Author’s note: This discussion is part of a recent publication, Vanishing Voices, that reflects on critical topics related to language learning in education abroad. Vanishing Voices is an international project that emerged from a professional seminar designed and organized by the Spanish Institute for Global Education, held in Seville, Spain, October 12–15, 2025. The publication is available to order from Star Scholars Press and from Amazon, including Amazon Spain.
What AI Does for Language Learners
With technological innovation – particularly one as powerful as AI – comes both promise and peril. AI brings increased access and personalization to language learning but threatens to flatten cultural identity through overreliance on standardization.
AI can literally bring a tutor to every phone, expanding individual opportunities for learning at under-resourced institutions and enhancing instructional capacity for less commonly taught languages. The on-demand nature of instruction can fit into the schedules and lifestyles (and even attention spans) of modern learners, while adaptive systems allow vocabulary or conversational scenarios to be personalized based on past mistakes and future needs.
Pronunciation feedback can be precise and immediate, while the ability to practice privately has been shown to reduce anxiety for language students. That reduction of anxiety and emphasis on relevance over repetition can yield positive impacts on student persistence as well as their perception of – and confidence during – language learning.
This individualized experience combined with unprecedented scalability brings promise for language learning but not without peril.
When Algorithms Flatten Language
Standardization comes with a price. When AI draws upon large language models, the technology defers to – or privileges – those that are most likely and thus most popular. Whilst there is opportunity to select different regional varieties (e.g. Latin American over Castilian Spanish), there is an operational bias towards what are perceived as the more ‘elite’ or ‘proper’ forms of a language (Lewis, 2025).
AI default languages erase the linguistic nuances and cultural context of regional dialects as well as heritage language learners. Words and phrases fall away, as do the history and understanding to explain why they were incorporated and are used. This is not just an academic exercise. Students will find identical phrases have different meanings based on location. They simply do not know what they do not know.
Additional nuances include level of formality, understanding of power dynamics, and incorporation of silence and non-verbal cues. Whilst there are AI videos to assist, the likelihood for misunderstanding is amplified through reliance on technology alone.
Beyond neutral outputs that miss ambiguity and nuance, there is a concern that learners – particularly in the digital generation – will default to technological enhancement over human interaction. Using AI as a crutch might be convenient and safe but avoiding discomfort and limiting risk can impede the learning process. True language acquisition happens through ‘productive struggle’ – the communication breakdowns and vulnerability that AI too readily smooths away.
Practical Strategies for Educators
Language educators should focus on AI for preparation and humans for guiding transformation. Teachers can adopt a consistent teaching framework that integrates AI tools for language learners. For example, after introducing a linguistic concept, they might share AI prompts to help students generate personalized exercises for review. Or, as a standard practice, they could guide students in use of AI to develop targeted word lists to help expand their vocabulary for a research paper. These repeated practices will also assist students in recognizing when to engage with AI and how to prepare appropriately.
The key is for educators to set the tone and provide clear frameworks on when technology should be used. A framework might spell out that emergency situations warrant translation support and transactional practice benefits from occasional AI scaffolding; but host family conversations, classroom participation, and social interactions should remain unmediated.
Whilst using AI tools, language educators can still emphasize the human connection. For example, a class assignment could ask students to use AI to create a vocabulary list and a summary of skills needed for their specific career field. Students can take greater ownership of the language related to their future careers by presenting the core elements of their fields and sharing key vocabulary with classmates. This approach brings AI engagement back to a personal level, allowing students to teach each other in an AI-free setting.
Learning a language, with or without AI, can cause feelings of discomfort and failure. Language learners can build critical AI literacy as a part of intercultural competence. Students should question which dialects their AI tools recognize as ‘correct’ and critically assess the assumptions made by their AI tools. In these ways, students can build confidence in their own skills and improve their intercultural understanding by learning to recognize the biases in AI tools and share their insights with classmates or peers.
AI as Tool, Not Teacher
Does AI help or hinder language learning? The answer depends on pedagogical intentionality.
AI can help as a supplemental, scaffolded practice to build confidence leading to or enhancing meaningful human interaction and authentic cultural context. AI can hinder learning when it is the full extent of the interaction and context, merely transactional and surface level or stand-alone.
Technology can flatten out the differences and depth that make multilingual education transformative. Educators must embrace the full range of linguistic identities and include AI literacy within language learning.
The goal is not producing students who speak ‘perfect’, standardized language mediated by AI, but encouraging learners who are able to navigate linguistic diversity with humanity and humility.
AI is a powerful tool but not the only teacher. Student success means learning to use AI to facilitate momentum towards a multilingual identity.
