MSc in Information Systems

Permanent URI for this collectionhttps://rda.sliit.lk/handle/123456789/2481

Students enrolled in the MSc in Information Systems programme are required to submit a thesis as a compulsory component of their degree requirements. This collection contains merit-based theses submitted by postgraduate students specialising in Information Systems. Abstracts are available for public viewing, while the full texts can be accessed on-site within the library.
CC BY-NC-ND 4.0 License
Theses and Dissertations of the Sri Lanka Institute of Information Technology (SLIIT) are licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License .

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    AI-Driven Help Desk Integration: Enhancing Customer Support with Chatbots, Sentiment Analysis, and SLA Automation
    (Sri Lanka Institute of Information Technology, 2025-11) Nimnadi Dilsika
    This research investigates the integration of Artificial Intelligence (AI) into help desk systems to improve customer service efficiency, accuracy, and overall satisfaction. The proposed AI-driven help desk framework combines three intelligent components: a chatbot for instant and automated responses, a sentiment analysis engine to detect and interpret customer emotions, and a Service Level Agreement (SLA) management module that ensures real-time tracking of response and resolution performance. Using a dataset of 40,000 simulated support tickets, the system was evaluated for key metrics such as response time, SLA compliance, and customer satisfaction levels. The results demonstrated notable improvements, including faster response rates, higher SLA adherence, and enhanced emotional understanding in customer interactions. Overall, the study confirms that AI integration transforms traditional help desks into proactive, data-driven, and emotionally intelligent service environments. Future advancements will focus on predictive SLA modeling, multilingual capabilities, and multimodal sentiment analysis for broader adaptability.