Career Trajectories of Graduates of Educational Programs in the Field of Artificial Intelligence: Results of a Qualitative Study of a Regional University

This article examines the training of specialists in the field of artificial intelligence (AI) by universities based on an analysis of the initial career trajectories of graduates of specialized master’s educational programs in the field of artificial intelligence. The relevance of the study is determined by the priority importance of human resources for the development of AI technologies. The scientific novelty of the study is determined by its object: using the method of in-depth interviews, the authors analyzed the effectiveness of training personnel for the field of AI. The objective of the study is to identify the main barriers to employment of graduates of the specialized educational program in AI in the field of their education using the example of a regional university. The empirical base of the study is transcripts of interviews with graduates of master’s educational programs in the field of artificial intelligence, graduating in 2024 and 2025 (N = 25) and transcripts of focus groups with undergraduate (N = 2) and master’s (N = 2) students of the same program. In addition, the curricula and syllabi of the disciplines of the analyzed educational programs are considered. The study revealed that 7 out of 25 graduates (28%) are employed in their field of study. This is primarily influenced by a lack of relevant experience and practical skills; employment in the IT field of interest at the time of enrollment in master’s program; and a lack of initial interest in working with AI technologies. A more detailed analysis of these factors revealed that half of the graduates viewed enrollment in a master’s program as a continuation of their bachelor’s degree, while only 15 out of 25 identified an educational program with AI technologies. Respondents also noted the educational programs’ insufficient practical focus. Among well-known factors contributing to employment in their field of study, such as gaining practical experience with AI during training, a graduate’s professional identity as a researcher significantly influences employment in the AI field. The practical significance of the work lies in the formation of recommendations based on the obtained results that contribute to the modernization of existing practices in domestic higher education in the field of AI.

1. Phelps, E.S. (2013). Mass Flourishing: How Grassroots Innovation Created Jobs, Challenge, and Change. Princeton, N.J: Princeton University Press, 392 p. ISBN: 978-0691158983.

2. Furman, J.L., Porter, M.E., Stern, S. (2002). The Determinants of National Innovative Capacity. Research Policy. Vol. 31, no. 6, pp. 899-933, doi: 10.1016/S0048-7333(01)00152-4.

3. Averyanov, А.О., Gurtov, V.A., Stepus, I.S. (2025). Employment og Graduates of Educational Programs in the Field of Artificial Intelligence. Universitetskoye upravleniye: praktika i analiz = University Management: Practice and Analysis. Vol. 29, no. 4, pp. 56-73, doi: 10.15826/umpa.2025.04.031 (In Russ., abstract in Eng.).

4. Shugal, N.B., Varlamova, T.A. (2024) Podgotovka vysokokvalifitsirovannykh kadrov v oblasti iskusstvennogo intellekta [Training Highly Qualified Personnel in the Field of Artificial Intelligence]. Moscow: HSE Publishing House, 60 p., doi: 10.17323/978-5-7598-3024-5 (In Russ.).

5. Gimpelson, V. (2004). Shortage of Skills in the Labor Market: Limited Supply, Lack of Demand, or False Signals from Employers? Voprosy ekonomiki = Economic issues. Vol. 3, pp. 76-94, doi: 10.32609/0042-8736-2004-3-76-94 (In Russ., abstract in Eng.).

6. Laykam, K.E., Zainullina, Z.Zh., Matraeva, L.V., Vasiutina, E.S., Korolkova, N.A. (2023). Entry into the Russian Labor Market of Graduates of Professional and Higher Educational Institutions (Based on Sample Surveys). Voprosy statistiki = Questions of statistics. Vol. 30, no. 1, pp. 5-17, doi: 10.34023/2313-6383-2023-30-1-5-17 (In Russ., abstract in Eng.).

7. Wang, B., Liang, K., Yuan, F. (2025). [Research on Strategies for Enhancing the Employment Competitiveness of Computer Science Graduates under the School Enterprise Cooperation Model]. In: Computer Science and Educational Informatization: 6th International Conference, CSEI 2024, Haikou, China, November 1–3, 2024, Revised Selected Papers, Part I. Springer, Singapore. Article no. 2447, pp. 103-110, doi: 10.1007/978-981-96-3735-5.

8. Kiss, Z. (2024). Vertical and Horizontal (Mis)Match of University Degrees in the Hungarian Labour Market. Humanities and Social Sciences Communications. Vol. 11, article no. 1699, doi: 10.1057/s41599-024-04203-x.

