APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND NATURAL LANGUAGE PROCESSING IN APPLIED LINGUISTICS: A SYSTEMATIC REVIEW OF METHODS, OUTCOMES, AND RESEARCH TRENDS

Abstract

AI and NLP are transforming applied linguistics, enabling deeper insights, more precise analyses, and innovative approaches to language learning and research.  This systematic review examines the applications of Artificial Intelligence (AI) and Natural Language Processing (NLP) within the field of applied linguistics, focusing on research methods, empirical outcomes, and emerging trends. In addition, peer-reviewed studies were systematically identified, screened, and analyzed to evaluate how AI-driven tools by following PRISMA-guided procedures. It includes machine learning algorithms, automated text analysis, speech recognition, and intelligent tutoring systems. These tools have been employed across key applied linguistics domains such as second language acquisition, language assessment, discourse analysis, and corpus linguistics. The findings indicate that AI and NLP technologies significantly enhance linguistic analysis accuracy, personalize learning experiences, streamline assessment processes, and reveal complex patterns in language use. In conclusion, the study offer transformative potential for both research and pedagogical practices in applied linguistics.