Faculty and Students Preparedness for Artificial Intelligence (AI) integration in Higher Education Institutions across Sub-Saharan Africa

Abstract

This study examines how faculty and students in Sub-Saharan African higher education are engaging with artificial intelligence (AI) in their academic practices. Specifically, the study sought to: assess faculty and students’ confidence and access in using artificial intelligence tools in higher education across Sub-Saharan Africa; examine patterns of training, self-learning, and institutional support shaping AI preparedness; identify training needs and preferred learning modalities for effective and responsible AI use, and analyze challenges, ethical concerns, and attitudes influencing AI adoption in higher education. Using a descriptive cross-sectional design, survey data were collected from 315 participants across public, private, and technical/vocational institutions. Quantitative items were analyzed with descriptive statistics, and open-ended responses were thematically analyzed. Findings show that formal AI training remains limited (most respondents report no structured training), while self-learning and peer support are the dominant modes of skill acquisition. Reported barriers include unreliable connectivity and data costs, uneven device access, skills gaps, concerns about accuracy and “hallucinations,” assessment integrity, plagiarism, and privacy. Attitudes toward AI are generally positive but cautious: participants value productivity, idea generation, and writing support, yet worry about overreliance and erosion of originality. Interpreted through Diffusion of Innovation, adoption appears early-to-mid stage, high perceived advantage but constrained by institutional preparedness. The study concludes that universities should (a) build tiered AI-literacy programs that progress from foundations to applied, role-specific competencies; (b) embed integrity-by-design assessment practices and clear disclosure/ethics policies; (c) invest in enabling infrastructure and equitable access; and (d) integrate AI across curricula and professional development. These steps would align day-to-day practices with policy, strengthen institutional capacity, and support responsible, context-appropriate AI use in the region.