Aug 2026· Journal of Monetary Economics and Management· pp. 504-511· 0 citations
TL;DR
The proposed approach, based on the "human-in-the-loop" principle and a unified information space of digital twins, ensures self-learning of models and continuous improvement of the accuracy of management decisions in conditions of high uncertainty in construction production.
Abstract
The article examines an approach to managing a construction organization based on the application of artificial intelligence methods, driven by the need to overcome systemic industry problems: staff shortages, low labor productivity, high uncertainty and risks in the implementation of investment and construction projects. The analysis of existing theoretical approaches to construction organization management is carried out, identifying interactive, organizational-technological, system-digital, process approaches and cybermanagement, which revealed their limitations in the context of digital transformation of the economy. An approach to managing a construction organization is proposed, containing four levels (strategic, tactical, operational and executive) and artificial intelligence methods: large language models (LLM) for market analysis and generation of strategic alternatives; neural network forecasting for optimization of schedules and cost of construction and installation works; computer vision and IoT for construction site monitoring, occupational safety and quality control; AR systems and digital twins for visualization and support of executive operations. The proposed approach, based on the "human-in-the-loop" principle and a unified information space of digital twins, ensures self-learning of models and continuous improvement of the accuracy of management decisions in conditions of high uncertainty in construction production.
This paper explores artificial intelligence (AI) integration in construction bid automation. The literature review suggests that currently, construction firms generally rely extensively on manual processes to produce their technical and commercial bid proposals. The problem with this existing practice in many firms is...
Oscar Kwame Kwasafo, S. Laryea, Neil Govender· Construction Business and Pr...· 0 citations
The article examines the modern stages of construction management, the authors identify the main criteria for improving efficiency and effectiveness in the implementation of construction. The conclusions and recommendations for improving the level of organizational and economic management of construction using modern t...
Marianna Slavikovna Arutunyan, Aleksey Evgenievich Tsuprunov, Daniil Dmitrievich Narislanov et al.· EKONOMIKA I UPRAVLENIE: PROB...· 0 citations
The article examines the transformation of the professional activities of project managers under the influence of the introduction of artificial
intelligence and automation in key project management processes. Based on
the analysis of modern scientific publications, industry research and practical
experience of Russian...
K. A. Chistyakova, Anna A. Kozachok· Academic journal· 0 citations
The review examines 130 peer-reviewed works from 1985 to 2025 on the application of Artificial Intelligence (AI) and Machine Learning (ML) in construction project management, covering Industry 3.0, Industry 4.0, and the post-COVID-19 era. The trend in articles demonstrated that AI and ML are widely employed in planning...
Saad Naseer, Muhammed Umer Yaqoob· International Journal on Com...· 0 citations
The transformation of the economic strategy of construction development in the digital economy is associated with the adoption of artificial intelligence technologies, which are changing the mechanisms for forming, implementing, and adapting strategic decisions. Growing market uncertainty, increasingly complex investme...
The article examines the theoretical and applied aspects of predictive management of the economic efficiency of construction projects in the context of digital transformation. The relevance of shifting from traditional reactive management, focused on identifying and correcting deviations after their occurrence, to pred...
M. Borovyk, Denys Dudnyk· Business Navigator· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.