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This paper focuses on the opportunities and challenges associated with the use of artificial intelligence (AI) in academic library operations. In the quest to render fast, effective and efficient services, academic libraries have adopted different technologies in the past. Artificial intelligence technologies is the latest among the technologies currently being introduced in libraries. The technology which is considered an intelligent system, come in the form of robots and expert systems which have natural language processing, machine learning and pattern recognition capabilities. This paper examined the features of AI, the application of AI to library operations, examples of academic libraries with AI technologies in Sub-Saharan Africa, the need for AI in libraries and the challenges associated with the adoption of AI in libraries. The study concluded that AI holds a lot of prospects for the improvement of information services delivery in African academic libraries. Consequently, its adoption is a sinequanon to delivering robust library services in the Fourth Industrial Revolution (4IR).

Open educational resources (OERs) have increased in popularity and are becoming an important method of providing access to, and enhancing, the teaching and learning experience for both lecturers and students. Despite their popularity, approaches that may work best for sustaining OER initiatives in Nigerian universities are still evolving in Library and Information Science (LIS) literature. Considering the current budget climate for higher education in Nigeria, a framework that is tended towards the sustainability of OER needs to be developed. This article examines opportunities and threats surrounding OER, as well as highlighting major players in the OER landscape. A mixed method approach consisting of a survey and focus groups was used to gather both qualitative and quantitative information from academics and librarians at selected universities in Nigeria, who participated in the Nigerian Universities Commission's (NUC) OER ranking exercise. Data was analysed using descriptive statistics and thematic analysis respectively. While this paper provides recommendations based on findings on one hand, it also proffers suggestions for other libraries interested in growing OER initiatives focusing on development, implementation and assessment for universities operating with limited resources.