AI-Assisted Service Work: Boosting Efficiency but Eroding Human Skills?

The integration of AI assistants into customer service has significantly enhanced operational efficiency and customer satisfaction. However, concerns about long-term impacts on employee skill retention, particularly in complex and adaptive tasks, have emerged. This study proposes a six-month longitudinal field experiment involving 300 customer service representatives, examining performance metrics and psychological factors across full AI assistance, partial AI assistance, and a control group. Additionally, an intervention using "AI-free" days and gamified problem-solving exercises is tested to mitigate potential skill erosion. Results will provide empirical insights into balancing AI-driven efficiency gains with the preservation of essential human cognitive skills, guiding responsible AI implementation strategies.

Institutions

Publication Details

Journal
Journal of the Association for Information Systems
Published
2025-08-15
Primary Topic
Magnetic confinement fusion research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI-Assisted Service Work: Boosting Efficiency but Eroding Human Skills?

Journal of the Association for Information Systems
Magnetic confinement fusion research
article

AI-Assisted Service Work: Boosting Efficiency but Eroding Human Skills?

article en

Abstract

The integration of AI assistants into customer service has significantly enhanced operational efficiency and customer satisfaction. However, concerns about long-term impacts on employee skill retention, particularly in complex and adaptive tasks, have emerged. This study proposes a six-month longitudinal field experiment involving 300 customer service representatives, examining performance metrics and psychological factors across full AI assistance, partial AI assistance, and a control group. Additionally, an intervention using "AI-free" days and gamified problem-solving exercises is tested to mitigate potential skill erosion. Results will provide empirical insights into balancing AI-driven efficiency gains with the preservation of essential human cognitive skills, guiding responsible AI implementation strategies.

Journal of the Association for Information Systems
Quinnipiac University (US)
Quality Education
Openalex Percentile: Top 38%
Magnetic confinement fusion research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.