Abstract
The article examines the role of artificial intelligence in improving the emotional and intellec-tual competencies of civil servants and assesses its impact on the quality of managerial decisions and communication processes in the public sector. The relevance of the study is driven by the need to adapt public administration personnel to the challenges of digital transformation, requiring enhanced com-munication skills, stress resistance, and the ability to make well-balanced decisions. It has been deter-mined that the use of adaptive learning platforms, intelligent behavioral analysis, and emotion recog-nition systems contributes to the personalized development of civil servants, optimizes training pro-cesses, and enhances managerial decision-making efficiency. To achieve this objective, the study employs methods of structural-functional analysis, system-atization of scientific approaches, modeling, and content analysis of modern AI tools. The primary technologies used for monitoring emotional states, adapting training programs, and improving com-munication strategies have been assessed. The study has established that integrating artificial intelligence into civil servant training sys-tems presents a range of challenges, including ethical, technological, and social risks. It has been found that automated emotional state analysis requires clear regulatory frameworks to prevent violations of confidentiality and manipulative use of data. It has been proven that the technological limitations of emotion recognition algorithms can lead to inaccurate conclusions, affecting the quality of managerial decisions. The social aspects of AI integration involve the risk of reducing interpersonal interaction, which may impact team effectiveness and trust in digital technologies within the public sector. The conclusions substantiate the need for a balanced combination of AI tools with traditional methods of emotional intelligence development, advocating for a comprehensive training system for civil servants. A model is proposed in which artificial intelligence is utilized for personalized learning, assessing communication competencies, and analyzing behavioral reactions. It is recommended to im-plement adaptive learning platforms, virtual AI coaches, and emotional state assessment systems to reduce stress levels, improve managerial decisions, and develop flexible communication strategies. The practical significance of the study lies in the potential application of the developed model for designing effective training programs for civil servants, considering their individual communica-tion and emotional competencies. The integration of artificial intelligence into public administration training will improve civil servant interaction with citizens, facilitate effective decision-making, and create new opportunities for adaptation to evolving socio-political conditions. Future research should focus on refining algorithms for emotional state analysis and developing mechanisms to assess the impact of AI tools on managerial efficiency. The study of social and ethical aspects of AI integration into civil servant training will help define optimal regulatory approaches to ensure the effectiveness and transparency of these technologies.