The role of AI in streamlining catalog management in Akwa Ibom State Polytechnic Library, Ikot Osurua, Akwa Ibom State
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- NGN 5000
Background of the study
Catalog management is fundamental to the efficient operation of any library, and AI is increasingly being leveraged to streamline this process. At Akwa Ibom State Polytechnic Library, Ikot Osurua, AI technologies are deployed to enhance the organization, classification, and retrieval of library resources. These systems utilize natural language processing and machine learning algorithms to analyze bibliographic data, automatically update catalog records, and generate relevant metadata (Odu, 2023). The adoption of AI in catalog management has resulted in faster processing times, improved data accuracy, and reduced human error. Enhanced cataloging efficiency not only benefits library staff but also significantly improves user experience by facilitating quicker access to needed materials. Despite these benefits, challenges such as high implementation costs, the complexity of integrating AI with existing systems, and the need for specialized staff training remain critical issues (Eze, 2024). This study investigates the role of AI in streamlining catalog management at Akwa Ibom State Polytechnic Library by evaluating its impact on operational efficiency, user satisfaction, and overall data accuracy.
Statement of the problem
While AI offers substantial improvements in catalog management, the implementation at Akwa Ibom State Polytechnic Library is challenged by issues such as system integration difficulties, inadequate training of library staff, and the high costs associated with AI technology. These factors can result in inaccuracies in catalog records and hinder the overall efficiency of the library’s services. This study aims to identify and address these challenges to ensure that AI integration in catalog management fully enhances the library’s operational capabilities (Onyema, 2024).
Objectives of the study
To assess the impact of AI on catalog management efficiency.
To identify challenges in integrating AI with existing systems.
To propose strategies for optimizing AI-driven catalog management.
Research questions
How does AI improve catalog management processes?
What challenges hinder effective integration of AI in catalog management?
What measures can enhance the performance of AI in this context?
Significance of the study
This study is significant as it provides insights into the potential of AI to revolutionize catalog management in academic libraries. The findings will help library administrators streamline operations, reduce manual errors, and improve resource accessibility at Akwa Ibom State Polytechnic Library (Chukwu, 2024).
Scope and limitations of the study
Limited to the topic only.
Definitions of terms
Catalog Management: The process of organizing and maintaining library records.
Natural Language Processing (NLP): AI technology used to interpret human language.
Machine Learning: Algorithms that enable systems to learn and improve from data.
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