Integrating AI into Asian Tertiary EFL Learners’ Speaking Instruction: A Systematic Literature Review

Few systematic review research specifically explores the integration of artificial intelligence (AI) in English as a Foreign Language (EFL) speaking instruction in Asian higher education. Given current research trends, AI-based instruction is receiving increasing attention for its potential to enhance language learning. Therefore, this review aims to trace the trend of empirical research on integrating AI in EFL speaking instruction between 2018 and 2024 in Asia. Using the PRISMA systematic review protocol, this paper analyzed 21 studies on AI-integrated EFL speaking instruction, exploring trends, AI tools, integrating instructional methods, and the challenges between 2018 and 2024. This research finds that since 2022, research on integrating AI in EFL speaking instruction in higher education has increased significantly, mainly in East Asia, and the research methods are primarily quantitative studies. AI chatbots, apps, and platforms are predominantly seen in EFL speaking instruction and AI virtual human teachers have the potential to be applied in oral English classrooms. Task-based learning shows the greatest potential method for integrating AI into English-speaking instruction. However, several challenges hinder the full adoption of AI in EFL curricula, highlighting gaps in empirical research. This review contributes to the discourse on AI-enhanced EFL instruction by offering new insights into existing practices, identifying research gaps, and emphasizing the need for more effective AI tools and instructional methods in Asian higher education. The study underscores the importance of experimental and qualitative research to refine AI-based pedagogical strategies and enhance EFL learners’ speaking proficiency in tertiary education.