APPLICATION OF ARTIFICIAL INTELLIGENCE TO THE DEVELOPMENT OF ENTREPRENEURIAL COMPETENCE IN FUTURE ECONOMISTS: THEORETICAL ASPECTS
DOI:
https://doi.org/10.28925/2412-124X.2025.14.7Keywords:
artificial intelligence, digital competence, entrepreneurial competence, future economists, professional training of students of economic specialties.Abstract
The authors of the article emphasize the importance of entrepreneurial competence for future economists, focusing on the use of artificial intelligence in this process, which is currently a modern technology for transforming education, particularly economic education. By analyzing foreign and Ukrainian publications on the use of AI in the professional training of students majoring in economics, the authors note that the issue of using AI to form or develop entrepreneurial competence of students majoring in economics has not been sufficiently addressed by either Ukrainian or foreign researchers. In this context, researching the possibilities of using AI as a tool for developing entrepreneurial competence of future economists in higher education institutions in Ukraine is a relevant and timely task. The research methodology involved searching for scientific publications in Scopus, ERIC, and Web of Science, followed by an analysis of the selected publications, which allowed the authors to identify a number of key trends, approaches, and established findings. In particular, AI technologies such as machine learning, natural language processing, expert systems, machine vision, large language models, big data, and AI chatbots play a significant role in fostering entrepreneurial competence. The integration of AI into entrepreneurial education enhances students’ digital competence and self-confidence, promotes innovative and creative thinking, technical skills, cognitive engagement, and multicultural communication, and increases their motivation and practical readiness to develop their own digital projects. All this is achieved through a clear strategy and ethical use of AI to improve the quality of economic education.
References
Kruhlyk, O. (2025). Formuvannia analitychnykh kompetentsii maibutnikh ekonomistiv v umovakh tsyfrovizatsii: rol i perspektyvy vykorystannia shtuchnoho intelektu [Formation of analytical competencies of future economists in the context of digitalization: the role and prospects of using artificial intelligence]. In The 24th International scientific and practical conference “Integration of new technologies into science to improve research”, June 17–20, 2025, Paris, France (pp. 300–303). International Science Group.
Kuzomko, V., Buranhulova, V. (2021). Mozhlyvosti vykorystannia shtuchnoho intelektu v diialnosti suchasnykh pidpryiemstv [Possibilities of using artificial intelligence in the activities of modern enterprises]. Economy and Society, 32. https://doi.org/10.32782/2524-0072/2021-32-67
Pivniuk, A. (2024). Vykorystannia shtuchnoho intelektu v suchasnii diialnosti pidpryiemstv [Using artificial intelligence in modern business activities]. Scientific notes of Taurida National V. I. Vernadsky University Series: Economy and Management, 35 (74), 4, 69–73. https://doi.org/10.32782/2523-4803/74-4-12
Fostolovych, V. (2022). Shtuchnyi intelekt v suchasnomu biznesi: potentsial, suchasni trendy ta perspektyvy intehruvannia u rizni sfery hospodarskoi diialnosti i zhyttiediialnosti liudyny [Artificial intelligence in modern business : potential, current trends and prospects of integration in different speres of economic activity and human life activity]. Efektyvna ekonomika, 7. https://doi.org/10.32702/2307-2105.2022.7.4
Shapran, O. (2016). Sutnist i struktura pidpryiemnytskoi kompetentnosti maibutnikh ekonomistiv [The essence and structure of entrepreneurial competence of future economists]. Bulletin of the Cherkasy Bohdan Khmelnytsky National University. Series_«Pedagogical_Sciences», 5, 136–141. https://ped-ejournal.cdu.edu.ua/issue/view/130/55
Graduate Management Admission Council (2025). AI in Business Education Current practices and future potential. https://www.gmac.com/market-intelligence-and-research/research-library/curriculum-insight/ai-current-practices-future-potential
