Language and Technology: Examining AI, NLP, and Linguistic Research Trends

Abstract

The rapid integration of technology into linguistic research has transformed the ways language is analyzed, understood, and applied. This study provides a comprehensive review of current trends at the intersection of language and technology, with particular emphasis on artificial intelligence (AI) and natural language processing (NLP). By examining scholarly publications from diverse linguistic subfields, the review identifies key thematic areas, including computational modeling of language, AI-driven language learning tools, sentiment and discourse analysis, and cross-linguistic NLP applications. Findings indicate a marked increase in interdisciplinary research, highlighting both the opportunities and challenges posed by algorithmic approaches to linguistic inquiry. The study also maps methodological patterns, theoretical orientations, and regional research outputs, revealing gaps in underrepresented languages and sociolinguistic contexts. Finally, emerging debates concerning ethical considerations, AI bias, and the implications of automated language technologies for society are discussed. This review underscores the growing synergy between linguistic theory and technological innovation, offering a roadmap for future research that balances computational sophistication with linguistic nuance.