9. Assaad, R., Krafft, C., Salehi-Isfahani, D. (2018). Does the Type of Higher Education Affect Labor Market Outcomes? Evidence from Egypt and Jordan. High Educ (Dordr). Vol. 75, no. 6, pp. 945-995, doi: 10.1007/s10734-017-0179-0.

10. Marois, G., Potančokova, M., Bezat, A., Cuaresma, J.C. (2026). Projecting Labour Market Imbalances and Skill Mismatch Under Demographic Change in the EU. European Journal of Population. Vol. 42, article no. 4, doi: 10.1007/s10680-025-09758-2.

11. Salas-Velasco, M. (2021). Mapping the (Mis)Match of University Degrees in the Graduate Labor Market. Journal for Labour Market Research. Vol. 55, article no. 14, doi: 10.1186/s12651-021-00297-x.

12. Kwok, C.Y.N. (2018). Managing Uncertainty in the Career Development of Emerging Adults: Implications for Undergraduate Students. Australian Journal of Career Development. Vol. 27, no. 3, pp. 137-149, doi: 10.1177/1038416217744216.

13. Bartlett, W., Uvalić, M. (2018). Higher Education and the Graduate Labour Market in the Western Balkans. In: Western Balkan Economies in Transition: Recent Economic and Social Developments / Editors R. Osbild, W. Bartlett. Springer, Cham. Pp. 47-59, doi: 10.1007/978-3-319-93665-9_4.

14. Cherednichenko, G.A. (2020). Graduates of Russian Universities in the Labor Market (Data from a Survey by Rosstat). Sotsiologicheskaya nauka i sotsial’naya praktika = Sociological Science and Social Practice. Vol. 8, no. 3, pp. 108-124, doi: 10.19181/snsp.2020.8.3.7490 (In Russ., abstract in Eng.).

15. Weismann, M., Roth, T. (2025). Conflict and Support during Apprenticeship Training in Germany: Consequences for Apprenticeship Success and Further Employment in the Company. Empirical Research in Vocational Education and Training. Vol. 17, article no. 27, doi: 10.1186/s40461-025-00201-8.

16. Tiouruna, I.O., Kliucharev, G.A. (2024). The Results of the “5-100” Project: Projection on the Employment of Graduates. Sotsiologicheskiye issledovaniya = Sociological research. No. 9, pp. 79-88, doi: 10.31857/S0132162524090079 (In Russ., abstract in Eng.).

17. Kapeliushnikov, R.I. (2021). Returns to Education in Russia: Nowhere below? Voprosy Ekonomiki = Economic Issues. No. 8, pp. 37-68. doi: 10.32609/0042-8736-2021-8-37-68 (In Russ., abstract in Eng.).

18. Silos, P., Smith, E. (2015). Human Capital Portfolios. Review of Economic Dynamics. Vol. 18, no. 3, pp. 635-652, doi: 10.1016/j.red.2014.09.001.

19. Boudarbat, B. (2008). Field of Study Choice by Community College Students in Canada. Economics of Education Review. Vol. 27, no. 1, pp. 79-93, doi: 10.1016/j.econedurev.2006.06.001.

20. Yudina, T.N., Mazaev, Yu.N., Kirillov, A.V. (2019). Job Search by the Graduates of Moscow Universities: Motivation and Claims. Vestnik Rossiyskogo universiteta druzhby narodov. Seriya: Sotsiologiya = RUDN Journal of Sociology. Vol. 19, no. 3, pp. 458-469, doi: 10.22363/2313-2272-2019-19-3-458-469 (In Russ., abstract in Eng.).

21. Rocca, A., Quintano, C. (2024). Success Stems from STEM Fields: An Analysis of Italian Graduates. Italian Economic Journal. Vol. 10, article no. 27, pp. 761-793, doi: 10.1007/s40797-023-00255-1.

22. Martin, J.P., Brown, J.S., Dunmoye, I.D. et al. (2025). AI and Engineering Careers: Recent Graduates’ Outlook on Opportunities and Challenges. International Journal of STEM Education. Vol. 12, article no. 64, doi: 10.1186/s40594-025-00583-x.

23. Burhan, Q.-u-A. (2025). Unraveling the AI Enigma: How Perceptions of Artificial Intelligence Forge Career Adaptability Through the Crucible of Career Insecurity and Skill Development. Management Research Review. Vol. 48, no. 3, pp. 470-488, doi: 10.1108/MRR-01-2024-0022.

