Integration of AI in CRM: Challenges and guidelines

Abstract

The integration of artificial intelligence (AI) in customer relationship management (CRM) holds great potential for enhancing organizational effectiveness. To achieve successful AI-CRM integration, companies must navigate a landscape filled with challenges and complexities marked by the distinctive nature of CRM processes. However, both academics and practitioners still face challenges in understanding the organizational and managerial elements crucial for successful AI-CRM integration. This study aims to fill this gap by identifying the challenges businesses must overcome in the process of AI integration in a CRM context, from the first discover phase to the final sustain phase. Since the context of AI-CRM integration encompasses expertise in artificial intelligence, customer relationship management, data science, and business management, we utilize a research approach that involves qualitative interviews with several actors (managers, consultants and specialists) across these domains to gain diverse insights into AI-CRM integration challenges and opportunities. We identified eleven specific challenges associated with AI-powered CRM and uncovered a temporal division of these challenges across the four phases of AI implementation. Furthermore, we have developed guidelines for addressing them effectively. The findings contribute to an empirical understanding of AI-CRM integration, offering a long-term perspective on leveraging AI for customer relationships. This research lays the foundation for exploring the activities and capabilities required to navigate the challenges of AI-CRM integration and provides essential questions for managers embarking on this journey.

Keywords

• AI-CRM integration
• Qualitative research
• Innovation management
• Challenges