Artificial intelligence in Zambian education: A systematic literature review and conceptual framework for sustainable resource allocation

Petros Ndumba; Ndechedzelo Teseletso Tau Tau; Wezzi Memory Mtika

doi:10.51867/AQSSR.3.4.5

Authors

Petros Ndumba The University of Zambia, Department of Educational Administration and Policy Studies Author https://orcid.org/0009-0005-8673-7066
Dr. Ndechedzelo Teseletso Tau Department of Educational Administration and Policy Studies, The University of Zambia Author https://orcid.org/0009-0007-2885-7814
Dr. Wezzie Memory Mtika Department of Educational Administration and Policy Studies, The University of Zambia Author

DOI:

https://doi.org/10.51867/AQSSR.3.4.5

Keywords:

Artificial Intelligence, Systematic Literature Review, Sustainable Resource Allocation, Conceptual Framework, Educational Administration, Predictive Analytics

Abstract

Zambian educational institutions face persistent challenges in allocating material, financial, and human resources fairly and efficiently. These challenges include uneven access to infrastructure and learning materials, staffing constraints, weak information systems, and limited capacity for data-informed planning. Recent scholarship suggests that artificial intelligence (AI) can support forecasting, decision support, monitoring, and optimisation, while also highlighting risks associated with data quality, infrastructure, algorithmic bias, privacy, and unequal institutional capacity. This article presents a systematic literature review (SLR) examining the relevance of AI to sustainable educational resource allocation, with particular attention to the Zambian context. Searches were conducted across Scopus, Web of Science, the Education Resources Information Center (ERIC), and Google Scholar for peer-reviewed journal articles published between 2021 and 2026 and were structured and reported with reference to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. The final coded corpus comprised 180 studies. The synthesis identifies three principal application areas, predictive analytics, teacher allocation, and infrastructure monitoring, alongside supporting domains such as financial planning and policy simulation. Drawing on the Resource-Based View, Dynamic Capabilities Theory, and AI and machine-learning perspectives, the review develops a conceptual framework that integrates AI-enabled allocation with governance, human oversight, contextual adaptation, and accountability. The review indicates substantial potential for AI-supported resource management, but the evidence does not justify assuming automatic gains in efficiency or equity. For Zambia, implementation is likely to depend on reliable data, connectivity, institutional capability, professional development, appropriate governance, and locally adapted models. The proposed framework therefore provides a basis for subsequent empirical validation rather than a claim of demonstrated implementation effectiveness.

Author Biographies

Petros Ndumba, The University of Zambia, Department of Educational Administration and Policy Studies

Doctoral researcher at the University of Zambia's Department of Educational Administration and Policy Studies and UNZA Datalab member under the Department of Computer Studies and Informatics
Dr. Ndechedzelo Teseletso Tau , Department of Educational Administration and Policy Studies, The University of Zambia

PhD-qualified Science Educator with expertise in Chemistry and teacher education, experienced in undergraduate and graduate teaching, supervision of student research projects, and mentoring student teachers during teaching practice. Strong background in curriculum development, outcome-based education, and performance-based assessment, with active engagement in educational research and peer-reviewed publications. Committed to advancing high-quality Science Education through innovative pedagogy, research, and academic service.
Dr. Wezzie Memory Mtika, Department of Educational Administration and Policy Studies, The University of Zambia

Wezzie is a researcher in the field of Educational Administration and Management. Her research interests include: Educational Leadership and Management; Quality Assurance in Education; Learner Discipline and Proactive Behaviour Management; Early Childhood Education Management; Adolescent Education, Well-being and School Climate. Her research particularly focuses on proactive educational management, school governance, and educational quality improvement in diverse educational contexts.

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