Artificial Intelligence as a Catalyst for CRM Operational Efficiency in Retail Banking

Abstract

Artificial intelligence (AI) is increasingly transforming customer relationship management (CRM) in retail banking by improving customer targeting, campaign execution, and decision-making. This paper examines how AI contributes to CRM operational efficiency through the lens of dynamic capabilities theory (DCT). The study draws on selected banking cases and combines a survey of 340 professionals from financial and non-financial institutions with semi-structured interviews with managers from three major Croatian banks. The findings provide descriptive evidence consistent with all three research hypotheses. More than 80% of respondents from AI-adopting organizations reported improved targeting effectiveness and faster campaign execution, while more than three-quarters reported improvements in AI-supported decision-making. The qualitative findings support these results but also indicate that the benefits depend on data quality, digital infrastructure, CRM integration, employee capabilities, and organizational readiness. The findings correspond most strongly to DCT’s sensing and seizing capabilities, while evidence of broader organizational transformation is less pronounced. For bank managers, the results indicate that investments in AI should be accompanied by strong data governance, integrated systems, employee capabilities, and organizational processes that translate AI-generated insights into action. The paper contributes to the literature by demonstrating that CRM value is created not through AI adoption alone, but through the organizational capabilities required to translate AI-generated insights into operational outcomes.