Artificial Intelligence in Language Teaching: Teachers’ Roles, Identity, and Professional Development: A Systematic Literature Review

Abstract

The accelerating integration of artificial intelligence (AI) into English language education is reshaping teachers’ instructional roles, professional identity, and professional development. Guided by PRISMA 2020 reporting principles, this systematic literature review synthesised 32 peer-reviewed studies published between 2020 and 2025, focusing on instructional roles (n = 28), teacher identity (n = 23), and PD (n = 18). The most common instructional role shifts involve (a) movement from knowledge transmission to learning facilitation, (b) reconfiguration from teacher-only delivery to human–AI pedagogical collaboration, and (c) transition from manual feedback provision to interpreting, validating, and mediating automated feedback, particularly in assessment. Teacher identity findings highlight tensions around professional authority, epistemic legitimacy, and perceived teacher value, often accompanied by insecurity and anxiety, while also documenting identity reconstruction through increased agency, reflective repositioning, and competence-based self-efficacy. PD needs concentrate on (a) assessment and feedback literacy for AI-mediated tasks, (b) ethical and data-privacy literacy, and (c) practical competence in task design and classroom orchestration with intelligent tools. Practically, policymakers should issue operational guidance for ethical use, data protection, and assessment integrity, alongside funding sustained school-based professional learning; teacher education should embed competence-based preparation in pedagogical co-design with AI, responsible use, and reflective identity work.