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Towards a New Paradigm of University Leadership Ranking: Reinventing Lecturers' Promotion Exercise Through AI-Driven and Citation Metrics in Nigeria

The increasing demand for innovation, accountability, global competitiveness and research excellence has necessitated a new paradigm for university leadership ranking systems and academic promotion practices in Nigerian universities. This study explores how university leadership ranking can be enhanced by reinventing lecturers’ promotion exercises through the integration of Artificial Intelligence (AI)-driven technologies and citation metrics. The study further x-ray how AI can improve traditional promotion procedures by utilizing bibliometric indicators such as citation counts, h-index, research visibility, and scholarly impact to provide objective, transparent, and data-driven evaluations of academic performance.  The paper argues that university leaders who adopt AI-enabled promotion frameworks are better positioned to foster innovation, academic excellence, institutional reputation, global academic visibility, institutional ranking by encouraging high-quality research outputs, and increasing their universities’ standing in national and international ranking. The paper further identifies challenges associated with adoption of AI and citation-based promotion systems, including inadequate digital infrastructure, insufficient internet facilities, AI competencies among lecturers, limited access to reputable indexing databases, ethical concerns, and the risk of algorithmic bias. Despite these challenges, the integration of AI and citation-based assessment offers substantial prospects for promoting fairness, transparency, accountability, efficiency in academic evaluations, and decision-making in university administration. The study concludes that embracing AI-driven promotion frameworks and citation metrics is critical for repositioning Nigerian universities leadership within the global higher education landscape. It recommends strategic investments in digital infrastructure, academic staff training, ethical guidelines to ensure sustainable and inclusive use of AI in universities system.

Keywords: Artificial Intelligence, Citation Metrics, Lecturers’ Promotion, and Universities Research Visibility.