Matrix of technical solutions based on artificial intelligence in the professional training of future lawyers

Importance. The current stage of technological development of society is characterized by the intensive integration of artificial intelligence (AI) technologies into professional spheres. AI-based technical solutions make it possible to automate some routine processes and free up time for humans to solve other more important and complex issues. Gradually, the interaction of specialistswith AI tools to solve professional problems is becoming a daily practice. In this regard, the training of qualified personnel at the university for the realities of today is impossible without integrating professionally oriented AI tools into the student learning process. Law is one of the activity fields in which modern AI technologies are able to take on many professional tasks. At the same time, the systematic integration of AI-based technical solutions into the university’s law student training process is impossible without a comprehensive study of the entire range of AI tools and their professionally oriented potential. The purpose of the work is to develop a matrix of AI-based technical solutions used in the professional training of future lawyers.

Materials and Methods. The study is conducted on the expert assessment method basis. This allowed the authors to: a) identify a list of professional tasks solved by lawyers in the field of professional activity; b) based on the identified tasks, develop a matrix of AI-based technical solutions used in the professional training of future lawyers. The materials are scientific papers on pedagogy, methods of teaching foreign languages and specialized disciplines, published in scientific journals indexed in the Ministry of National Security (Scopus and Web of Science), as well as those included in the list of the Higher Attestation Commission of the Russian Federation (K1, K2), the Federal State Educational Standard for Higher Education in the field of Law. The AI tools widely used among current lawyers, which they use in their professional activities to solve professional problems, are used as practical materials.

Results and Discussion. A matrix of AI-based technical solutions used in the professional training of future lawyers has been developed. The matrix is presented according to twelve professional tasks that lawyers solve in the course of their professional activities. The main and most accessible AI-based technical solutions for teachers of specialized disciplines that can help lawyers solve professional problems are the following: Legal AI tools, Legal Document Generator and DocZilla AI are used to draw up contracts (lease, sale, employment agreements, etc.), DocZilla AI and Genie AI – for the analysis and comparison of document editions, Mistral AI and LexisNexis – for checking documents for errors and contradictions, ROSS Intelligence and WestLaw – to search for relevant court decisions and analyze use cases, TrademarkVision and PatentPal – to search for similar trademarks, Perplexity AI – to analyze license agreements, Legalese Decoder, ChatGPT, YandexGPT, GigaChat and DeepSeek – to simplify legal terms for clients (colleagues, students), Canva and MidJourney – to visualize processes (for example, judicial meetings), LegalAI and Jasper AI – for legal advice, Perplexity AI, ChatGPT, YandexGPT, GigaChat and DeepSeek – for mathematical calculations (taxes, insurance payments, etc.), MidJourney – to create images of suspects, Legalese Decoder and Mistral AI are used for conducting examinations (handwriting, ballistic, etc.).

Conclusion. The research novelty is the development of a matrix of AI-based technical solutions used in the professional training of future lawyers. The perspective of the conducted research lies in the development of step-by-step methods of teaching aspects of specialized disciplines based on the students’practice with specific technical solutions based on AI.

1. Ivakhnenko E.N., Nikol’skii V.S. (2023). ChatGPT in higher education and science: a threat or a valuable resource? Vysshee obrazovanie v Rossii = Higher Education in Russia, vol. 32, no. 4, pp. 9-22. (In Russ.) https://doi.org/10.31992/0869-3617-2023-32-4-9-22, https://elibrary.ru/tzhihu

2. Robert I.V. (2024). Implementation of artificial intelligence capabilities in education. Prostranstvo pedagogicheskikh issledovanii = Education Research Environment, no. 1 (1), pp. 60-75. (In Russ.) https://doi.org/10.23859/3034-1760.2024.77.66.004, https://elibrary.ru/neeext

