РОЗРОБКА ІНФОРМАЦІЙНИХ ТЕХНОЛОГІЙ ДЛЯ ІНТЕЛЕКТУАЛЬНОГО ПЛАНУВАННЯ РОБОТИ КОМАНДИ ІТ-ПРОЄКТУ НА ОСНОВІ ГНУЧКОЇ МЕТОДОЛОГІЇ

The subject of the study is the development of information technology for intelligent planning of the IT project team. The purpose of the study is to reduce project risks associated with the perception of tasks and their distribution among team members within the project sprint by introducing methods and models for intelligent planning of the IT project team. The information technology is developed on the basis of a set of methods and models, namely: a method for intelligent planning of the IT project team; a model for evaluating a textual description of a task; a method for improving textual descriptions of project tasks; a model for distributing sprint tasks among performers; a method for generating recommendations when planning the work of an IT project team. The use of models related to the processing of textual descriptions of project tasks provides a better understanding of the tasks by the team and increases the efficiency of project implementation. The use of artificial intelligence, including large language models, and stable distribution algorithms in management processes contributes to the automation and efficiency of working with project sprint tasks, increases productivity and team cohesion.  The result of the study is an information technology based on the integration of artificial intelligence into sprint planning, task allocation, and risk management. The application of the proposed information technology has significant potential to increase project flexibility, efficiency, and overall success. The developed information technology takes into account the project context and expert opinions, which makes it flexible and adaptive to the specifics of a particular project and team characteristics, which is important for further improving project management processes.  The information technology for intelligent planning of the IT project team's work will  you to assess and reduce the negative impact of factors that threaten the timing and quality of the project by analyzing historical data and modeling team behavior.