Article
This study aims to explore the potential of integrating robotic process automation (RPA) and artificial intelligence (AI) technologies to address the strategic digital transformation challenges and improve management efficiency in the physical education and sports sector.
The purpose is to identify prospects and methods for the intelligent automation of management processes in physical education and sports based on the integration of RPA and AI technologies. Intelligent automation is considered as a digital technology for analyzing data, processing complex tasks, and improving the efficiency and proactivity of management decisions.
Methods and organization of the research. The research methodology integrates a systems approach and comparative analysis, is based on the development of a functional-process architecture for managing physical education and sports, and includes elements of qualitative analysis and a review of case studies from the following databases: Elibrary.ru, Link.springer.com, and Scholar.google.com. The scientific novelty of the methodology lies in proposing the RPA+AI integration model for implementing management processes in the physical education and sports (PE&S) ecosystem. General principles of digital transformation are adapted to the specifics of the industry, and implementation tools are systematized through database creation, parameter validation, and responsibility matrix generation.
Results and discussion. The results demonstrate that combining the potential of RPA and AI reduces labor costs, increases the return on intellectual capital, and improves the validity, flexibility, and quality of management decisions through integrated data processing and the modernization of processes across all management levels.
Conclusion. The scientific novelty lies in the development of a methodological framework for applying intelligent automation in PE&S. The practical significance lies in the potential application of the results for the digital transformation of management processes in the industry ecosystem.
1. Verisov, M. Life after import substitution: how the RPA market is developing in Russia / - URL: https://trends.rbc.ru/trends/industry/64782f739a794758c4f8d779
2. Vishnyakova, O. N. Artificial intelligence as a tool for HR marketing in the field of physical education and sports / O. N. Vishnyakova, E. N. Kulik // Science and sport: current trends. – 2025. – Vol. 13, No. 3 (51). – Pp. 222-233. – DOI 10.36028/2308-8826-2025-13-3-222-233. – EDN LESNZV.
3. Godin, V. V. Information pyramid of organization and tasks of artificial intelligence / V. V. Godin, A. E. Terekhova // Step into the future: artificial intelligence and digital economy: Smart Nations: economy of digital equality: proceedings of the III International Scientific Forum, Moscow, December 9-10, 2019 / Ministry of Science and Higher Education of the Russian Federation, State University of Management. Volume Issue 1. – Moscow: State University of Management, 2020. – Pp. 259-269. – EDN ADBPXA.
4. Doguchaeva, S. M. Intelligent components of automation in the digital segment of the modern economy / S. M. Doguchaeva // Modern science: current problems of theory and practice. Series: Economics and Law. – 2021. – No. 6. – Pp. 16-19. – DOI 10.37882/2223-2974.2021.06.11. – EDN DJZQER.
5. Melnikov, I. Intelligent automation - more than RPA / I. Melnikov // Open systems. DBMS. – 2024. – No. 1. – Pp. 11-12. – EDN EHDGMJ.
6. Polyakov, K. G. Digitalization of management: analysis of transformations of management processes in the conditions of the modern economy / K. G. Polyakov // Scientific aspect. – 2024. – Vol. 6, No. 6. – Pp. 668-676. – EDN LIEZTE.
7. Designing an intelligent business process automation system in HR management based on machine learning technologies / A. S. Samusenko, E. L. Vaitekuniene, Yu. K. Ershov, A. V. Nizameeva // Global scientific potential. – 2025. – Vol. 1, No. 5 (170). – Pp. 225-228. – EDN LVAVHM.
8. Tulyakov, T. Robotic process automation (RPA), artificial intelligence (AI), combining two technologies - URL: https://rpa2.ru/blog/tekhnologii/robotizirovannaya-avtomatizatsiya-prot…
9. Afrin S., S. Roksana and R. Akram, "AI-Enhanced Robotic Process Automation: A Review of Intelligent Automation Innovations," in IEEE Access. – vol. 13. – pp. 173-197. – 2025, doi: 10.1109/ACCESS.2024.3513279.
