Exploring the Impact of Artificial Intelligence on Language Acquisition, Linguistic Development, and Language Use: A Case Study from India

Artificial Intelligence (AI) significantly contributes to linguistic development in the contemporary scenario. Although the presence of AI is evident in language teaching, studies related to its role in building Teacher-Student Rapport (TSR), Teacher Immediacy (TI) and Willingness to Communicate (WTC) are scarce. This study explores how teacher-student rapport and students’ attitudes towards artificial intelligence intersect in a technology driven world. It sheds light on strategies to enhance engagement and motivation in language education. By integrating insights from existing research, this inquiry seeks to investigate the role of AI in fostering TSR, TI and WTC. Thus, it reveals the complex relationships between these variables and bridges the existing research gap. Data were collected from 50 ESL teachers and 165 ESL students in higher education institutions in two different south Indian states namely Tamil Nadu and Kerala. Moreover, data obtained through in-depth interviews with teachers who are trained to use AI for English language teaching are also analyzed in this study. The questionnaire’s internal consistency and reliability were rigorously tested using Cronbach’s alpha coefficient. The collected data underwent a comprehensive analysis, incorporating a range of techniques: a five-point Likert scale to gauge attitudes, percentage calculations for quantitative insights, graphical representations for visual clarity, flowcharts to illustrate processes, and descriptive analysis to contextualize the findings. The result of the study shows that AI plays a pivotal role in enhancing TSR, TI and WTC. It also highlights the significance of human interaction and feedback in language teaching, due to language’s ambiguous nature. © 2025 Elsevier B.V., All rights reserved.