Rymkul Ismailova

The purpose of this study is to explore the involvement of citizens in the administration of local budgets, which significantly contribute to the financial and economic independence of rural areas. The study presents the findings of a sociological research conducted in the Turkestan region, Kazakhstan. The survey included 259 rural residents from 14 rural districts and two significant cities in the region, all aged 18 and above and permanent residents of these areas.
The analysis is based on the survey results, focusing on the overall level of citizens’ engagement in decision-making regarding local budget formation and distribution in rural areas. The study reveals a low level of citizen participation in managing the local budget. While general meetings and local gatherings serve as primary avenues for citizen involvement, only 79.9% of respondents reported participating in budget discussions, with only 20.1% of their opinions considered during budget allocation.
Finally, the study identifies several factors that negatively affect effective citizen participation in local budget management. These factors include a lack of timely awareness and information about upcoming planning and budget meetings (56.4%), insufficient transparency in the actions of local executive leaders (Akims) (14.3%), bureaucratic complexity and a formal approach to budget discussions (3.5%), and low levels of citizen trust in rural district Akims (5.4%).

Acknowledgment
This study is funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (BR18574203).

This study explores the integration of artificial intelligence (AI) into project management through a bibliometric analysis of scholarly publications and patents from 2001 to 2024. The paper aims to identify key trends, emerging applications, and global contributions to this evolving field. The study analyzes 51,752 patents from Lens, 5.5 million scholarly records from Google Scholar, and 436,380 records from Web of Science, providing a comprehensive overview of AI’s impact on project management. The analysis maps the evolution of AI-driven project management practices, focusing on resource allocation, risk management, and scheduling optimization. The findings reveal a substantial increase in AI-related project management research, with China and the United States leading in research output. A notable surge in publications post-2019 suggests acceleration due to the COVID-19 pandemic and the growing demand for digital transformation in project execution. Despite the rising adoption of AI in project management, research gaps persist, particularly in interdisciplinary methodologies, practical AI applications, and ethical concerns related to algorithmic decision-making. This study contributes to understanding AI’s transformative role in project management and highlights future research directions to enhance AI adoption for improved efficiency, decision-making, and project performance. The findings underscore the need for continued exploration of interdisciplinary approaches, practical implementations, and ethical considerations to foster innovation and efficiency in AI-driven project management.