10. Crawford, D. Bain & Company Technology Report 2024/ – URL: https://ict.moscow/analytics/technology-report-2024/
11. Faqihi, A., & Miah, S. J. (2023). Artificial Intelligence-Driven Talent Management System: Exploring the Risks and Options for Constructing a Theoretical Foundation. Journal of Risk and Financial Management, 16(1), 31. https://doi.org/10.3390/jrfm16010031
12. Golenkov, V. Problems and prospects of automating various types and elds of human activity with the help of next-generation intelligent computer systems / V. Golenkov, V. Taranchuk, M. Kovalev // Открытые семантические технологии проектирования интеллектуальных систем. – 2022. – No. 6. – P. 327-346. – EDN TOBWWF.
13. Halid, H., Ravesangar, K., Mahadzir, S.L., Halim, S.N.A. (2024). Artificial Intelligence (AI) in Human Resource Management (HRM). In: Machado, C. (eds) Building the Future with Human Resource Management. Management and Industrial Engineering. Springer, Cham. – URL: https://doi.org/10.1007/978-3-031-52811-8_2
14. Ismanov I., N. Qayumov, D. Mukhamadjonova and B. Akhmadaliyev, "AI and Cost Management: Strategies for Reducing Expenses and Improving Profit Margins in Business," 2024 International Conference on Knowledge Engineering and Communication Systems (ICKECS), Chikkaballapur, India. – 2024. - pp. 1-7. – doi: 10.1109/ICKECS61492.2024.10616761.
15. Kaczmarek, P. (2024). Leveraging Artificial Intelligence and Robotic Process Automation to Streamline Administrative Workflows in Public Health Departments. ISCSITR – International Journal of Scientific Research in Artificial Intelligence and Machine Learning (ISCSITR-IJSRAIML). - 5(2). – рр. 29-35.
16. McLean, S., Read, G. J. M., Thompson, J., Baber, C., Stanton, N. A., & Salmon, P. M. (2023). The risks associated with Artificial General Intelligence: A systematic review. Journal of Experimental & Theoretical Artificial Intelligence. – 35(5). – рр. 649-663. – https://doi.org/10.1080/0952813X.2021.1964003
17. Mukayev, T. Development of intelligent workflow automation systems based on the integration of RPA and AI models / T. Mukayev // Cold Science. – 2025. – No. 17. – P. 15-27. – EDN WYULKG.
18. Pokala, Poornachandar, The Integration And Impact Of Artificial Intelligence In Modern Enterprise Resource Planning Systems: A Comprehensive Review (November 01, 2024). https://doi.org/10.5281/zenodo.14050064, Available at SSRN. – URL: https://ssrn.com/abstract=5069295 or http://dx.doi.org/10.2139/ssrn.5069295
19. Principles of Automation of Development of Open Projects Based on the Ecosystem of Intelligent Computer Systems of the Next Generation / N. Grakova, N. Zotov, M. Orlov [et al.] // Открытые семантические технологии проектирования интеллектуальных систем. – 2025. – No. 9. – P. 147-172. – EDN RZPOKI.
20. Suraj, P. (2024) Synergizing robotics and artificial intelligence: transforming manufacturing and automation for industry 5.0. Synergy: Cross-Disciplinary Journal of Digital Investigation. – 2 (11). – pp. 69-75. – ISSN 2995-4827
21. Yendluri D. K., R. Thatikonda, R. Thatikonda, J. Ponnala, M. Kempanna and A. Bhuvanesh / Risk Management in Robotic Process Automation. – 2024 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), Gwalior, India. – 2024. – pp. 1-6. – doi: 10.1109/IATMSI60426.2024.10503443.
22. Zhang, H. Navigating post-crowdfunding commercialization: Launch decision, market sales, and product survival. J. of the Acad. Mark. Sci. – 2025 – https://doi.org/10.1007/s11747-025-01128-y
