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In the given scientific inquiry, the problem of utilizing artificial intelligence tools for optimizing and automating management processes in professional and Olympic sports management is examined. Considering the realities, managers of sports clubs, public organizations, and professional sports associations often juggle coaching and managerial duties, leading to compromised task execution due to time constraints and excessive paperwork. It has been identified that managerial work demands continuous education and enhancement of personnel management skills, encompassing not only quality control of duties performed by sports association or club members, but also personnel selection, adaptation, training, initiation, and implementation of cutting-edge technologies and work methods. A significant portion of these tasks can be delegated to artificial intelligence processing, which, when properly utilized, can alleviate managers from 60% of paper and routine work, resulting in even more precise and thorough automation. Consequently, managers would have more time to focus on managerial tasks requiring indispensable human qualities, experiential wisdom, and interpersonal communication. This approach is particularly pertinent to sports management, as sports managers are the professionals who amalgamate professional work skills with athletes, coaches, parents, governmental representatives, and investors. The invaluable experience and expertise of sports managers significantly influence the development and deepening of Ukrainian and global sports. By characterizing methods of utilizing artificial intelligence tools in professional and Olympic sports management processes, strategies for optimization in sports management were examined to analyze and identify ways to enhance working conditions for sports managers, especially in professional and Olympic sports. The objective is to create conditions for the development of domestic and international sports, optimizing the performance of coaches and personnel in sports associations and public organizations.
Serputko et al. (Mon,) studied this question.