Paper Number
2372
Paper Type
Complete Research Paper
Abstract
In recent years, conversational AI solutions have become increasingly prevalent in customer service centers within the retail banking and insurance industry. This case study delves into the interplay and influence of institutional logic on organizational responses in addressing constraints encountered while implementing these conversational AI solutions. We collaborated with six prominent Swiss retail banks and insurance companies to analyze their conversational AI implementation practices over one year. Our research identifies three primary organizational responses to absorb resource constraints in this context: development of AI Business Unit Capabilities, formation of specialized AI Teams, and establishment of AI Value Streams. Furthermore, we identified that a company’s institutional logic — ranging from opportunistic and cautious to pragmatic AI utilization and innovative customer-centric — significantly molds its organizational response to resource constraints. Additionally, these organizational responses exhibit varying degrees of constraint absorption (i.e., full, partial, or minimal).
Recommended Citation
Schmitt, Kevin and Blohm, Ivo, "Navigating Resource Constraints in Conversational AI Implementations: The Role of Institutional Logics and Organizational Responses" (2024). ECIS 2024 Proceedings. 3.
https://aisel.aisnet.org/ecis2024/track03_ai/track03_ai/3
Navigating Resource Constraints in Conversational AI Implementations: The Role of Institutional Logics and Organizational Responses
In recent years, conversational AI solutions have become increasingly prevalent in customer service centers within the retail banking and insurance industry. This case study delves into the interplay and influence of institutional logic on organizational responses in addressing constraints encountered while implementing these conversational AI solutions. We collaborated with six prominent Swiss retail banks and insurance companies to analyze their conversational AI implementation practices over one year. Our research identifies three primary organizational responses to absorb resource constraints in this context: development of AI Business Unit Capabilities, formation of specialized AI Teams, and establishment of AI Value Streams. Furthermore, we identified that a company’s institutional logic — ranging from opportunistic and cautious to pragmatic AI utilization and innovative customer-centric — significantly molds its organizational response to resource constraints. Additionally, these organizational responses exhibit varying degrees of constraint absorption (i.e., full, partial, or minimal).
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