The role of AI in improving interlibrary loan services in Ekiti State University Library, Ado-Ekiti, Ekiti State
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Background of the study
Interlibrary loan (ILL) services are critical in facilitating resource sharing and supporting academic research across institutions. The integration of AI into ILL systems at Ekiti State University Library has the potential to streamline operations, enhance efficiency, and reduce turnaround times for resource requests. AI-powered algorithms can automate the process of cataloging, matching user requests with available materials across networks, and predicting resource demand based on historical usage patterns (Afolabi, 2023). By employing natural language processing and machine learning techniques, the library can offer personalized recommendations and optimize routing for interlibrary loans, thereby reducing human error and administrative burdens. Furthermore, AI can assist in inventory management, ensuring that high-demand resources are adequately stocked and accessible when needed. Despite these benefits, the transition to AI-enhanced ILL services requires addressing challenges related to system integration, data interoperability between libraries, and staff training (Babatunde, 2024). This study aims to assess the role of AI in transforming interlibrary loan processes, identifying best practices and potential pitfalls in its implementation, with a focus on enhancing service delivery at Ekiti State University Library.
Statement of the problem
Although AI offers promising enhancements to interlibrary loan services, the implementation at Ekiti State University Library faces several challenges. The current system struggles with data inconsistencies, limited interoperability with partner institutions, and a lack of technical expertise among staff. These issues result in delays and inefficiencies that hamper the effectiveness of ILL services. Moreover, the cost of integrating advanced AI systems poses a significant barrier, particularly in resource-constrained environments. The absence of comprehensive evaluations on these aspects necessitates further investigation to ensure that AI integration meets the desired outcomes (Afolabi, 2023).
Objectives of the study
To evaluate the effectiveness of AI in streamlining interlibrary loan services.
To identify technical and operational challenges in AI integration within ILL systems.
To recommend strategies for improving AI-driven interlibrary loan services.
Research questions
How does AI improve the efficiency of interlibrary loan services?
What are the primary technical and operational challenges faced during AI integration?
How can interlibrary loan processes be optimized using AI?
Significance of the study
This study is significant in that it investigates the transformative potential of AI in enhancing interlibrary loan services. The findings will aid library managers, IT professionals, and academic administrators in developing more efficient, cost-effective, and user-friendly ILL systems. The research also contributes to the broader understanding of AI applications in library operations (Afolabi, 2023; Babatunde, 2024).
Scope and limitations of the study
This study focuses on the impact of AI on interlibrary loan services at Ekiti State University Library. It does not cover other library services or institutions outside the study area.
Definitions of terms
Interlibrary Loan (ILL): A service that allows libraries to borrow materials from one another to fulfill user requests.
Natural Language Processing (NLP): A branch of AI that enables computers to understand and interpret human language.
Interoperability: The ability of different systems and organizations to work together seamlessly.
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