This research examines how a contextually applicable Artificial Intelligence (AI)-driven assistant has been developed and implemented to work with Moodle in Nigerian higher education. With the educational realities of the diversity of language, cultures, and learning demands in Nigeria, this AI assistant offers a localised learning experience according to the needs of the population. The AI assistant can assist students by being able to answer queries and give course direction, as well as offer immediate feedback due to using machine learning and natural language processing, and also target any linguistic and educational shortcomings in the Nigerian environment. The study employ mixed-methods design, such as quantitative and qualitative data. In particular, case studies were carried out at the selected institutions, such as the National Open University of Nigeria, the University of Lagos, and Covenant University. Quantitative data was analysed using regression and comparative models; evidence confirms that the AI teaching assistant was of significant help in increasing student engagement and offering learner-specific learning pathways, which helped students retain and achieve higher performance at 85%. Qualitative data underwent thematic coding which showed that there were positive attitudes towards its potential in improving teaching efficiency (80%), though lack of technical capacity, training, and fears over privacy of data were perceived as limitations. This paper reveals the introduction of contextually relevant AI-based tools within Moodle will improve the digital aspect of pedagogy in Nigerian universities under good institutional policies and development of capacity.