Graduation Year
2024
Document Type
Thesis
Degree
M.S.Cp.
Degree Name
MS in Computer Engineering (M.S.C.P.)
Degree Granting Department
Computer Science and Engineering
Major Professor
Ankur A. Mali, Ph.D.
Committee Member
Seungbae S. Kim, Ph.D.
Committee Member
John J. Licato, Ph.D.
Keywords
context switch, NLP
Abstract
This study investigates the theoretical impacts of supportive AI tools, specifically Large Language Models (LLMs), on agent behavior and communication dynamics in call centers. While technological advancements have streamlined operations, limited research addresses the indirect ways these tools influence agent behavior. Using frameworks like context switching—the cognitive shift required when external stimuli prompt attention shifts—and the Hawthorne effect, where perceived observation modifies behavior, we examine how LLMs shape communication patterns. In call centers, this context switching occurs indirectly as agents adapt to AI note-taking features, whereas in industries like Architecture, Engineering, and Construction (AEC), automation tools prompt more immediate changes in workflows.
To analyze these effects, we looked at key performance indicators (KPIs) such as call duration, sentiment, and language complexity, using natural language processing (NLP) techniques like sentiment analysis, part-of-speech tagging, and BERTopic modeling. These methods helped us identify changes in language use and communication style before and after the introduction of AI support tools. Our findings suggest that agents in call centers adapt their communication to become more efficient and customer-oriented in response to these supportive tools, leading to interactions that are more structured and purpose-driven, ultimately enhancing service quality and effectiveness.
This research highlights how AI, even when intended only as a support tool, can still influence how people behave and communicate at work. These insights point to the importance of further studying the long-term effects of AI on workplace interactions and culture.
Scholar Commons Citation
Gonzalez, Gerardo L. Wibmer, "Exploring LLM Integration and Its Influence on Agent Behavior and Productivity in Insurance Call Centers" (2024). USF Tampa Graduate Theses and Dissertations.
https://digitalcommons.usf.edu/etd/10691
