AI Chatbot Knowledge-centric Services for Enhanced Customer Interaction

Abstract

The internet and the growth in internet users have undoubtedly influenced the evolution of chatbot development and adoption. Various industries are increasingly adopting Artificial Intelligence (AI) and chatbot technologies to manage customer interactions and enhance customer service. As these industries increase the deployment of AI chatbot to support their customers and improve their user-experience, its therefore significant for them to understand the knowledge-centric service delivery. This study investigates the knowledge-centric quality service and responsiveness of a rule-based WhatsApp chatbot implemented by a South African mobile telecommunications service provider in resolving customer queries. The study adopted a mono-method approach within the interpretivism paradigm, were qualitative insights gathered through thematic analysis of interviews with three employees and a further platform evaluation. The chatbot immediately replies and presents the main menu with various options for the user to select. The matrix shows how the chatbot performed in each main menu task/item relative to usability, accuracy, performance, and interactive responsiveness. Findings highlight the importance of ongoing performance monitoring and iterative improvements in AI-driven knowledge interface design to align with evolving customer expectations and industry benchmarks for service quality. This study contributes to the growing discourse on AI-driven customer knowledge-centric service solutions in South African mobile telecommunications and other industries by offering a comprehensive framework for evaluating and enhancing chatbot effectiveness. This research paper position chatbots as a knowledge-mediation interface that translates organizational information into task-oriented exchanges, shaping escalation pathways, retention of operational know how and customer experience.