Ethical AI Integration in African Higher Education: Enhancing Research Supervision, Grant Discovery, and Proposal Writing Without Compromising Academic Integrity

Abstract

Purpose – This article investigates how artificial-intelligence (AI) tools can strengthen research supervision, grant discovery and proposal writing in African universities without eroding academic integrity. Design/methodology/approach – A qualitative systematic review of 60 peer-reviewed and grey-literature sources (2020-2025) was conducted. Inclusion and exclusion decisions followed a PRISMA cascade; full-text evidence was coded inductively in NVivo to surface themes around efficacy, risk and governance. Findings – AI applications consistently reduce supervisor feedback-cycle time by an estimated 45 % (median, n = 7 institutional case studies) and raise grant-award hit-rates from 12 % to 19 % when algorithmic match-makers filter calls. Yet these gains introduce plagiarism, data-provenance and authorship-blur risks that intensify where connectivity is weak or policy lagging. A three-year governance roadmap grounded in Ubuntu ethics and Diffusion-of-Innovation theory is proposed to convert efficiency into equitable quality. Practical implications – Policy pilots in Year 1, faculty training in Year 2, and KPI-driven impact audits in Year 3 give administrators a phased strategy for safe AI scale-up. The matrix of affordances versus safeguards (Table 3) offers an immediate checklist for ethics committees. Originality/value – This is the first Africa-focused synthesis that marries PRISMA-guided evidence with Ubuntu-informed ethics to deliver an actionable, culturally consonant AI-governance model for higher education on the continent.

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