Shift of ambidexterity modes: An empirical investigation of the impact of artificial intelligence in customer service

Abstract

To manage the trade-offs between exploration and exploitation, customer service organizations typically choose a specific ambidexterity mode, such as structural separation or behavioral integration, that suits their context. However, recent research suggests that organizations need to dynamically change their ambidexterity modes to better align with changing environmental and organizational contexts. This study examines the impact of AI in facilitating the shift across various modes of ambidexterity in customer service organizations. Our findings reveal that achieving shifts in ambidexterity modes is challenging, and organizations must overcome technology, business process, and stakeholder related barriers. Based on our findings, we develop a set of propositions for further investigation. Our study contributes to research on the dynamic perspective of ambidexterity by shedding light on how customer service organizations shift from one ambidexterity mode to another and by articulating the important roles played by AI in achieving such shifts.