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Artificial intelligence (AI) can bring immediate and long-term benefits, but also challenges and risks to education systems (UNESCO, 2023). This is a hotly contested topic in English language teaching and learning (ELT/L). With numerous opportunities and hurdles, stakeholder views are critical. The British Council and education technology experts investigate AI’s current and potential use in ELT/L, in a new report. It includes a review of 43 research studies, a global survey of 1,348 English language teachers, and interviews with 19 key witnesses. The main findings, trends, challenges and areas for future research are set out below.

Current trends

Asia leads in AI in ELT research. However, there is a significant gap in peer-reviewed research on AI in adult ELT/L. AI tools are being used to improve speaking, writing and reading skills, however, seem less used for listening skills. They can facilitate practice, and reduce fear of speaking in English (Çakmak, 2022; Chen et al., 2022). Further research could determine if these benefits persist without continued AI use.

AI-powered tools can provide new ways of teaching, and support students in goal setting and self-learning (Kim, 2022; Lee et al., 2023). Despite these advances, traditional lecture-style teaching remains common.

In total, 1,348 teachers from 118 countries/territories were surveyed on how they use AI tools. The most popular tools were language learning apps, language generation AI and chatbots. Teachers reported using them primarily for creating materials, helping students practise English, creating lesson plans and correcting learners’ English. However, 24 per cent reported not using any AI tools, which could indicate a skills gap.

Evidence suggests that ELT is the most common discipline for AI use in education (Crompton & Burke, 2023). Most interviewees agreed AI won’t replace teachers soon, but it’s important to identify which tasks AI can perform. While AI has transformative potential, concerns exist about its compatibility with outdated learning theories.

‘While AI has transformative potential, concerns exist about its compatibility with outdated learning theories.’

Some interviewees felt AI tools could aid accessibility – such as for visually impaired learners – and one suggested that automatic translation tools could aid the less linguistically confident.


While AI in ELT/L is not without challenges, the challenges are underreported in the literature. Technical malfunctions and limited capabilities were key issues. Fear, including concerns about data privacy, fear of the unknown, and fear of losing a natural learning environment (see for example Viktorivna et al., 2022), was another significant challenge. Moreover, by carrying messages about what is considered appropriate and standard language use and disregarding nuances in language groups, AI might reinforce standardised language use (Rowe, 2022).

Evidently, bias needs to be addressed. While regulatory frameworks may help, universal enforcement may be challenging. Teachers also need to develop learners’ ability to critically assess their ‘Al peer’.

Interviewees raised concerns about the influence of large tech companies on classrooms, while recognising the need for grassroots and context-sensitive AI. Other interviewees said a lack of AI proficiency could widen digital divides. Some also warned about increasing datafication.

Future directions

First, we need agreed definitions of AI to ensure a common understanding of the technology. Additionally, we may require domain-specific definitions for Al in ELT. Second, there is a need to review existing ethics guidelines and establish principles for the responsible use of AI in ELT/L. Finally, we need to detail how AI may be used for specific tasks. More research is needed on integrating AI into assessment, and the longer-term impact of specific AI tools on learning.

Many teachers surveyed (54 per cent) feel they haven’t had enough training on using AI. Addressing the existing knowledge gap around digital/AI literacies will be a significant challenge.

In conclusion, while AI currently offers affordances and potential for ELT/L, integration requires careful consideration of various factors.


Çakmak, F. (2022). Chatbot-human interaction and its effects on EFL pupils’ L2 speaking performance and anxiety. Novitas-ROYAL (Research on Youth and Language), 16(2), 113–131.’_L2_Speaking_Performance_and_Anxiety

Chen, C.-H., Koong, C.-S., & Liao, C. (2022). Influences of integrating dynamic assessment into a speech recognition learning design to support pupils’ English speaking skills, learning anxiety and cognitive load. Educational Technology & Society, 25(1), 1–14.

Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: The state of the field. International Journal of Educational Technology in Higher Education, 20, 22 (2023).

Kim, N.-Y. (2022). AI-integrated mobile-assisted language learning: Is it an effective way of preparing for the TOEIC test in classroom environments? English Teaching, 77(3), 79–102.

Lee, D., Kim, H.-H., & Sung, S.-H. (2023). Development research on an AI English learning support system to facilitate learner-generated-context-based learning. Educational Technology Research and Development, 71, 629–666.

Rowe, L. W. (2022). Google Translate and biliterate composing: Second-graders’ use of digital translation tools to support bilingual writing. TESOL Quarterly, 56(3), 883–905.

UNESCO (2023). Ministerial roundtable on generative AI in education.  

Viktorivna, K. L., Oleksandrovych, V. A., Oleksandrivna, K. I., & Oleksandrivna, K. N. (2022). Artificial intelligence in language learning: What are we afraid of? Arab World English Journal (AWEJ) Special Issue on CALL, 8, 262–273.