Abstract
The study examined the contributions of artificial intelligence to library collection
development at Ignatius Ajuru University of Education, Port-Harcourt. The study
adopted three objectives, research questions, and one hypothesis, using a descriptive
survey design. The target population consisted of 24 postgraduate students, who were
surveyed using a 4-point rating scale questionnaire titled “Contribution of Artificial
Intelligence to Library Collection Development in Academic Libraries” (CAILCDALQ). A
total of 24 copies of the questionnaire were distributed, with 20 copies returned and
found valid for analysis, resulting in a utilization rate of 83.3%. The data were analyzed
using SPSS Version 25, employing mean and standard deviation for descriptive
statistics, and Pearson Product-Moment Correlation (PPMC) to test the hypothesis
concerning the relationship between predictive analytics and AI-driven methods in
library collection development. Based on the findings, the study recommends that
university administrators and library management prioritize upgrading IT
infrastructure to support AI technologies, library management organize training
programs to enhance staff skills in using AI tools, and library associations and academic
institutions collaborate to increase awareness about the potential of AI in library
services through workshops, webinars, and sharing success stories.
Keywords: Predictive analytics, recommendation systems, automated cataloguing,
academic libraries
Publication Date: 2026-07-31