Abstract
This study examined infrastructural readiness, staff attitude, and ethical considerations on the
effectiveness of artificial intelligence (AI) in archival preservation management within academic
libraries in Cross River State, Nigeria. A correlational survey design was employed with a
population of 779 archival staff, from which 390 participants were selected using multistage
sampling. Data were collected with a validated instrument titled Infrastructural Readiness, Staff
Attitude, and Ethical Considerations on Effectiveness of AI in Archival Preservation
Management in Academic Libraries Questionnaire (IRSAEC-AIAPMALQ). Findings revealed
that infrastructural readiness significantly predicted AI effectiveness, emphasizing the role of
modern computing systems, network connectivity, and digital tools. Staff attitude was also
significant, indicating that openness to technology and proactive engagement enhanced AI
adoption. Ethical considerations further influenced AI effectiveness by ensuring compliance with
professional and legal standards. Additionally, the joint effect of the three predictors explained a
substantial variance in AI effectiveness, underscoring the multidimensional nature of AI adoption
in archival management. Based on the findings of the study, it was recommended among others
that; academic institutions should strengthen infrastructural readiness by investing in robust
digital infrastructures, including reliable internet connectivity, cloud-based storage systems, and
AI-driven archival tools capable of automating indexing, metadata creation, and long-term
preservation, and that library administrators and policymakers should prioritize continuous staff
capacity building through targeted training, workshops, and mentorship programs focused on AI
competencies, digital ethics, and emerging preservation technologies. By cultivating positive
staff attitudes and improving digital literacy, institutions can reduce resistance to innovation and
enhance the effective utilization of AI solutions.
Keywords: Artificial intelligence, archival preservation management, infrastructural readiness,
staff attitude, ethical considerations, academic libraries
Publication Date: 2025-11-08