24. Bryzgalin, E.A., Alexandrova, J.Y., Pryazhnikov, N.S. (2024). Theoretical-Psychological Analysis of Contemporary Notions of Professional Identity: Developmental Challenges. Part 2. Psikhologicheskie Issledovaniya = Psychological Research. Vol. 17, no. 93, article no. 274, doi: 10.54359/ps.v17i93.1517 (In Russ., abstract in Eng.).

25. Pratt, M., Rockmann, K., Kaufmann, J.B. (2006). Constructing Professional Identity: The Role of Work and Identity Learning Cycles in the Customization of Identity Among Medical Residents. Academy of Management Journal. Vol. 49, no. 2, pp. 235-262, doi: 10.5465/AMJ.2006.20786060.

26. Shneyder, L.B. (2001). Professional’naya identichnost’: monografiya. [Professional Identity: A Monograph]. Moscow: Moscow Open Social University, p. 272 (In Russ.).

27. Dummert, S. (2024) Intergenerational Transmission of Unemployment after Apprenticeship Graduation: Does Parental Socioeconomic Background Still Matter? Journal for Labour Market Research. Vol. 58, article no. 6, doi: 10.1186/s12651-024-00364-z.

28. Sorokin, P.S., Afanaseva, I.A., Vyatskaya, Yu.A., Kovalyova, A. (2025). Agency of Students and Graduates of Russian Universities in the Sphere of Labor and Employment: Educational Experience and Well-Being. Vysshee obrazovanie v Rossii = Higher Education in Russia. Vol. 34, no. 7, pp. 133-152, doi: 10.31992/0869-3617-2025-34-7-133-152 (In Russ., abstract in Eng.).

29. Titarenko, L.G., Shirokanova, A.A. (2020). Students’ Employment Entry Strategies in the Belarus Regulated Labour Market. Sotsiologicheskiye issledovaniya = Sociological Research. Vol. 12, pp. 128-138, doi: 10.31857/S013216250010303-6.

30. Donetskaya, S.S., Dovgal, S.V. (2018). Graduates’ Promotion on Labor Market and Tracking Their Career: The Experience of Novosibirsk State University. Vysshee obrazovanie v Rossii = Higher Education in Russia. No. 4, pp. 93-100. Available at: https://elibrary.ru/download/elibrary_32834841_24382150.pdf (accessed 18.03.2026) (In Russ., abstract in Eng.).

31. Maltseva, V.A., Rozenfeld, N.Ya. (2022). Educational and Career Trajectories of the Russian Youth in a Longitudinal Perspective: A Case of University Graduates. Voprosy obrazovaniya = Educational Studies. No. 3, pp. 99-148, doi: 10.17323/1814-9545-2022-3-99-148. (In Russ., abstract in Eng.).

32. Lihui, H. (2024). Analysis of Employment Information of University Graduates through Data Mining. Automatic Control and Computer Sciences. Vol. 58, pp. 58-65, doi: 10.3103/S0146411624010073.

33. Yates, J. (2025). Graduates’ Career Choices: An Empirically Derived Process Model. International Journal for Educational and Vocational Guidance, doi: 10.1007/s10775-024-09720-4.

34. Melnik A.D., Sudakova A.E., Antonova N.L. (2024) Choosing a Starting Professional Trajectory: Job-Education Mismatch Effect. The Education and Science Journal. Vol. 26, no. 8, pp. 174-206, doi: 10.17853/1994-5639-2024-8-174-205 (In Russ., abstract in Eng.).

35. Volchik, V.V., Maslyukova, E.V. (2020). Employment Insecurity and Behavioral Preferences of University Graduates. Journal of Institutional Studies. Vol. 12, no. 4, pp. 112-125, doi: 10.17835/2076- 6297.2020.12.4.112-125 (In Russ., abstract in Eng.).

36. Benriyene, S., Ismaili, B.A., Bakkali, S. (2024). [Artificial Intelligence and Employability: A Literature Review of Engineer’s Competencies]. In: Ezziyyani, M., Kacprzyk, J., Balas, V.E. (eds) International Conference on Advanced Intelligent Systems for Sustainable Development (AI2SD’2023). AI2SD 2023. Lecture Notes in Networks and Systems. Springer, Cham. Vol. 930, doi: 10.1007/978-3-031-54318-0_18.

37. Levin, B.A., Piskunov, A.A., Poliakov, 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, doi: 10.31992/0869-3617-2022-31-6-79-95 (In Russ., abstract in Eng.)

38. Mosly, I. (2024). Artificial Intelligence’s Opportunities and Challenges in Engineering Curricular Design: A Combined Review and Focus Group Study. Societies. Vol. 14, no. 6, article no. 89, doi: 10.3390/soc14060089.

