A recent survey found that people in the UK associate AI with words like 'robot' and 'worrying' (UK Government, 2024). Perhaps you feel the same. However, for second-language learners, AI offers immense potential when used wisely. In this article, we will explore practical ways to use AI for learning a language, from practising conversations to improving vocabulary, and consider some of the challenges you might face.

Using AI for Conversation Practice

Practising conversations can be difficult, especially for shy learners. AI can simulate conversations, allowing learners to practise speaking or writing without fear of judgement.

Example Prompt:

"Act as a friendly and encouraging English speaker. I am a non-native English learner practicing my conversational skills. Please start by asking me about my day or any general topic. As I respond, kindly provide corrections for any grammar or vocabulary mistakes I make. Ensure your corrections are clear, constructive, and include explanations when needed. Keep the tone supportive and engaging to help me build confidence."

AI models can generate realistic dialogues, helping learners build confidence. Research shows that role-playing through AI-driven models provides both meaningful practice and a judgement-free space (Hu et al., 2025). This builds fluency by copying real-life interactions.

AI also allows learners to practise specific situations, such as ordering food in a restaurant or asking for directions. This targeted practice can make learners more confident when they face similar situations in real life. Furthermore, learners can adjust the difficulty level of the conversation to match their progress, making the tool adaptable for continuous improvement.

Enhancing Grammar and Vocabulary Building

AI is very good at offering personalised explanations for grammar and vocabulary. By asking specific questions, learners can receive tailored exercises or examples to strengthen their knowledge.

Example Prompt:

"Explain the difference between the words 'since' and 'for' when referring to time. Provide a clear and concise explanation suitable for a learner of English. Include five simple, grammatically correct example sentences for each word, emphasizing their typical usage in time-related contexts."

Studies highlight that learners benefit from targeted feedback, as it helps them understand subtle nuances (Liu & Yen, 2025). Additionally, tools like vocabulary tests generated by AI can help learners remember words better by including wrong answers and tasks suited to their level.

Beyond testing, AI can also recommend new vocabulary based on your interests. For instance, if a learner is keen on sports, they could use AI to ask for new words related to the topic, such as 'goalkeeper,' 'penalty,' or 'offside.' These personalised suggestions keep the learning process relevant and engaging.

Gamification and Engagement

Keeping yourself engaged is crucial, and AI can make learning feel like a game. Gamification means turning tasks into games to make learning fun and engaging (OED, 2024). AI can create challenges, quizzes, or puzzles based on your learning goals.

Example Prompt:

"Create an engaging quiz for matching idioms with their meanings. The quiz should include at least five idioms, such as 'break the ice,' 'spill the beans,' and 'burn the midnight oil.' For each idiom, provide four multiple-choice options, where only one is correct. Use varied and relatable contexts to make the quiz fun and educational. At the end of the quiz, include a short explanation of each idiom and its usage for further learning."

Gamified tasks help keep learners interested by making activities fun and competitive. This approach not only aids in vocabulary acquisition but also increases learners’ willingness to engage regularly.

Additionally, AI can introduce creative tasks, such as translating a song or solving riddles in the target language. These activities combine learning with entertainment, helping to sustain motivation over time. For younger learners, interactive games or story-based activities created by AI can make language learning feel like play rather than study.

Limitations and Challenges

While AI offers many benefits, it is important to recognise its potential challenges alongside these advantages. One common challenge is accuracy. AI can sometimes produce incorrect or biased outputs. For instance, grammar explanations may oversimplify complex rules, or cultural contexts might be misrepresented (Liu & Yen, 2025). It is important to always double-check AI-generated responses with trusted sources. Another issue is the lack of human touch. AI does not have emotional intelligence or the cultural knowledge that a native speaker or experienced teacher can offer (Hu et al., 2025). Over-reliance is another concern. Using AI too much might stop learners from exploring other methods of learning or engaging with native speakers. Finally, AI can struggle with understanding deeper context or sarcasm. This limitation may result in less meaningful practice. For example, if a learner discusses complex emotions or idiomatic expressions, the AI might give incomplete or incorrect responses. To address these challenges, learners should balance AI tools with traditional learning methods, like working with teachers or practising in real-life situations.

Conclusion

Using AI for language learning offers exciting opportunities, from personalised conversation practice to engaging vocabulary exercises. However, learners should remain cautious about its limitations and use it alongside other methods, such as taking online lessons with professional teachers on italki, and engaging with other learners and native speakers. With a balanced approach, AI can become a powerful ally in your language-learning journey.

Remember, language learning is a gradual process that benefits from consistency and variety. Stay motivated, embrace challenges, and celebrate every small achievement along the way. Whether through AI, human interaction, or both, persistence is key to achieving fluency.

References

Hu, L., Zhang, X., Song, D., Zhou, C., He, H., Nie, L., & others (2025). ‘Efficient and Effective Role Player: A Compact Knowledge-grounded Persona-based Dialogue Model Enhanced by LLM Distillation’, ACM Transactions on Information Systems. Available at: https://doi.org/10.1145/3711857

Liu, Y.-C., Yen, A.-Z., & others (2025). ‘ISSR: Iterative Selection with Self-Review for Vocabulary Test Distractor Generation’. Available at: https://arxiv.org/abs/2501.03462

OED (2024). Gamification. Oxford English Dictionary. Available at: https://www.oed.com/dictionary/gamification_n?tab=meaning_and_use#1259512960.

UK Government (2024). Public Attitudes to Data and AI Tracker Survey: Wave 4 Report. Available at: https://www.gov.uk/government/publications/public-attitudes-to-data-and-ai-tracker-survey-wave-4/public-attitudes-to-data-and-ai-tracker-survey-wave-4-report.