The Use of Artificial Intelligence in Business Management

Authors

DOI:

https://doi.org/10.58423/2786-6742/2026-13-115-127

Keywords:

business management, management decisions, management functions, digital technologies, artificial intelligence

Abstract

The development of digital technologies is increasing the role of information systems capable of processing large volumes of data and generating analytical information for business management. Artificial intelligence technologies play a key role in this process, enabling comprehensive data processing, forecasting economic performance indicators, and providing information support for decision-making. The study aims to summarize current research on the use of artificial intelligence technologies in business management and to identify the specific features of their application in the implementation of key management functions. The methodology includes the literature review, the comparative method, as well as methods of analysis and synthesis, which allowed the authors to review scientific sources on the outlined issues, compare the views of domestic and foreign authors, generalize theoretical provisions, and systematize the main directions of using artificial intelligence technologies in business management. The article analyzes the results of scientific research devoted to the application of artificial intelligence technologies in the economic activities of enterprises. Based on an analysis of the scientific literature, the directions of artificial intelligence technology use in the field of business management are summarized, and their role in forming the information base for managerial decision-making is determined. The study systematizes the use of artificial intelligence technologies in performing core management functions, including analysis, planning, organization, motivation, and control. It demonstrates that the application of intelligent information systems enables the processing of large volumes of economic data, the construction of analytical models, and the forecasting of changes in economic indicators. The study contributes by systematizing the areas of application of artificial intelligence technologies in business management in accordance with the main management functions, which made it possible to more comprehensively define the role of intelligent information systems in modern management practices. The findings indicate that the integration of artificial intelligence technologies into the business management system contributes to improving information support for management activities, expands the possibilities of economic analysis, and creates conditions for improving the soundness of managerial decisions. The results provide a deeper scientific understanding of the role of intelligent information systems in modern management and identify directions for further research on the use of artificial intelligence technologies in economic activity. The study has practical implications for improving information support for enterprise management activities, facilitating managerial decision-making, and enhancing the teaching of economic and management disciplines.

Author Biographies

Olena Zaika, State Biotechnological University

PhD, Senior Lecturer

Liliia Kharchevnikova, State Biotechnological University

Candidate of Economic Sciences, Associate Professor

References

1. Brynjolfsson, E., & Mitchell, T. (2017). What can machine learning do? Workforce implications. Science, 358(6370), 1530-1534. https://doi.org/10.1126/science.aap8062 DOI: https://doi.org/10.1126/science.aap8062

2. Raisch, S., & Krakowski, S. (2021). Artificial intelligence and management: The automation augmentation paradox. Academy of Management Review, 46(1), 192-210. https://doi.org/10.5465/amr.2018.0072 DOI: https://doi.org/10.5465/amr.2018.0072

3. Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., ... Williams, M. D. (2021). Artificial intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, (57), Article 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002 DOI: https://doi.org/10.1016/j.ijinfomgt.2019.08.002

4. Enholm, I., Papagiannidis, E., Mikalef, P., & Krogstie, J. (2022). Artificial intelligence and business value: A literature review. Information Systems Frontiers, (24), 1709-1734. https://doi.org/10.1007/s10796-021-10186-w DOI: https://doi.org/10.1007/s10796-021-10186-w

5. Di Vaio, A., Palladino, R., Hassan, R., & Escobar, O. (2020). Artificial intelligence and business models in the sustainable development goals perspective. Journal of Business Research, (121), 283-292. https://doi.org/10.1016/j.jbusres.2020.08.019 DOI: https://doi.org/10.1016/j.jbusres.2020.08.019

6. Davenport, T. H., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48(1), 24-42. https://doi.org/10.1007/s11747-019-00696-0 DOI: https://doi.org/10.1007/s11747-019-00696-0

7. Huang, M.-H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2), 155-172. https://doi.org/10.1177/1094670517752459 DOI: https://doi.org/10.1177/1094670517752459

8. Asatova, N. S., & Mazhiyeva, G. (2025). Public finance management using artificial intelligence. Journal of Economic Research & Business Administration, (153), 130-144. https://doi.org/10.26577/be202515339 DOI: https://doi.org/10.26577/be202515339

9. Kumar, M., Gupta, M., & Kumar, D. (2026). A study of the impact of artificial intelligence on financial management. EPRA International Journal of Multidisciplinary Research, (969). https://doi.org/10.36713/epra25600 DOI: https://doi.org/10.36713/epra25600

10. Olar, A.-N., Bilți, R., Cilan, T.-F., & Rusu, C.-M. (2025). The influence of artificial intelligence on financial management decision. Journal of Financial Studies, (10), 346-361. https://doi.org/10.55654/JFS.2025.10.SP.23 DOI: https://doi.org/10.55654/JFS.2025.10.SP.23

11. Raina, K., Sharma, G. D., Taheri, B., Dev, D., & Chavriya, S. (2025). Artificial intelligence-driven management: Bridging innovation, knowledge creation, and sustainable business practices. Journal of Innovation & Knowledge, Article 100860. https://doi.org/10.1016/j.jik.2025.100860 DOI: https://doi.org/10.1016/j.jik.2025.100860

