Generative-artificial intelligence: Implications to Nigerian academic libraries
The adoption of generative artificial intelligence (AI) in academic libraries is essential for maintaining their relevance in an increasingly dynamic information environment. Embracing this technology enables libraries to meet the evolving needs of their clientele and align with global developments in information and communication technologies. This paper explores the concept of AI technology, categorizing it according to levels of intelligence, complexity, and functional tasks. It further examines the necessity and applicability of generative AI in key library operations, including information retrieval, reference services, and other core information functions. The study highlights the benefits and implications of generative AI adoption, such as the optimization of resource management, enhancement of user experience, provision of real-time and round-the-clock responses to user inquiries, and improvement of service accessibility and efficiency. Despite these advantages, the paper identifies several challenges hindering effective adoption in Nigerian academic libraries, including concerns over intellectual property rights, technophobia among some librarians, and issues of data quality and reliability. The study concludes that successful integration of generative AI in Nigerian academic libraries depends largely on the level of awareness, digital literacy, and technical competencies possessed by both librarians and users. It recommends that librarians acquire the necessary skills not only to manage AI-based tools but also to design context-specific systems capable of addressing challenges related to intellectual property, data integrity, and adherence to bibliographic standards such as the Anglo-American Cataloguing Rules, Second Edition (AACR2).
Authors
- Salisu Dahiru
Institutions
- Maitama Sule University Kano (NG)
Publication Details
- Journal
- Library and Information Perspectives and Research
- Published
- 2025-12-31
- DOI
- https://doi.org/10.47524/lipr.v7i4.22
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00