<![CDATA[This study investigates the role of artificial intelligence (AI) in enhancing language learning, with a focus on five key applications: automatic text analysis, personalized learning, adaptive feedback, language error detection, and automatic translation. The study addresses the challenge of integrating AI effectively in educational contexts while balancing technological potential with pedagogical guidance. The objective is to provide a comprehensive understanding of how AI tools contribute to more adaptive, efficient, and engaging language learning experiences. A systematic literature review method was employed, selecting and critically analyzing studies published between 2020 and 2025 that examined AI-assisted language learning strategies. The findings indicate that automatic text analysis supports comprehension monitoring and guided learning, while personalized learning adapts content to individual learner needs, enhancing motivation and retention. Adaptive feedback delivers immediate, targeted guidance that fosters accuracy and self-regulated learning, and language error detection tools enable learners to identify and correct grammatical and lexical mistakes, promoting metalinguistic awareness. Automatic translation broadens access to authentic texts and cross-cultural materials, supporting comprehension and independent learning. Synthesizing these findings highlights the transformative potential of AI to improve learning outcomes while also revealing challenges such as tool reliability, ethical considerations, and the need for teacher oversight. The study concludes that AI, when thoughtfully integrated, complements instruction, enhances learner engagement, and supports differentiated and data-driven teaching strategies, providing valuable insights for language educators and guiding future research on AI-enabled language learning.]]>