12. Machucho, R., & Ortiz, D. (2025). The impacts of artificial intelligence on business innovation: A comprehensive review of applications, organizational challenges, and ethical considerations. Systems, 13(4), Article 264. https://doi.org/10.3390/systems13040264 DOI: https://doi.org/10.3390/systems13040264

13. Vrontis, D., Christofi, M., Pereira, V., Tarba, S., Makrides, A., & Trichina, E. (2022). Artificial intelligence, robotics, advanced technologies and human resource management: A systematic review. The International Journal of Human Resource Management, 33(6), 1237-1266. https://doi.org/10.1080/09585192.2020.1871398 DOI: https://doi.org/10.1080/09585192.2020.1871398

14. Urbanovič, M., & Holubčík, M. (2026). Artificial intelligence in managerial decision-making for sustainable business models: A systematic literature review. Systems, 14(3), Article 245. https://doi.org/10.3390/systems14030245 DOI: https://doi.org/10.3390/systems14030245

15. Tewari, V. (2026). Artificial intelligence enabled embedded systems for modern management. ICTACT Journal on Microelectronics, (11), 2227–2231. https://doi.org/10.21917/ijme.2026.0374 DOI: https://doi.org/10.21917/ijme.2026.0374

16. Weng, T. (2025). Theory and practice of deep integration of artificial intelligence and business management. Proceedings of Business and Economic Studies, (8), 133-139. https://doi.org/10.26689/pbes.v8i8.13359 DOI: https://doi.org/10.26689/pbes.v8i8.13359

17. Rodchenko, V., & Nesterenko, O. (2025). Conceptual model of implementation of artificial intelligence in the business activity of the enterprise. Acta Academiae Beregsasiensis. Economics, 1(10), 516-531. https://doi.org/10.58423/2786-6742/2025-10-516-531 [in Ukrainian] DOI: https://doi.org/10.58423/2786-6742/2025-10-516-531

18. Bulakh, O. V. (2023). Global impact of artificial intelligence and machine learning on the effectiveness of e-commerce. Biznes Inform, (8), 114-121. https://doi.org/10.32983/2222-4459-2023-8-114-121 [in Ukrainian] DOI: https://doi.org/10.32983/2222-4459-2023-8-114-121

19. Krasnostanova, N. E., & Mikhliaiev, M. O. (2025). Artificial intelligence as a tool for supporting managerial decision-making in the strategic planning of small and medium-sized businesses in Ukraine. Biznes Inform, (9), 70-77. https://doi.org/10.32983/2222-4459-2025-9-70-77 [in Ukrainian] DOI: https://doi.org/10.32983/2222-4459-2025-9-70-77

20. Pivniuk, A. (2024). The use of artificial intelligence in modern business activity. Naukovi zapysky Tavriiskoho natsionalnoho universytetu imeni V. I. Vernadskoho. Seriia: Ekonomika i upravlinnia, 35(74), 69-73. https://doi.org/10.32782/2523-4803/74-4-12 [in Ukrainian] DOI: https://doi.org/10.32782/2523-4803/74-4-12

21. Chaus, R. I. (2024). The influence of artificial intelligence on the digital transformation of business. Ekonomika i upravlinnia, (3), 24-31. https://doi.org/10.36919/2312-7872.3.2024.24 [in Ukrainian] DOI: https://doi.org/10.36919/2312-7872.3.2024.24

22. Axinte, A. (2024). Using artificial intelligence in business. European Financial Resilience and Regulation, 29-36. https://doi.org/10.47743/eufire-2024-1-3 DOI: https://doi.org/10.47743/eufire-2024-1-3

23. Makridakis, S. (2017). The forthcoming artificial intelligence (AI) revolution: Its impact on society and firms. Futures, (90), 46-60. https://doi.org/10.1016/j.futures.2017.03.006 DOI: https://doi.org/10.1016/j.futures.2017.03.006

24. Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577-586. https://doi.org/10.1016/j.bushor.2018.03.007 DOI: https://doi.org/10.1016/j.bushor.2018.03.007

25. How does artificial intelligence shape the productivity and quality of business research? (2025). Discover Artificial Intelligence, (5). https://doi.org/10.1007/s43621-025-01480-7 DOI: https://doi.org/10.1007/s43621-025-01480-7

26. Hasan, R., Mishra, R., & Dwivedi, Y. K. (2024). Managing artificial intelligence in international business: Opportunities and challenges. Thunderbird International Business Review, 66(3). https://doi.org/10.1002/tie.22369 DOI: https://doi.org/10.1002/tie.22369

27. Shevchuk, A. (2025). Optimization of business process management using innovative methods, in particular artificial intelligence. Ekonomika, finansy, upravlinnia: aktualni problemy nauky ta praktychnoi diialnosti, (2), 46-59. https://doi.org/10.37128/2411-4413-2025-2-3 [in Ukrainian] DOI: https://doi.org/10.37128/2411-4413-2025-2-3

Downloads

Published

2026-05-29

How to Cite

Zaika, O., & Kharchevnikova, L. (2026). The Use of Artificial Intelligence in Business Management. Acta Academiae Beregsasiensis. Economics, 1(13), 115–127. https://doi.org/10.58423/2786-6742/2026-13-115-127