3. Sysoyev P.V. (2023). Artificial intelligence in education: awareness, readiness and practice of using artificial intelligence technologies in professional activities by university faculty. Vysshee obrazovanie v Rossii =Higher Education in Russia, vol. 32, no. 10, pp. 9-33. (In Russ.) https://doi.org/10.31992/0869-3617-2023-32-10-9-33, https://elibrary.ru/tzytkm

4. Kazakova E.I., Kuz’minov Ya.I. (2025). “We should foster a culture of critical attitude towards artificial intelligence”. Elena Kazakova and Yaroslav Kuzminov discuss the challenges facing the education system. Voprosy obrazovaniya = Educational Studies Moscow, no. 1, pp. 8-24. (In Russ.)https://doi.org/10.17323/vo-2025-25882, https://elibrary.ru/fmenzj

5. Cotton D.R.E., Cotton P.A., Shipway J.R. (2023). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, pp. 1-12. https://doi.org/10.1080/14703297.2023.2190148

6. Sysoyev P.V. (2024). Ethics and AI-plagiarism in an academic environment: students’ understanding of compliance with author’s ethics and the problem of plagiarism in the process of interaction with generative artificial intelligence. Vysshee obrazovanie v Rossii = Higher Education in Russia, vol. 33, no. 2, pp. 31-53. (In Russ.) https://doi.org/10.31992/0869-3617-2024-33-2-31-53, https://elibrary.ru/vtaiuo

7. Evstigneev M.N. (2025). Learner’s autonomy in the context of the artificial intelligence technologies development and spread in language education. Inostrannye yazyki v shkole = Foreign Languages at School, no. 2, pp. 13-21. (In Russ.) https://elibrary.ru/artmrn

8. Sysoyev P.V. (2025). Personalized learning based on artificial intelligence: how ready are modern students for new educational opportunities. Vysshee obrazovanie v Rossii = Higher Education in Russia, vol. 34, no. 2, pp. 51-71. (In Russ.) https://doi.org/10.31992/0869-3617-2025-34-2-51-71, https://elibrary.ru/weagvq

9. Titova S.V., Temuryan K.T. (2024). Intelligent learning system for language teaching: types, structure, design principles. Inostrannyeyazyki v shkole = Foreign Languages at School, no. 3, pp. 25-32. (In Russ.) https://elibrary.ru/svcmqy

10. Sysoyev P.V., Filatov E.M. (2023). ChatGPT in students’ research: to forbid or to teach? Vestnik Tambovskogo universiteta. Seriya: Gumanitarnye nauki = Tambov University Review: Series Humanities, vol. 28, no. 2, pp. 276-301. (In Russ.) https://doi.org/10.20310/1810-0201-2023-28-2-276-301, https://elibrary.ru/sphxkz

11. Sysoyev P.V., Evstigneev M.N. (2025). The use of artificial intelligence technologies in the students’ research work. Vestnik Moskovskogo universiteta. Seriya 19: Lingvistika i mezhkul’turnaya kommunikatsiya = Moscow State University Bulletin. Series 19. Linguistics and Intercultural Communication, vol. 28, no. 1, pp. 85-101. (In Russ.) https://doi.org/10.55959/MSU-2074-1588-19-28-1-6, https://elibrary.ru/aynwsu

12. Mikhaleva O.V. (2024). Artificial intelligence in the system of modern education: prospects and risks. Pedagogicheskaya informatika = Pedagogical Informatics, no. 2, pp. 193-199. (In Russ.) https://elibrary.ru/diegma

13. Hendrycks D., Mazeika M., Woodside T. (2023). An Overview of Catastrophic AI Risks. 54 p. https://doi.org/10.48550/arXiv.2306.12001

14. Itinson K.S. (2020). Informatization of medical education: artificial intelligence systems in the education of students and doctors. Baltiiskii gumanitarnyi zhurnal = Baltic Humanitarian Journal, vol. 9, no. 3 (32), pp. 91-93. (In Russ.) https://doi.org/10.26140/bgz3-2020-0903-0021, https://elibrary.ru/jfcjma

