AI-driven cultural fluency in isiZulu: Harnessing artificial intelligence to empower indigenous language education

Abstract

The rapid development of artificial intelligence (AI) and autonomous learning systems has transformed language education worldwide. However, most studies have focused on well-resourced languages such as English, Spanish, French, and Mandarin, with limited attention to African indigenous and under-resourced languages, such as isiZulu. This study interrogates the use of autonomous language-learning technologies in isiZulu, exploring how adaptive digital tools and AI-driven methodologies can support learner autonomy, enhance cultural relevance, and promote linguistic proficiency, particularly through the interpretation of idioms and proverbs. Drawing on secondary literature on computer assisted language learning (CALL), narrative studies of AI in language education, and emerging research on distributed agency in second language teaching, the study examines both the potential opportunities and inherent challenges of deploying autonomous systems in isiZulu education. It further discusses the need for culturally responsive pedagogies, teacher professional development, and appropriate technological adaptations. The study concludes with recommendations for future research and policy implications that prioritise equity and sustainability in multilingual educational contexts.