Reconceptualizing Applied Linguistics in the Era of Generative AI: Emerging Trends, Opportunities, and Challenges

Abstract

Artificial intelligence (AI) is increasingly transforming the study and practice of applied linguistics, creating new possibilities for language learning, teaching, assessment, research, translation, and communication. This literature review examines the emerging role of AI in applied linguistics and considers how recent technological developments are contributing to a reconceptualization of the field. Particular attention is given to natural language processing, generative AI, large language models, AI-supported language learning, second language acquisition, language assessment, and linguistic research. The review highlights the potential of AI to provide personalized learning, immediate feedback, adaptive assessment, large-scale language analysis, conversational practice, and new forms of human–AI communication. At the same time, it identifies important challenges related to accuracy, algorithmic bias, privacy, academic integrity, authorship, transparency, linguistic inequality, and overreliance on automated systems. The discussion further suggests that AI is expanding the traditional boundaries of applied linguistics by introducing emerging areas such as AI-mediated discourse, machine-generated language, AI literacy, and human–AI interaction. Rather than replacing human linguistic expertise, AI is best understood as a complementary technology that can extend human capabilities when integrated critically, ethically, and pedagogically. The review concludes that the future of applied linguistics depends on developing human-centered and interdisciplinary approaches that balance technological innovation with human agency, linguistic diversity, educational quality, and ethical responsibility in increasingly AI-mediated language environments.