15. Chan K., Zary N. (2019). Applications and challenges of implementing artificial intelligence in medical education: integrative review. JMIR Medical Education, vol. 5, no. 1, art. 13930. https://doi.org/10.2196/13930

16. Zhang W., Cai M., Lee H., Evans R., Zhu C., Ming C. (2024). AI in medical education: global situation, effects and challenges. Education and Information Technologies, vol. 29, pp. 4611-4633. https://doi.org/10.1007/s10639-023-12009-8, https://elibrary.ru/rdfanm

17. Waisberg N., Hudek A. (2021). AI for Lawyers: How Artificial Intelligence is Adding Value, Amplifying Expertise, and Transforming Careers. Hoboken, Wiley, 208 p.

18. Sysoyev P.V., Kharin V.V., Gavrilov M.V. (2024). Method of teaching law students to draft international legal documents based on artificial intelligence tools as part of an integrated course. Yazyk i kul’tura = Language and Culture, no. 67, pp. 272-289. (In Russ.) https://doi.org/10.17223/19996195/67/15, https://elibrary.ru/rfqxpk

19. Aleinikova D.V. (2022). Features of teaching lawyers argumentative discourse in the context of digitalization. Vestnik Moskovskogo gosudarstvennogo lingvisticheskogo universiteta. Obrazovanie i pedagogicheskienauki = Vestnik of Moscow State Linguistic University. Humanities, no. 2 (843), pp. 14-19. (In Russ.) https://doi.org/10.52070/2500-3488_2022_2_843_14, https://elibrary.ru/lzbest

20. Levin B.A., Piskunov A.A., Polyakov V.Yu., Savin A.V. (2022). Artificial intelligence in engineering education. Vysshee obrazovanie v Rossii = Higher Education in Russia, vol. 31, no. 7, pp. 79-95. (In Russ.) https://doi.org/10.31992/0869-3617-2022-31-7-79-95, https://elibrary.ru/kcnapj

21. Parshina K.V., Saltykova G.M. (2021). Modern technology in teaching students the direction of “Design” training. Pedagogicheskii zhurnal = Pedagogical Journal, vol. 11, no. 1-1, pp. 263-270. (In Russ.) https://doi.org/10.34670/AR.2021.47.77.032, https://elibrary.ru/scqdmg

22. Kharlamenko I.V. (2025). Augmented reality in teaching vocabulary in a foreign language. Inostrannye yazyki v shkole = Foreign Languages at School, no. 2, pp. 27-32. (In Russ.) https://elibrary.ru/xlqhly

23. Klochikhin V.V. (2020). Stages of students’ collocation competence development based on linguistic corpus. Vestnik Tambovskogo universiteta. Seriya: Gumanitarnye nauki = Tambov University Review: Series Humanities, vol. 25, no. 186, pp. 14-24. https://doi.org/10.20310/1810-0201-2020-25-186-14-24, https://elibrary.ru/mqddog

24. Klochikhin V.V., Polyakov O.G. (2023). Artificial intelligence technologies: corpus analysis tools in foreign language teaching. Inostrannye yazyki v shkole = Foreign Languages at School, no. 3, pp. 24-30. (In Russ.) https://elibrary.ru/bdttfe

25. Sysoyev P.V., Ivchenko M.I. (2025). Development of learners’ foreign language pronunciation skills on the basis of artificial intelligence tools. Perspektivy nauki i obrazovaniya = Perspectives of Science and Education, no. 2, pp. 600-614. (In Russ.) https://doi.org/10.32744/pse.2025.2.38, https://elibrary.ru/jrddjj

26. Ivchenko M.I., Polyakov O.G. (2025). Using the ELSA speak AI tool in pronunciation teaching and learning. Inostrannye yazyki v shkole = Foreign Languages at School, no. 2, pp. 54-58. (In Russ.) https://elibrary.ru/zrvafq

