Integrating Artificial Intelligence into School-based Sexuality Education in South Africa: Barriers, Enablers, and Pathways for Innovation

Artificial Intelligence (AI) has great potential to transform school-based sexuality education in South Africa by enabling personalised content, improving engagement, and addressing diverse socio-cultural needs. However, the feasibility of AI integration remains uncertain due to limited consolidated evidence, which is exacerbated by the digital divide, unequal access to technology, and varying cultural contexts, particularly in rural communities. This integrated literature review identified the barriers, enablers, and innovative pathways for incorporating AI into sexuality education in South Africa. Following PRISMA guidelines, peer-reviewed and grey literature published from 2020 to 2024 were searched in Scopus, PubMed, Web of Science, and African Journal Online using terms such as "Artificial Intelligence," "sexuality education," and "South Africa." Included studies focused on AI-based tools, platforms, or pedagogies relevant to the South African context. Data were thematically analysed and interpreted through the Technology Acceptance Model to assess perceptions of AI’s usefulness, ease of use, and contextual influences. Twelve studies met the inclusion criteria. Barriers included inadequate rural digital infrastructure, limited AI teacher training, ethical concerns, and socio-cultural resistance. Enablers were policy support, youth digital literacy, and multi-sector partnerships. Innovation pathways involved co-designing AI tools, adaptive chatbots, hybrid learning, AI platforms, Virtual Reality simulations, intelligent tutoring, and AI literacy in teacher development. Therefore, AI can transform school-based sexuality education in South Africa if integrated contextually, ethically, and equitably. Future policies and interventions should address barriers and leverage enablers to achieve sustainable and inclusive outcomes. Recommendations were made for future research that should focus on participatory AI design, policy alignment, and impact evaluation.