Artificial Intelligence in Higher Education and Psychological Counseling: A Methodological Framework for Implementation

The article substantiates and systematizes approaches to the use of artificial intelligence (AI) technologies in higher professional education as a tool for information and analytical support of individual training, coaching, management activities and psychological counseling. The purpose of the work is to present ways to use AI tools (generative models, intelligent assistants, recommendation systems and intelligent document processing tools) in the educational process and university management while maintaining human responsibility and the requirements of academic ethics. It is shown that the key effect of AI in higher education is the transition from “average” learning to personalized trajectories supported by educational and subject analytics, as well as the formation of new mentoring (coaching) practices based on data. Solutions (analytical recommendation systems; intelligent educational environments; management support systems) are proposed and typical scenarios are described: an AI tutor, a coaching scenario, an analytical dashboard, automation of teacher training, support for psychological counseling (query screening, dialogue simulators). The risks (hallucinations, data bias) and the need for verification by a source specialist are highlighted separately. The practical significance of the work lies in the formation of applicable approaches to the introduction of AI in higher education, focused on improving the quality of education and the manageability of educational processes. The following theoretical methods were used in the development: (1) analysis and synthesis, a systematic approach, comparative analysis, classification, generalization of psychological-pedagogical, organizational and managerial experience in the implementation of AI; (2) information and analytical methods — content analysis of scientific publications and practices of AI application in higher education; analysis of typical application cases (generative assistants, chatbots); (3) methodological modeling — designing a methodological model for the use of AI (levels: training / coaching / management / consulting), description of functions, inputs/outputs and constraints (including requirements for data, validation and ethics); (4) identification of risks and measures to minimize them, verification by sources, regulations for disclosure of the use of AI, data protection. Keywords: artificial intelligence; professional education; analytics; coaching; psychological counseling; pedagogy.

1. Ivanova S.V., Azarkhin A.V. The model of using artificial intelligence in the educational process of universities. Concept. 2025;09:303-317. (In Russ.). URL: https://doi.org/10.24412/2304-120X-2025-11189

2. Davydov S. G., Matveeva N. N., Ademukova N. V., Vichkanova A. A. Artificial intelligence in Russian higher education: current state and development prospects. University management: Practice and Analysis. 2024;28(3):32-44. (In Russ.). URL: https://doi.org/10.15826/umpa.2024.03.023

3. Koroteev M.V., Marunko A. S., Romanova E.V., Chulina N. Yu. Machine learning methods for extracting keywords from educational and official materials. Innovation and Investment. 2025;(7):611-615. (In Russ.). URL: https://elibrary.ru/seinwu

4. Abashin V. G., Zagorodnih N. A., Presnetsova V. Yu. Prospects of using neural networks in the process of improving the management of commercial organizations. Information Systems and Technologies. 2024;142(2):21-27. (In Russ.). URL: https://elibrary.ru/vcaaef

5. Kosarev V. E., Milovidov V. I. On the use of machine learning methods for processing information fl ws of Internet acquiring of a commercial bank. Innovation and Investment. 2025;(1):502-507. (In Russ.). URL: https://elibrary.ru/vttiop

6. Gugadina E. P., Bocharov M. I. Automation of the process of compiling work programs for disciplines using a virtual assistant to work with a neural network. Standards and Monitoring in Education. 2025;13(3):64-69. (In Russ.). URL: https://doi.org/10.12737/1998-1740-2025-13-3-64-69

7. Gobareva Ya.L., Gorodetskaya O.Y. XBRL as a management reporting tool. In the collection: Actual problems of accounting, analysis, control and taxation. Moscow: Rusains; 2025. (In Russ.). URL: https://elibrary.ru/pqtvng

8. Avramenko A. D., Sudakov V.A. The method of generating a training sample for machine learning in the traveling salesman problem. In the collection: Aviation and Cosmonautics. Moscow: Pero Publishing House; 2024. (In Russ.). URL: https://elibrary.ru/pwsykn

9. Khasanov I.I., Khasanova Z.R. The use of machine learning on graphs to build recommendation systems that take into account the individuality of users. Modern High-tech Technologies. 2025;(6):54-61. (In Russ.). URL: https://doi.org/10.17513/snt.40422

10. Zhuravkov A.A., Labintsev A. I. Determination of the dynamic characteristics of a blow in martial arts using recurrent neural networks. In: Neurocomputers and their applications. Moscow: MGPPU; 2022. (In Russ.). URL: https://elibrary.ru/wrfuko

11. Kublik E.I., Labintsev A.I., Chipchagov M.S., Shilov M.A. Improving the effectiveness of advertising campaigns on radio through integration with digital monitoring tools. Humanities. Bulletin of the Financial University. 2023; 13(5):121-128. (In Russ.). URL: https://doi.org/10.26794/2226-7867-2023-13-5-121-128

12. Budaev E.S. Development of a web application for the intelligent analysis of customer reviews using a modified seq2seq model with an attention mechanism. Computational Nanotechnology. 2024;11(1):151-161. (In Russ.). URL: https://doi.org/10.33693/2313-223X-2024-11-1-151-161

13. Zholobova G.N., Sinitsyna E.D. The use of machine learning to analyze employee loyalty based on text reviews. Neurocomputers: Development, Application. 2024;26(6):76-85. (In Russ.). URL: https://elibrary.ru/wminjg

14. Sedykh I.Yu., Khripunova M. B. Artificial intelligence technologies in modern higher education in Russia. Digital solutions and artificial intelligence technologies. 2025;1(1):20-27. (In Russ.). URL: https://www.digitarin. ru/jour/article/view/4/4

15. Salnikov E.A., Muminova S. R. The evolution of artificial intelligence: from modern technologies to future innovations. Digital Solutions and Artifi Intelligence Technologies. 2025;1(2):64-71. (In Russ.). URL: https://www.digitarin.ru/jour/article/view/14/14

16. Kogteva A.N. Promising areas of application of artificial intelligence in the military-industrial complex. Digital Solutions and Artificial Intelligence Technologies. 2025;1(2):58-63. (In Russ.). URL: https://www.digitarin.ru/ jour/article/view/13/13

17. Grigoriev S.M. Higher school teacher in the era of artificial intelligence and digital transformation. Human Сapital. 2026;1(205):40-50. (In Russ.). URL: https://elibrary.ru/wvagfg