Customer Service Representative's Perception of the AI Assistant in an Organization's Call Center

2025-07-01

AI Summary

This study investigates the “dual burden” experienced by power-grid customer service agents when using AI assistants: while AI reduces operational burdens (e.g., typing, information retrieval, memory load), it simultaneously introduces new cognitive and regulatory demands—including learning overhead, compliance pressure, and psychological strain. Drawing on ethnographic observation and semi-structured interviews with 13 customer service representatives, complemented by qualitative thematic analysis, the research uncovers the implicit cognitive and affective efforts required to sustain effective human–AI collaboration. Its key contribution is a novel analytical framework—“technology-enabled burden shifting”—which challenges the conventional unidirectional efficiency paradigm by foregrounding how AI deployment redistributes, rather than eliminates, labor burdens within socio-technical systems. The findings provide empirically grounded insights for human-centered AI design and organizational support strategies in intelligent transformation initiatives.

Technology Category

• Humans and AI: Intelligent User Interfaces
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Philosophy and Ethics of AI: AI & Jobs/Labor

Application Category

• Economics, Online Markets and Human Computation: Research challenges in human and human-AI computation
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

The integration of various AI tools creates a complex socio-technical environment where employee-customer interactions form the core of work practices. This study investigates how customer service representatives (CSRs) at the power grid service customer service call center perceive AI assistance in their interactions with customers. Through a field visit and semi-structured interviews with 13 CSRs, we found that AI can alleviate some traditional burdens during the call (e.g., typing and memorizing) but also introduces new burdens (e.g., earning, compliance, psychological burdens). This research contributes to a more nuanced understanding of AI integration in organizational settings and highlights the efforts and burdens undertaken by CSRs to adapt to the updated system.

Problem

• CSRs' perception of AI assistance in customer interactions
• Impact of AI on traditional and new CSR burdens
• Understanding AI integration in organizational call centers

Innovation

• AI tools integration in call centers
• Field visits and CSR interviews
• Analyzing AI burdens and benefits