27. Sysoyev P.V., Filatov E.M. (2024). Method of teaching students’ foreign language creative writing based on evaluative feedback from artificial intelligence. Perspektivy nauki i obrazovaniya = Perspectives of Science and Education, no. 1 (67), pp. 115-135. (In Russ.) https://doi.org/10.32744/pse.2024.1.6, https://elibrary.ru/tmstly

28. Sysoyev P.V., Filatov E.M., Khmarenko N.I., Murunov S.S. (2024). Teacher vs artificial intelligence: a comparison of the quality of feedback provided by a teacher and generative artificial intelligence in assessing students’ creative writing. Perspektivy nauki i obrazovaniya = Perspectives of Science and Education, no. 5 (71), pp. 694-712. (In Russ.) https://doi.org/10.32744/pse.2024.5.41, https://elibrary.ru/xzgvgm

29. Korenev A.A. (2024). Strategies of using artificial intelligence for written corrective feedback in language education. Vestnik Moskovskogo universiteta. Seriya 19. Lingvistika I mezhkul’turnaya kommunikatsiya = Moscow State University Bulletin. Series 19. Linguistics and Intercultural Communication, no. 2, pp. 68-77. (In Russ.) https://doi.org/10.55959/MSU-2074-1588-19-27-2-5, https://elibrary.ru/hizddu

30. Sysoyev P.V., Filatov E.M. (2023). Method of the development of students’ foreign language communication skills based on practice with a chatbot. Perspektivy nauki i obrazovaniya = Perspectives of Science and Education, no. 3 (63), pp. 201-218. (In Russ.) https://doi.org/10.32744/pse.2023.3.13, https://elibrary.ru/fjyhew

31. Sorokin D.O. (2024). The use of voice assistants for the development of foreign language oral communication skills. Inostrannye yazyki v shkole = Foreign Languages at School, no. 3, pp. 73-77. (In Russ.)https://elibrary.ru/rfmsmk

32. Sorokin D.O. (2025). Theuse of Character.AI web application for the development of learners’ foreign language communication skills. Inostrannye yazyki v shkole = Foreign Languages at School, no. 2, pp. 59-65. (In Russ.) https://elibrary.ru/kpckof

33. Filatov E.M. (2024). Development of students’ foreign language communicative skills based on the Character.AI web application. Vestnik Tambovskogo universiteta. Seriya: Gumanitarnye nauki = Tambov University Review: Series Humanities, vol. 29, no. 5, pp. 1248-1260. (In Russ.) https://doi.org/10.20310/1810-0201-2024-29-5-1248-1260, https://elibrary.ru/ncusck

34. Sysoyev P.V., Filatov E.M., Evstigneev M.N., Polyakov O.G., Evstigneeva I.A., Sorokin D.O. (2024). A matrix of artificial intelligence tools in pre-service foreign language teacher training. Vestnik Tambovskogo universiteta. Seriya: Gumanitarnye nauki = Tambov University Review: Series Humanities, vol. 29, no. 3, pp. 559-588. (In Russ.) https://doi.org/10.20310/1810-0201-2024-29-3-559-588, https://elibrary.ru/jazkme

35. Sysoyev P.V., Filatov E.M., Sorokin D.O. (2024). Feedback in foreign language teaching: from information technologies to artificial intelligence. Yazyk i kul’tura = Language and Culture, no. 65, pp. 242-261. (In Russ.) https://doi.org/10.17223/19996195/65/11, https://elibrary.ru/plzyov

36. Sysoyev P.V., Evstigneev M.N. (2025). Integration of artificial intelligence technologies in language and methodological pre-service teachers’ training. Yazyk i kul’tura = Language and Culture, no. 69, pp. 204- 219. (In Russ.) https://doi.org/10.17223/19996195/69/10, https://elibrary.ru/guzvbi.