<![CDATA[Pupose- This study aims to synthesize current empirical evidence on the use of AI in language education by identifying commonly used AI technologies, examining reported learning and teaching benefits, and analyzing persistent challenges and future research directions.Methodology- The study employed a Systematic Literature Review (SLR) with qualitative thematic synthesis of 50 empirical studies published between 2023 and 2024. The studies were identified using AI- and language-learning-related search terms and examined through a structured data extraction process that covered AI tools, educational contexts, language domains, reported benefits, challenges, and theoretical perspectives. The extracted data were coded and analyzed thematically to identify recurring patterns, which were interpreted through the perspectives of Computer-Assisted Language Learning (CALL), Technology Acceptance Model (TAM), and Sociocultural Theory (SCT).Findings-The findings showed that ChatGPT and generative AI systems dominate current AI-assisted language learning research. The most frequently reported benefit was feedback, scaffolding, and personalization (44%), followed by language performance and skill development (42%) and teacher support and pedagogical productivity (36%). However, major challenges included accuracy and reliability issues, such as hallucinations (38%), AI literacy and training needs (28%), and risks of over-reliance and reduced critical thinking (26%). Contribution-This study presents a comprehensive synthesis of recent empirical evidence and proposes a human–AI collaborative learning perspective.]]>
