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Artificial intelligence is becoming an increasingly integral part of the educational process in the contemporary world, particularly in the realm of foreign language learning. Recent systematic reviews present artificial intelligence as offering innovative teaching tools, such as chatbots, adaptive platforms, and biometric feedback, to personalize learning and enhance its efficiency. The article presents a summary of the main findings for the period 2024-2025, discussing such aspects as benefits, challenges, and future directions of AI in language education (Zheng & Yang, 2024), (Zhu & Wang, 2025).

Research confirms the rapid development of AI technologies in foreign language learning. Among the main trends is the use of chatbots based on AI, such as Chat GPT, for improvement in speaking, writing, and grammar competencies. Such a systematic review of 24 studies showed that chatbots reduce anxiety when speaking and improve performance in EFL. Other technologies include ITS, automated feedback systems, and mobile applications with generative artificial intelligence that can adjust materials to the student's level of understanding (Du & Daniel, 2024).

Within the framework of activity theory, chatbots are integrated into learning systems to promote cognitive, emotional, and behavioural outcomes. Recent research states that AI enhances cognitive skills, such as communicative competence, in 48% of cases and influences students' emotions, including motivation, in 38% of cases. Heart rate and eye movement data are also utilized by biometric feedback platforms, such as Smart Sparrow, to adapt reading materials, ultimately leading to increased comprehension and reduced anxiety (Li, Zhou, Yin & Chiu, 2025), (Yuan, 2025).

Trends also include mobile applications that apply generative AI to improve student self-efficacy. Participants using AI features with Duolingo reported a perceived increase in confidence using the language in real-life situations after a month, with the figures ranging between 61% and 79%. In general, research targets higher education (65%), as well as writing and speaking competencies, with a focus on data and machine learning for personalization (Kittredge, Hopman, Reuveni, Dionne, Freeman & Jiang, 2025), (Feng, 2025).

AI has distinct advantages in enhancing learning results. For instance, learning with artificial intelligence methods diminishes cognitive load and improves EFL outcomes. In a study involving 484 students, an experiment demonstrated that personal feedback and adaptation within learning led to enhanced results. The integration of chatbots, such as Chat GPT, increases motivation through instant feedback and cultural insights, thereby making the interaction more engaging, (Karataş, Abedi, Ozek Gunyel, Karadeniz & Kuzgun, 2024).

For future teachers, AI can aid in learning English as a second language, improve pronunciation, for instance, through Elsa Speak applications, and enhance cultural understanding. A systematic review drew attention to the importance of personalization in pinpointing knowledge gaps, and reading biometric feedback increased comprehension by 12.4 points while reducing anxiety in a group of 300 EFL learners. Overall, artificial intelligence promotes engagement more effectively, reduces anxiety, and increases the potential for transferring learned skills into real-life contexts (Peña-Acuña & Corga Frenandes, 2024), (Kittredge, Hopman, Reuveni, Dionne, Freeman & Jiang, 2025).

Despite the various advantages, artificial intelligence also poses challenges - the over-dependency on AI results in skill deterioration and plagiarism. Additionally, technical issues such as connection failure or poor audio quality can also pose obstacles. Lack of early empirical effects, limited human-computer interactions, and advantages over disadvantages are also noted in different research studies (Zheng & Yang, 2024). Some ethical controversies, such as data privacy in biometric systems, require attention. AI is also not very effective in deep communication and collaboration, which hampers its development of basic skills (Yuan, 2025).

Research suggests that strengthening interdisciplinary communication in areas such as computer science and linguistics can help better understand personalization. Long-term and classroom studies are needed to assess the impact of AI and its integration with teachers in achieving a balance (Zhu & Wang, 2025).

Artificial intelligence is revolutionizing foreign language learning through personalized, practical tools that improve motivation and bring better results. However, reaching full potential requires addressing such challenges as dependency and accessibility. With further research, AI plays a vital role in paving the way for inclusive and effective language education.

References

Du, J., & Daniel, B. K. (2024). Transforming language education: A systematic review of AI-powered chatbots for English as a foreign language speaking practice. Computers and Education: Artificial Intelligence, 6, 100230.

Feng, L. (2025). Investigating the effects of artificial intelligence-assisted language learning strategies on cognitive load and learning outcomes: a comparative study. Journal of Educational Computing Research, 62(8), 1741-1774.

Karataş, F., Abedi, F. Y., Ozek Gunyel, F., Karadeniz, D., & Kuzgun, Y. (2024). Incorporating AI in foreign language education: An investigation into ChatGPT’s effect on foreign language learners. Education and Information Technologies, 29(15), 19343-19366.

Kittredge, A. K., Hopman, E. W., Reuveni, B., Dionne, D., Freeman, C., & Jiang, X. (2025, February). Mobile language app learners’ self-efficacy increases after using generative AI. In Frontiers in Education (Vol. 10, p. 1499497). Frontiers Media SA.

Li, Y., Zhou, X., Yin, H. B., & Chiu, T. K. (2025). Design language learning with artificial intelligence (AI) chatbots based on activity theory from a systematic review. Smart Learning Environments, 12(1), 24.

Peña-Acuña, B., & Corga Fernandes Durão, R. (2024, November). Learning English as a second language with artificial intelligence for prospective teachers: a systematic review. In Frontiers in education (Vol. 9, p. 1490067). Frontiers Media SA.

Yuan, H. (2025). Artificial intelligence in language learning: biometric feedback and adaptive reading for improved comprehension and reduced anxiety. Humanities and Social Sciences Communications, 12(1), 1-16.

Zheng, L., & Yang, Y. (2024). Research perspectives and trends in artificial intelligence-enhanced language education: A review. Heliyon, 10(19).