This paper explores the integration of artificial intelligence (AI) applications into customer relationship management (CRM), focusing on how organizations can implement AI successfully in this context. Using an explorative qualitative approach that includes interviews with AI experts, solution providers, and companies attempting AI-CRM integration, we identify key steps and practical activities often overlooked in literature and industry practice. Our findings provide a comprehensive framework for integrating AI into CRM, emphasizing aspects such as ethics by design, customer data centralization, model retraining, and ongoing user involvement. This study offers academic contributions by extending theoretical insights on AI-CRM integration and provides practical guidance for executives and practitioners, helping align AI capabilities with CRM peculiarities to meet business needs.

Artificial intelligence in customer relationship management: A systematic framework for a successful integration

Cristina Ledro
;
Anna Nosella
;
Andrea Vinelli
;
2025

Abstract

This paper explores the integration of artificial intelligence (AI) applications into customer relationship management (CRM), focusing on how organizations can implement AI successfully in this context. Using an explorative qualitative approach that includes interviews with AI experts, solution providers, and companies attempting AI-CRM integration, we identify key steps and practical activities often overlooked in literature and industry practice. Our findings provide a comprehensive framework for integrating AI into CRM, emphasizing aspects such as ethics by design, customer data centralization, model retraining, and ongoing user involvement. This study offers academic contributions by extending theoretical insights on AI-CRM integration and provides practical guidance for executives and practitioners, helping align AI capabilities with CRM peculiarities to meet business needs.
2025
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3555542
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