AI-Powered Customer Service Chatbot for Transafam Power Limited: Enhancing Efficiency in Nigeria's Power Sector.

 Effective customer service is vital in Nigeria’s competitive power sector, where timely communication drives customer satisfaction. This study designs and evaluates an AI-powered chatbot for Transafam Power Limited to address communication gaps caused by limited traditional channels (e.g., phone calls, emails, WhatsApp) operating only during business hours. Utilizing a sequence-to-sequence deep learning model with attention mechanisms and rule-based natural language processing (NLP), the chatbot delivers 24/7 support, handles routine inquiries, and escalates complex issues to human agents. Trained on a decade of customer interaction data (2014–2023), the system achieves an intent recognition accuracy of 87% and a resolution rate of 85%. Performance is assessed through statistical metrics, including response time, accuracy, and user satisfaction, with significance tested via chi-square analysis. A web-based prototype, developed using HTML, CSS, JavaScript, MySQL, and Python, integrates seamlessly with human agents. Feature importance analysis highlights key predictors of query resolution, enhancingsystem interpretability. This research underscores the transformative potential of AI-driven chatbots in improving customer service efficiency and accessibility in the power utility sector. Keywords: Customer Service Chatbot, Artificial Intelligence, Natural Language Processing, Transafam Power Limited, Power Sector, Intent Recognition, Statistical Analysis