AI literacy of library and information science students in Africa: insights from Ghana, Nigeria, Rwanda, South Africa and Uganda
DOI:
https://doi.org/10.47989/ir31348430Keywords:
AI literacy, LIS education, librarianship, Ethical AI, Africa, AI Governance, Digital LiteracyAbstract
Introduction. As artificial intelligence (AI) reshapes global education and information systems, Africa’s readiness remains uneven. This study examines AI-literacy among Library and Information Science (LIS) students—future librarians—across five African countries: Ghana, Nigeria, Rwanda, South Africa and Uganda. It assesses their technical proficiency, tool usage and ethical awareness in an AI-driven era.
Method and Analysis. A quantitative survey was conducted with 437 LIS students from five African countries. The Games-Howell Post Hoc Test was used to compare AI literacy across countries. ANOVA and Multinomial Logistic Regression (MLR) were applied to analyse variations in AI literacy levels based on country, study level, gender and English proficiency.
Results. The findings reveal significant disparities in AI literacy between the five African nations. The results of the Games-Howell post hoc test show that both Rwanda and Uganda have significantly higher mean AI literacy scores compared to Ghana and Nigeria. In contrast, South Africa's scores did not show a statistically significant difference from the other countries, highlighting the varied readiness levels. The study found that ChatGPT dominates usage at 71.9%, while specialised tools such as Elicit remain significantly underutilised at just 4.6%. Ethical concerns among students are also notable, with 39.6% citing worries about privacy risks and 33.2% being troubled about algorithmic bias, highlighting AI anxieties and its societal impact.
Conclusion. This study calls for integrating AI literacy into LIS curricula and advocating for multilingual AI tools. Where new modules are not feasible, institutions can leverage existing courses such as Information Retrieval, Digital Libraries and Research Methods to embed AI content. The results emphasise that context-driven interventions are essential to ensure AI enhances equitable knowledge access rather than deepening existing disparities.
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Copyright (c) 2026 Zakir Hossain, Md. Sakib Biswas, Sophia V. Adeyeye, Monica M. Danquah, Margaret Sraku-Lartey, Berthilde Uwamwezi, Corinne Hertel
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