39. Dewan, U., Hingle, A., McDonald, N., Johri, A. (2025). Engineering Educators’ Perspectives on the Impact of Generative AI in Higher Education. In: 2025 IEEE Global Engineering Education Conference. Pp. 1-10, doi: 10.48550/arXiv.2502.00569.

40. Alshammari, S.H., Alrashidi, M.E., Alshammari, M.H. et al. (2025). Determinants of Student Adoption of Artificial Intelligence Applications in Higher Education. Scientific Reports. Vol. 15, article no. 35921, doi: 10.1038/s41598-025-19851-5.

41. Toshchenko, Zh.T. (2024). Forms of the Higher Education Participation in Ensuring Labor Productivity. Vestnik Rossiyskogo universiteta druzhby narodov. Seriya: Sotsiologiya = RUDN Journal of Sociology. Vol. 24, no. 1, pp. 28-42, doi: 10.22363/2313-2272-2024-24-1-28-42 (In Russ., abstract in Eng.).

42. Gilmanov, A.Z., Kovalenko, S.O. (2015). Role of University in Work Placement of Graduate Students – Experiences of Bonn University. Sotsiologicheskiye issledovaniya = Sociological Research. Vol. 1, pp. 134-135. Available at: https://elibrary.ru/download/elibrary_23104960_11724526.pdf (accessed 18.03.2026). (In Russ.).

43. Sandler, D.G., Sushchenko, A.D., Kuznetsov, P.D., Pechenkina, T.E. (2018). Employment for University Graduates and its Measure the Higher Education Quality. Universitetskoye upravleniye: praktika i analiz = University Management: Practice and Analysis. Vol. 22, no. 3, pp. 73-85, doi: 10.15826/umpa.2018.03.028 (In Russ., abstract in Eng.).

44. Gurtov, V.A., Serova, L.M., Stepus, I.S., Fedorova, E.A., Moroz, D.M. (2014). Development of the Graduates’ Employment Monitoring System. Vysshee obrazovanie v Rossii = Higher Education in Russia. No. 5, pp. 11-23. Available at: https://elibrary.ru/item.asp?id=21518997 (accessed 18.03.2026). (In Russ., abstract in Eng.).

45. Puzanova, Zh.V., Larina, T.I. (2025). Integrating Applied Artificial Intelligence into Non-Technical Master’s Programs: Conceptual Models and Practical Approaches. Vysshee obrazovanie v Rossii = Higher Education in Russia. Vol. 34, no. 8-9, pp. 33-53, doi: 10.31992/0869-3617-2025-34-8-9-33-53 (In Russ., abstract in Eng.).

46. Soloviev, V.P., Pereskokova, T.A. (2018). Technical Education in Russia: Problems and Solutions. Inzhenernoye obrazovaniye = Engineering Education. No. 24, pp. 30-40. Available at: https://old.aeer.ru/files/io/m24/art_4.pdf (accessed 18.03.2026). (In Russ.).

47. Belash, O.Yu., Chirkova, A.A. (2018). Indicators of Education Quality in Internal Monitoring: Difference Between Students and Lecturers in Assessing Indicators Importance. Inzhenernoye obrazovaniye = Engineering Education. No. 24, pp. 166-173. Available at: https://elibrary.ru/download/elibrary_42210868_58221413.pdf (accessed 18.03.2026). (In Russ., abstract in Eng.).

48. Bolotov, V. A. (2005). On the Development of an All-Russian System for Assessing the Quality of Education. Voprosy obrazovaniya = Educational Issues. No. 1, pp. 5-10. Available at: https://elibrary.ru/item.asp?id=21847514 (accessed 18.03.2026). (In Russ.).

49. Gurtov, V.A., Averyanov, A.O., Korzun, D.Zh., Smirnov, N.V. (2022). A System for Classification of Technologies in the Field of Artificial Intelligence for Personnel Forecasting. Ekonomicheskiye i sotsial’nyye peremeny: fakty, tendentsii, prognoz = Economic and Social Changes: Facts, Trends, Forecast. Vol. 15, no. 3, pp. 113-133, doi: 10.15838/esc.2022.3.81.6 (In Russ., abstract in Eng.).

50. Rozhkova, K.V., Roshchin, S.Yu., Travkin, P.V. (2024). From Combining Study and Work to Combining Work and Study? The Changing Model of Russian Higher Education. Voprosy obrazovaniya = Educational Studies. No. 2, pp. 286-322, doi: 10.17323/vo-2024-17242 (In Russ., abstract in Eng.).