Abstract
The emergence of the Fifth Industrial Revolution (5IR) emphasises the need for ethical, human-centric technological integration in knowledge institutions. As a result, this study investigates the competencies, usage patterns, ethical concerns, and contextual challenges influencing the sustainable adoption of Artificial Intelligence (AI) tools among librarians in Nigeria. Grounded in the Technology-Organisation-Environment (TOE) framework and guided by AI ethics principles of transparency, accountability, and fairness, the study employed a mixed-methods descriptive research design. Using a snowball sampling technique, data were gathered from 1244 librarians across Nigeria via a semi-structured online survey distributed through social media platforms (WhatsApp and Facebook). The survey combined closed-ended items and open-ended prompts to capture both quantitative and qualitative insights. Quantitative data were analysed using descriptive statistics (means, frequencies, and percentages), while qualitative responses were subjected to narrative analysis. Findings reveal that librarians predominantly use language tools such as Grammarly and Quillbot, yet demonstrate lower competence and adoption of complex tools like speech-to-text and literature analysis applications. Ethical concerns ranging from data privacy to cultural insensitivity were prevalent, along with structural barriers including poor infrastructure, lack of policies, and limited training opportunities. In conclusion, the need for comprehensive strategies to promote sustainable AI adoption remains a gap. Therefore, the study proposes a holistic strategy for sustainable AI adoption encompassing institutional policy, inclusive training, infrastructural equity, ethical education, and the localisation of AI tools. These measures are vital for aligning librarianship in Nigeria with global 5IR trends while remaining responsive to local realities.
Keywords
Get full access to this article
View all access options for this article.
References
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
