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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). [ABSTRACT FROM AUTHOR]

This study examines through a systematic review, the reference services rendered in academic libraries using artificial intelligence (AI) and by collecting data through environmental scanning. The objective of this systematic literature review is to provide a synthesis of empirical studies exploring the application of artificial intelligence for reference services in academic libraries. Data were collected from Web of Science, Scopus, and LISA databases. Following the rigorous/established selection process, a total of thirty five articles were finally selected, reviewed and analyzed. Thirty five papers were identified, analyzed and summarized on the subject relating to the application of AI and the methods which are most often used. The findings demonstrate that university libraries in Canada and China are leading in the deployment of AI for reference services. The AI techniques used mostly in the scanned university libraries are self-directed learning and natural language processing techniques; while the challenges of using AI for reference services are the problem of quality intelligence, linguistic style, privacy, a threat to intellectual freedom, bias, and cost; inadequate experts, poor network, poor training and lack of innovation, and limited knowledge about the technology. The study indicates university libraries take into account implementing AI for reference services. [ABSTRACT FROM AUTHOR]

A growing number of new public citation databases, available free of charge and accessible on the open web, are offering researchers a new place to start their searching, providing an alternative to Google Scholar and library resources. These new "public discovery services" index significant portions of scholarly literature, then differentiate themselves by applying technologies like artificial intelligence and machine learning, to create results sets that are promoted as more meaningful, easier to navigate, and more engaging than other discovery options. Additionally, these new public discovery services are adopting new linking technologies that connect researchers from citation records to full text content licensed on their behalf by their affiliated libraries. With these new sites logging millions of sessions a month, they present unique opportunities for libraries to connect to researchers working outside the library and challenges in how the library can make itself obvious in the user workflow. [ABSTRACT FROM AUTHOR]