استطلاع لقياس فاعلية توظيف الذكاء الاصطناعي وتحليل البيانات على تحسين إدارة المعرفة في مؤسسات المعلومات والمكتبات العمانية

Abstract

This study aims to explore the effectiveness of integrating artificial intelligence (AI) and data analytics in improving knowledge management in Omani information institutions and libraries. These institutions face challenges in adopting the latest technologies due to a lack of competencies and resources. The study highlights the role of AI in improving classification, searching, and information retrieval processes, and the role of data analytics in enhancing decision-making. Using a quantitative methodology based on surveys directed at employees and users, the study seeks to provide recommendations for developing effective strategies that enhance the efficiency of knowledge management and the quality of services provided. Through the adoption of a quantitative analysis approach, data was collected via surveys targeted at library staff and users to evaluate their experiences with AI and data analytics. The results showed that AI applications significantly improved the efficiency of classification and information retrieval, while data analytics played a prominent role in enhancing informed decision-making. However, the study also identified some challenges, such as limited technological infrastructure and the need for additional training for staff. The results suggest that integrating AI and data analytics in library and information processes can contribute to improving operational efficiency, service quality, and data-driven decision-making. The study also provides recommendations for overcoming current challenges, including improving staff training, investing in digital infrastructure, and developing effective integration strategies. In conclusion, the integration of AI and data analytics offers significant benefits for the development of Omani library services and enhances their role in the digital age. However, it requires a coordinated effort to overcome technical barriers and limited resources.