This study aims to identify trends in the use of artificial intelligence in foreign language learning, classify the major forms of AI technologies, and synthesize their effects on personalized language learning. A systematic literature review was conducted following the PRISMA guidelines, analyzing 53 peer-reviewed studies published between 2018 and 2025 from Scopus, Web of Science, and IEEE Xplore. The results show a marked increase in publications after 2022, with research attention shifting from conventional adaptive learning systems to large-language-model-based chatbots, intelligent tutoring systems, speech recognition tools, and automated writing feedback. AI supports personalization by adapting content, learning pathways, and task difficulty; providing immediate feedback; promoting learner autonomy and self-regulation; and reducing language anxiety. However, its effectiveness depends on pedagogical design, learners’ technological readiness, cultural and linguistic contexts, and teachers’ orchestration roles. The article recommends the development of culturally responsive AI models, longitudinal studies, multimodal integration, and ethical and data-protection standards for AI-supported language education.