tehrani, A., Pandit, A., Apostolidis, C., & Ray, S. (in press). AI-Capable Relationship Marketing: Shaping the Future of Customer Relationships. Journal of Business Research,

Journal Article Type Article
Acceptance Date Mar 5, 2025
Deposit Date Mar 6, 2025
Journal Journal of Business Research
Print ISSN 0148-2963
Publisher Elsevier
Peer Reviewed Peer Reviewed
Keywords Artificial intelligence, Machine learning, Dynamic capabilities, Relationship marketing, Customer experience, Cost reduction
Public URL https://durham-repository.worktribe.com/output/3679529