Communications on Applied Electronics
Foundation of Computer Science (FCS), NY, USA
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Volume 8 - Issue 1 |
Published: September 2025 |
Authors: Ajayi Olusola Olajide |
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Ajayi Olusola Olajide . Reimagining Academic Library Services with AI: A User-Centric Framework for Research Support and Digital Transformation in African Universities. Communications on Applied Electronics. 8, 1 (September 2025), 21-27. DOI=10.5120/cae2025652912
@article{ 10.5120/cae2025652912, author = { Ajayi Olusola Olajide }, title = { Reimagining Academic Library Services with AI: A User-Centric Framework for Research Support and Digital Transformation in African Universities }, journal = { Communications on Applied Electronics }, year = { 2025 }, volume = { 8 }, number = { 1 }, pages = { 21-27 }, doi = { 10.5120/cae2025652912 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2025 %A Ajayi Olusola Olajide %T Reimagining Academic Library Services with AI: A User-Centric Framework for Research Support and Digital Transformation in African Universities%T %J Communications on Applied Electronics %V 8 %N 1 %P 21-27 %R 10.5120/cae2025652912 %I Foundation of Computer Science (FCS), NY, USA
In the era of Artificial Intelligence (AI), academic libraries must evolve from traditional static services into dynamic, user-centric platforms that support intelligent research discovery and scholarly engagement. This study presents the design and simulation of a lightweight AI-powered library assistant tailored for African academic libraries, emphasizing personalized information retrieval, automated research support, and citation assistance. The prototype was developed in Python using open-source natural language processing (NLP) frameworks, including Hugging Face Transformers and Sentence-BERT for semantic search, the Crossref API for citation generation, and domain mapping for journal recommendation. A simulation involving sixty user queries across ten personas was conducted, and performance was compared with traditional academic library service benchmarks. The results indicate that the AI assistant dramatically reduced query response time from approximately two days to 0.056 seconds, improved relevance scores from 65% to 87.7%, and enhanced citation accuracy to 97%, while achieving 89% precision in journal recommendations and a user satisfaction rating of 4.6/5. These findings demonstrate that lightweight, low-cost AI systems can significantly enhance research productivity and user experience in African academic libraries. The study concludes with a framework for sustainable AI adoption that addresses infrastructural, digital literacy, and ethical challenges. By bridging the gap between conceptual discussions and empirical validation, this work provides both theoretical and practical contributions to reimagining scholarly communication and library services in under-resourced contexts.