The challenges of AI implementation in academic libraries: A case study of University of Ilorin Library, Kwara State
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- NGN 5000
Background of the study
AI technologies—ranging from machine learning‑driven recommendation engines to natural language processing chatbots—offer academic libraries the potential to streamline workflows and enhance user experiences (Nguyen, 2023). Yet, successful AI integration depends on overcoming multifaceted challenges: infrastructure deficits, data quality issues, staff skill gaps, and ethical considerations (Chima, 2024). In Nigerian academic contexts, studies highlight unreliable power supply, limited bandwidth, and scarce funding as barriers to deploying robust AI systems (Adewale, 2025). University of Ilorin Library has initiated AI projects, including automated metadata extraction and a virtual reference assistant, but reports indicate frequent system downtimes, low user adoption, and concerns over data privacy (Ibrahim, 2024). Understanding these obstacles through a focused case study can guide other institutions contemplating similar initiatives, offering lessons on risk mitigation, stakeholder engagement, and capacity building.
Statement of the problem
Despite the promise of AI, University of Ilorin Library’s automation efforts face persistent challenges—technical, organizational, and human—that threaten project sustainability. However, no comprehensive study has documented these challenges or proposed context‑specific solutions, leaving decision‑makers without evidence to guide resource allocation and strategic planning.
Objectives of the study
To identify technical, organizational, and ethical challenges in AI implementation at University of Ilorin Library.
To assess the impact of these challenges on project outcomes.
To propose strategies for overcoming identified barriers.
Research questions
What technical and infrastructural issues hinder AI deployment?
How do organizational culture and staff competencies affect AI projects?
What measures can address ethical and data governance concerns?
Significance of the study
By systematically documenting implementation challenges and recommending practical solutions, the study will equip library managers, IT teams, and university leaders with actionable guidance to enhance AI project success, ensuring investments yield tangible improvements in library services.
Scope and limitations of the study
This case study is confined to AI projects within University of Ilorin Library. It excludes broader institutional IT initiatives and other libraries in Kwara State.
Definitions of terms
Implementation challenges: Obstacles encountered during planning, deployment, and maintenance of AI systems.
Data governance: Policies and practices ensuring data quality, privacy, and ethical use.
Virtual reference assistant: An AI‑powered chatbot that answers user queries.
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