Descriptive survey assesses library staff's skills in data analytics, AI, and digital tools, highlighting training needs.
Objective: To assess library staff’s skills and training requirements in response to the Fourth Industrial Revolution. Methods: The methodology adopted was a descriptive survey design was employed. The study population consisted of librarians from all academic libraries in both public and private universities in Lusaka Province. The study employed a stratified random sampling technique and data was collected using a standard questionnaire with closed-ended questions and analysed using descriptive statistics. Results: The study underscored the evolving technological landscape in library management, highlighting varying levels of proficiency and confidence among respondents in using digital tools and advanced technologies. While most respondents demonstrated confidence in digital library systems (85%) and familiarity with data analytics tools (70.7%), gaps persisted in advanced areas such as AI-based systems, cloud services, and VR/AR integration, with significant portions reporting only moderate or limited proficiency. Consistent with previous studies, the findings emphasised the importance of targeted training and professional development to bridge these gaps, particularly in emerging Fourth Industrial Revolution (4IR) technologies. Respondents identified digital literacy, AI, and data analytics as priority training areas, aligning with the demand for enhanced technological competencies. By fostering continuous learning and institutional support, libraries could empower staff to adapt to technological advancements, ensuring innovative and effective service delivery in the digital era. Conclusion: The study revealed a generally positive trend in confidence and familiarity with digital and emerging technologies among library staff, though varying levels of proficiency highlighted areas for growth. Respondents exhibited strong confidence in using digital library management systems, with the majority feeling confident or very confident. Similarly, familiarity with data analytics tools and AI-based systems showed promise, with many respondents reporting comfort and a reasonable level of understanding.
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- et al. (2025) studied this question.
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