Assessing the application of artificial intelligence and machine learning technologies in library services in Africa

Purpose The paper aimed to investigate the status quo of the application and adoption of AI and ML technologies in providing library services in the African continent. It sought to establish the different use cases that these technologies are put to; it also sought to establish what benefits and challenges come along with the implementation of AI and ML technologies in the context of African libraries. Design/methodology/approach The study adopts the structured literature review approach that identifies the current literature on the application of AI and ML technologies in library services in Africa. It involves searching various academic databases like Scopus, Web of Science, and Google Scholar, using keywords such as “artificial intelligence,” “machine learning,” “library services” and “Africa.” It will be analyzed and synthesized in order to achieve a comprehensive overview of the topic. Findings The review finds that AI/ML technologies in African library services are still in their introductory stage, and there are hardly a few research studies and case studies conducted so far. Its potential benefits include improved information retrieval, enhanced user experience and operational efficiencies. However, a number of challenges are also emphasized in the review, which include the limited availability of technological infrastructure, lack of digital literacy among the library staff and issues concerning data privacy and security, among others. Practical implications These research findings will carry considerable weight among library professionals, policy and technology providers in Africa. The study gave strategic advice on the use of AI and ML technologies within the services provided by libraries. The critical issues have been mentioned along with best practices in this regard. The insights gained from this research can facilitate relevant training programs as well as building capacity that is so much more essential for the diffusion of these technologies in African libraries. Originality/value The present review represents, to the best of the authors’ knowledge, the first comprehensive review that specially outlines the applications of AI and ML technologies in library services on the African continent. The findings further add to the scant literature at hand and create a base for future research and implementation in the African library sector.

Authors

Institutions

Publication Details

Journal
Library Management
Published
2025-05-29
DOI
https://doi.org/10.1108/lm-07-2024-0078
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessing the application of artificial intelligence and machine learning technologies in library services in Africa

Ogagaoghene Uzezi Idhalama, Prisca Iheoma Nwachukwu
Library Management
AI in Service Interactions
article

Assessing the application of artificial intelligence and machine learning technologies in library services in Africa

Ogagaoghene Uzezi Idhalama, Prisca Iheoma Nwachukwu
article en

Abstract

Purpose The paper aimed to investigate the status quo of the application and adoption of AI and ML technologies in providing library services in the African continent. It sought to establish the different use cases that these technologies are put to; it also sought to establish what benefits and challenges come along with the implementation of AI and ML technologies in the context of African libraries. Design/methodology/approach The study adopts the structured literature review approach that identifies the current literature on the application of AI and ML technologies in library services in Africa. It involves searching various academic databases like Scopus, Web of Science, and Google Scholar, using keywords such as “artificial intelligence,” “machine learning,” “library services” and “Africa.” It will be analyzed and synthesized in order to achieve a comprehensive overview of the topic. Findings The review finds that AI/ML technologies in African library services are still in their introductory stage, and there are hardly a few research studies and case studies conducted so far. Its potential benefits include improved information retrieval, enhanced user experience and operational efficiencies. However, a number of challenges are also emphasized in the review, which include the limited availability of technological infrastructure, lack of digital literacy among the library staff and issues concerning data privacy and security, among others. Practical implications These research findings will carry considerable weight among library professionals, policy and technology providers in Africa. The study gave strategic advice on the use of AI and ML technologies within the services provided by libraries. The critical issues have been mentioned along with best practices in this regard. The insights gained from this research can facilitate relevant training programs as well as building capacity that is so much more essential for the diffusion of these technologies in African libraries. Originality/value The present review represents, to the best of the authors’ knowledge, the first comprehensive review that specially outlines the applications of AI and ML technologies in library services on the African continent. The findings further add to the scant literature at hand and create a base for future research and implementation in the African library sector.

Library ManagementVol. 46(5)
Nnamdi Azikiwe University (NG), Ambrose Alli University (NG)
Openalex Percentile: Top 94%
AI in Service Interactions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.