Abstract
Although AI-enabled customer relationship management (CRM) systems have gained momentum in healthcare to enhance performance, there is a striking dearth of knowledge on how such capabilities are formed and affect service innovation. The study adopted a mixed-method approach to investigate the underlying phenomena. This research infused resource-based theory, dynamic capability theory, and theory of productivity paradox to investigate how healthcare in India acquires AI-enabled CRM capabilities and enhances service innovation. We identified the facets of AI-enabled CRM capabilities using a case study and developed a framework for AI-enabled CRM capability and service innovation. This study noticed that customer service flexibility (CSF) is a missing link in this relationship. The findings of the quantitative study employing PLS-SEM reveal the linear relationships between AI-enabled CRM capability, CSF, and service innovation. This study explains the formation of AI-enabled CRM capabilities to fill the research gap and direct innovative performance in healthcare, which is an immediate need to sustain in a volatile environment. This study provides theoretical implications to enhance the research stream and practical implications for decision-makers. \textcopyright 2022 Elsevier Ltd