INCORPORATING AI INTO THE ESP CURRICULUM: TEACHING METHODS AND TECHNIQUES

The integration of Artificial Intelligence (AI) into English for Specific Purposes (ESP) curriculum design represents a paradigm shift in vocational and professional language education. This article examines contemporary teaching methods and empirical techniques for embedding AI technologies within ESP frameworks, specifically focusing on data-driven learning (DDL), automated writing evaluation (AWE), and intelligent tutoring systems (ITS). Utilizing a mixed-methods research framework, the study evaluates the linguistic proficiency, domain-specific lexical acquisition, and professional communicative competence of undergraduate students across technical and medical specializations. Quantitative metrics demonstrate a 24% increase in specialized vocabulary retention and a 31% reduction in syntactical errors when AI-driven diagnostic tools are deployed alongside traditional genre-based pedagogy. Qualitative analysis corroborates heightened learner autonomy and optimized alignment with authentic workplace communication demands. The findings offer a scalable methodology for higher education institutions to modernize ESP curricula, balancing automated precision with pedagogical oversight.