Zhou Bo

his study conducts a bibliometric analysis of Artificial Intelligence (AI) in English education, employing co-citation and co-occurrence analyses to investigate significant research trends, theoretical frameworks, and interdisciplinary connections. The analysis delineates four primary research clusters: AI-assisted language acquisition, ChatGPT in educational methodologies, AI chatbots for English as a Foreign Language (EFL) students, and AI-facilitated student engagement. The co-citation analysis identifies pivotal studies that influence the intellectual framework of the field, whereas the co-occurrence analysis underscores thematic trends and research deficiencies. This study enhances the Technology Acceptance Model (TAM) by integrating pedagogical and ethical aspects, illustrating the interaction between perceived ease of use, usefulness, policy frameworks, teacher readiness, and AI implementation in education. Notwithstanding AI’s transformative potential, challenges persist, encompassing data privacy issues, algorithmic bias, ethical dilemmas, and the necessity for interdisciplinary collaboration. To connect AI with sustainable and equitable education, future research has to investigate the long-term adoption of AI, geographic disparities, and strategies for effective pedagogical integration. This study presents a framework for the ethical, effective, and interdisciplinary integration of AI in English education by promoting collaboration among educators, AI researchers, and policymakers.