Opportunities and Challenges of Generative AI for Cybersecurity in Sub-Saharan African Organizations: A Systematic Literature Review

Generative AI (GAI) is increasingly used and studied across various fields in different countries; however, its implications for cybersecurity in Africa remain underexplored. This study investigates the opportunities and challenges of GAI on cybersecurity within the Sub-Saharan African organizations through a systematic literature review. Peer-reviewed journal articles and conference proceedings papers were retrieved from five databases, yielding 51 relevant publications, which were synthesized. The literature review was guided by the PRISMA flow diagram to ensure a structured review. Thematic analysis informed a taxonomy of GAI-related challenges and opportunities, aligned with the NIST Cybersecurity Framework 2.0. Key challenges include the absence of context-specific governance frameworks, technical and model-related limitations, data quality issues and people-related challenges. It was found that the reliance of GAI models on a few dominant languages limits their effectiveness in cybersecurity tasks such as threat detection within Sub-Saharan Africa’s multilingual context. Conversely, GAI presents opportunities to mitigate the region’s cybersecurity skills shortage by automating functions such as cybersecurity awareness and training, log analysis and continuous auditing. The findings provide valuable insights for policymakers, practitioners, and governments seeking to harness GAI for cybersecurity in Sub-Saharan Africa, while also highlighting avenues for future research.