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Artificial intelligence in management education: opportunities and challenges

https://doi.org/10.55959/MSU0130-0105-6-60-3-15

Abstract

The key objective of the study is to reveal the potential for improving the quality of teaching activity in the field of management disciplines based on the application of artificial intelligence (AI) tools. As a methodological approach the authors consider a systemic analysis of transformation of the role and main functions, tasks of a teacher in conditions of rapid development and availability of generative artificial intelligence (AI) tools. The authors substantiate the rise and development of a new hybrid model ‘teacher + AI’ in the field of management disciplines. The paper considers prompt engineering as a tool to develop and design management courses, shows the possibilities of improving evaluation system using artificial intelligence, pays special attention to new tools to visualize learning material to increase students’ involvement, cites successful practices of integrating various AI tools in the learning process. The authors argue that AI not only provides new opportunities to improve teaching activities but also generates new problems of both pedagogical and organizational nature in the field of management disciplines. The findings aim at expanding the discourse on the opportunities and risks of using.

About the Authors

O. P. Molchanova
Lomonosov Moscow State University

Moscow



I. D. Burak
Lomonosov Moscow State University
Russian Federation

Moscow



S. V. Shchelokova
Lomonosov Moscow State University
Russian Federation

Moscow



References

1. Bajzarov, A. E., Sevrjukov, S. Ju., Trofi mceva, A. S., Sytnik, A. N., Rudakova, D. D., Bazluckaja, M. M., & Drozdova, P. P. (2024). Iskusstvennyj intellekt i obrazovanie. Korotko o tom, chto proishodit. (B. A., Red.) Sankt-Peterburg: Centr prepodavatel’skogo masterstva v biznes-obrazovanii VShM SPbGU.

2. Molchanova, O. P., & Shchelokova, S. V. (2023). Sinhronizacij a obrazovatel’noj issledovatel’skoj i konsul’tacionnoj dejatel’nosti v oblasti menedzhmenta kak antikrizisnaja mera. V G. I. Brjalina, & L. V. Lapidus (Red.), Mezhdunarodnaja ezhegodnaja nauchnaja konferencij a Lomonosovskie chtenij a-2022. Sekcij a jekonomicheskih nauk. Nauka i iskusstvo jekonomicheskoj politiki v krizisnyh uslovij ah Sbornik luchshih dokladov. (str. 381–388). Moskva: Jekonomicheskij fakul’tet MGU imeni M. V. Lomonosova.

3. Tihonov, A. N., Abrameshin, A. E., Voronina, T. P., Ivannikov, A. D., & Molchanova, O. P. (1998). Upravlenie sovremennym obrazovaniem: social’nye i jekonomicheskie aspekty. Moskva: Vita-Press.

4. Bouschery, S., Blazevic, V., & Piller, F. (2023). Augmenting Human Innovation Teams with Artifi cial Intelligence: Exploring Transformer-Based Language Models. Journal of Product Innovation Management, 40(3).

5. Burak, I., & Razumova, T. (2023). INTED2023 Proceedings. Distant vs face-to-face vs hybrid learning: pros & cons for professional education (pp. 7215-7219). Valencia: IATED.

6. Chatterjee, J., & Dethlefs, N. (2023). This new conversational AI model can be your friend, philosopher, and guide ... and even your worst enemy. Patterns, 4(1), 100676.

7. Cranefi eld, J., Winikoff , M., Chiu, Y., Li, Y., Doyle, C., & Richter, A. (2022). Partnering with AI: The case of digital productivity assistants. Journal of the Royal Society of New Zealand, 53(1), 95-118.

8. Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., Carter, L., Chowdhury, S., Crick, T., Cunningham, S. W., Davies, G. H., Davison, R. M., Dé, R., Dennehy, D., Duan, Y., Dubey, R., Dwivedi, R., Edwards, J. S., Flavián, C., Gauld, R., Grover, V., Hu, M.-C., Janssen, M., Jones, P., Junglas, I., Khorana, S., Kraus, S., Larsen, K. R., Latreille, P., Laumer, S., Malik, F. T., Mardani, A., Mariani, M., Mithas, S., Mogaji, E., Nord, J. H., O’Connor, S., Okumus, F., Pagani, M., Pandey, N., Papagiannidis, S., Pappas, I. O., Pathak, N., Pries-Heje, J., Raman, R., Rana, N. P., Rehm, S. V., Ribeiro-Navarrete, S., Richter, A., Rowe, F., Sarker, S., Stahl, B. C., Tiwari, M. K., van der Aalst, W., Venkatesh, V., Viglia, G., Wade, M., Walton, P., Wirtz, J., & Wright, R. (2023). Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642

9. D’Amico, А., Delteil, В., Hazan, Е., Tricoli, А., & Montard, А. (5 February 2025 г.). How AI is transforming strategy development. Получено из McKinsey & Company: https://www.mckinsey.com/capabilities/strategy-and-corporate-finance/our-insights/how-ai-istransforming-strategy-development#/

10. Fatemi, G., & Saito, E. (2020). Unintentional plagiarism and academic integrity: The challenges and needs of postgraduate international students in Australia. Journal of Further and Higher Education, 44(10), 1305–1319.

11. Gupta, P., Mahajan, R., Badhera, U., & Kushwaha, P. S. (2024). Integrating generative AI in management education: A mixed-methods study using social construction of technology theory. The International Journal of Management Education, 22(3).

12. Hu, K. (2023). ChatGPT sets record for fastest-growing user base. Получено January 2025 г., из Reuters: https://www.reuters.com/technology/chatgpt-sets-record-fastestgrowing-user-base-analyst-note-2023-02-01

13. Jose, E. M. K., Prasanna, A., Kushwaha, B. P., & Das, M. (2024). Can generative AI motivate management students? The role of perceived value and information literacy. The International Journal of Management Education, 22(3), 101082. https://doi.org/10.1016/j.ijme.2024.101082

14. Lee, K.-W. (2025). An integrated framework for Gen AI-assisted management learning: Insights from Kolb’s learning cycle theory and knowledge types perspectives. The International Journal of Management Education, 23(2), 101164. https://doi.org/10.1016/j.ijme.2025.101164

15. Lim, W. M., Gunasekara, A., Pallant, J., Pallant, J. L., & Pechenkina, E. (2023). Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators. The International Journal of Management Education, 21(2), 100790.

16. Shchelokova, S., & Suslova, I. (2023). Managerial competencies of graduates: Requirements in the post-covid era. INTED2023 Proceedings (стр. 6662–6662). IATED.

17. Valcea, S., Hamdani, M. R., & Wang, S. (2024). Exploring the Impact of ChatGPT on Business School Education: Prospects, Boundaries, and Paradoxes. Journal of Management Education, 48(5), 915-947. https://doi.org/10.1177/10525629241261313

18. Wang, K., Cui, W., & Yuan, X. (2025). Artifi cial Intelligence in Higher Education: The Impact of Need Satisfaction on Artifi cial Intelligence Literacy Mediated by Self-Regulated Learning Strategies. Behavioral Sciences, 15(2), 165. https://doi.org/10.3390/bs15020165


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For citations:


Molchanova O.P., Burak I.D., Shchelokova S.V. Artificial intelligence in management education: opportunities and challenges. Moscow University Economics Bulletin. 2025;(3):348-365. (In Russ.) https://doi.org/10.55959/MSU0130-0105-6-60-3-15

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ISSN 0130-0105 (Print)