Paper Number

ICIS2025-2193

Paper Type

Short

Abstract

Live customer-service calls place heavy demands on agents’ limited attentional resources: they must listen, speak, retrieve information, and follow prescribed procedures simultaneously. Yet most AI support tools remain reactive, relying on user-initiated queries and thus amplifying the very cognitive load they are meant to relieve. To address this issue, we examined AI-augmented proactive guidance embedded directly in service agents’ interfaces. Using a design-science research methodology, we carried out three iterative development and evaluation cycles. These cycles yielded three design principles, rooted in theory and practice, and guided our transition from a low-fidelity prototype to a fully instantiated web-application artefact. Findings from controlled evaluations in the form of semi-structured interviews with customer-service practitioners validate our nascent design theory. Alongside the design principles, we provide a transferable system architecture for practical deployment and outline avenues for further evaluation.

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Dec 14th, 12:00 AM

Real-Time Guidance Design: Principles for AI-Augmented Proactive Guidance Systems Supporting Human Dialogue in Customer Service

Live customer-service calls place heavy demands on agents’ limited attentional resources: they must listen, speak, retrieve information, and follow prescribed procedures simultaneously. Yet most AI support tools remain reactive, relying on user-initiated queries and thus amplifying the very cognitive load they are meant to relieve. To address this issue, we examined AI-augmented proactive guidance embedded directly in service agents’ interfaces. Using a design-science research methodology, we carried out three iterative development and evaluation cycles. These cycles yielded three design principles, rooted in theory and practice, and guided our transition from a low-fidelity prototype to a fully instantiated web-application artefact. Findings from controlled evaluations in the form of semi-structured interviews with customer-service practitioners validate our nascent design theory. Alongside the design principles, we provide a transferable system architecture for practical deployment and outline avenues for further evaluation.

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