Zhaxat Kenzhin

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.

The industrial era is gradually giving way to a creative economy driven by human resources. This study aimed to assess the impact of human resources within the creative economy on countries’ economic growth. The focus was on human capital involved in the creative economy. Panel data from 21 countries (2016–2023) were analyzed. The ILO classification methodology for employment types was applied. A fixed-effects regression model was employed to assess the impact of human capital on economic growth, while controlling for relevant factors. The model’s coefficient of determination increased from 0.494 to 0.652 with the addition of new variables, indicating improved accuracy. These variables were used to assess the effect of creative economy indicators on GDP per capita across countries. A direct correlation has been established between the share of employed people involved in the creative economy and the country’s level of economic development, specifically in terms of GDP per capita (Gini coefficient: r = –0.431, P = 0.01). The quantitative importance of human resources of the creative economy was calculated for both developed and developing countries of the world. The practical value of the obtained results lies in the possibility of their use for the development of public management decisions to stimulate the economic growth of the country.

Type of the article: Research Article

Abstract
The current direction of state development is its focus on citizens (G2C). This transition is accompanied by digitalization, which enables the provision of services to citizens to reach a whole new level through e-government. The aim of this study is to identify the factors in the socio-economic and political environments that influence the formation of e-government across countries. Based on panel data (UN, World Bank, World Intellectual Property Organization, International Monetary Fund) for 48 countries for 2014–2024, regression and dynamic analyses were performed. It has been established that the main factors influencing the e-government index are the human development index (1.29–1.78), the ease of doing business index (–0.00069), the global innovation index (–0.0038), and gross domestic product per capita (4.47e-06). For developed countries, human development (1.9) and innovation (0.0081) are significant, while for developing countries, economic prosperity (1.62) and the business environment (1.61e-05) are significant. Dynamic models confirm the lag effect of the e-government rating (0.43), which indicates the stability of institutional factors. It has been found that the development of e-government is determined by the impact of the innovation economy, human capital, and the openness of state institutions, which form the cumulative effect of the digital transformation of governance.