Alqahtani, M. M. (2023). Artificial intelligence and entrepreneurship education: A paradigm in Qatari higher education institutions after COVID-19 pandemic. International Journal of Data and Network Science, 7 (2), 695–706. https://doi.org/10.5267/j.ijdns.2023.3.002
Bacigalupo, M., Kampylis, P., Punie, Y., & Van den Brande, G. (2016). EntreComp: The Entrepreneurship Competence Framework. EU4Digital. https://eufordigital.eu/uk/library/entrecomp-the-entrepreneurship-competence-framework
Bublyk, L. (2025). Maibutni perspektyvy rozvytku navychok ShI dlia studentiv ekonomichnykh osvitnikh napriamiv [Future percpectives on AI skills development for economics students]. Economy and Society, 71. https://doi.org/10.32782/2524-0072/2025-71-19
Chen, L., Ifenthaler, D., Yau, J. Y., & Sun, W. (2024). Artificial intelligence in entrepreneurship education: a scoping review. Education + Training, 66 (6), 589–608. https://doi.org/10.1108/et-05-2023-0169023-0169
Chui, M., Hazan, E., Roberts, R., Singla, A., Smaje, K., Sukharevsky, A., Yee, L., Zemmel, R. (2023). The economic potential of generative AI: The next productivity frontier. McKinsey & Company. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier
Duong, C. D., & Vu, T. N. (2025). Entrepreneurial education and higher education students’ e-entrepreneurial intention: a moderated mediation model of generative AI incorporation and e-entrepreneurial self-efficacy. Higher Education Skills and Work-based Learning, 15 (5), 1024–1048 https://doi.org/10.1108/heswbl-12-2024-0390
Empowering learners for the age of AI: An AI literacy framework for primary and secondary education (2025). (Review draft). AILit Framework. https://ailiteracyframework.org
Lang, Q., Tian, S., Wang, M., & Wang, J. (2024). Exploring the answering capability of large language models in addressing complex knowledge in entrepreneurship education. IEEE Transactions on Learning Technologies, 17, 1–11. https://doi.org/10.1109/tlt.2024.3456128
Malik, A., Onyema, E. M., Dalal, S., Lilhore, U. K., Anand, D., Sharma, A., & Simaiya, S. (2023). Forecasting students’ adaptability in online entrepreneurship education using modified ensemble machine learning model. Array, 19, 100303. https://doi.org/10.1016/j.array.2023.100303
Mayer, H., Yee, L., Chui, M., Roberts, R. (2025). Superagency in the workplace: Empowering people to unlock AI’s full potential. McKinsey & Company. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/superagency-in-the-workplace-empowering-people-to-unlock-ais-full-potential-at-work
Nweke, L.O., Okebanama, U.F. & Mba, G.U. (2025). Enhancing entrepreneurial skills through experiential learning in IoT, AI, and cybersecurity. Discover Education, 4, 149. https://doi.org/10.1007/s44217-025-00573-9
Park, J.-H., Kim, S.-J., & Lee, S.-T. (2025). AI and Creativity in Entrepreneurship Education: A Systematic Review of LLM Applications. AI, 6 (5), 100. https://doi.org/10.3390/ai6050100
Somià, T., & Vecchiarini, M. (2024). Navigating the new frontier: the impact of artificial intelligence on students’ entrepreneurial competencies. International Journal of Entrepreneurial Behaviour & Research, 30 (11), 236–260. https://doi.org/10.1108/ijebr-08-2023-0788
Uzule, K., Dehtjare, J., Verina, N., Ulbinaite, A., & Kitanovikj, B. (2025). Extending the concept of diversity in entrepreneurship competence education to include AI skills: public administration employers and experts’ insights. Problems of Education in the 21st Century, 83 (4), 579–602. https://doi.org/10.33225/pec/25.83.579
Vuorikari, R., Kluzer, S., & Punie, Y. (2022). DigComp 2.2: The Digital Competence Framework for Citizens – With new examples of knowledge, skills and attitudes. Publications Office of the European Union. https://data.europa.eu/doi/10.2760/115376
Yu, G., Ramayah, T., & Lin, Z. (2025). Toward understanding the role of generative AI in entrepreneurship education: A systematic review. Computers and Education Artificial Intelligence, 100470. https://doi.org/10.1016/j.caeai.2025.100470
Zhou, H., Chen, Y., Liu, Y., Jiang, R., Wang, J., & Sun, M. (2025). Harnessing generative AI and argumentation-driven learning for entrepreneurial competence development: evidence from university-based studies. Interactive Learning Environments, 1–18. https://doi.org/10.1080/10494820.2025.2519122
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