Abstract: As Generative Artificial Intelligence (Gen AI) is evolving rapidly, there is a significant change in the approach by the contact center industry with respect to work culture. Historically, customer service agents working in a contact center used to depend significantly on static scripts and fragmented information systems, which thereby resulted in delayed resolutions, cognitive overload, and made them deliver inconsistent customer experiences. This study explores the paradigm shift that's occurring in contact service centers through implementing Gen AI. Real-time intent recognition, contextual response generation, and personalized engagement across channels are some novel capabilities introduced by Gen AI by adopting Large Language Models (LLMs). Organizations can reduce Average Handling Time (AHT), improve First Contact Resolution (FCR), and enhance Customer Satisfaction (CSAT) scores by integrating Gen AI into core workflows such as issue summarization, behavioral analytics, sentiment tracking, and knowledge retrieval. In order to demonstrate the quantifiable improvements in agent performance and customer engagement, this study adopted a blended research design by combining enterprise case studies, simulation scenarios, and comparative KPI evaluations. Furthermore, it addresses implementation bottlenecks such as onboarding efficiency, multilingual support, emotional intelligence, and real-time guidance. With reference to the industry standards, ethical considerations such as data privacy, algorithmic bias, and explainability are examined. Case examples that are collected from the industry leaders are leveraged to validate the study's conclusions. Through this study, a structured and well-organized roadmap for enterprises is delivered, which aims at transforming contact centers from reactive service units into proactive, intelligence-driven ecosystems.

Satya Karteek Gudipati, “Transforming the Working Style of Call Center Agents Through Generative AI” International Journal of Advanced Computer Science and Applications(IJACSA), 16(6), 2025. http://dx.doi.org/10.14569/IJACSA.2025.0160602

@article{Gudipati2025,
title = {Transforming the Working Style of Call Center Agents Through Generative AI},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160602},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160602},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {6},
author = {Satya Karteek Gudipati}
}