TRANSFORMATION OF CONSTRUCTION PROJECT MANAGEMENT THROUGH AI: ENHANCING EFFICIENCY AND MITIGATING RISKS

ТРАНСФОРМАЦИЯ УПРАВЛЕНИЯ СТРОИТЕЛЬНЫМИ ПРОЕКТАМИ С ПОМОЩЬЮ ИИ: ПОВЫШЕНИЕ ЭФФЕКТИВНОСТИ И СНИЖЕНИЕ РИСКОВ

Чупурова Софья Николаевна

студент, ИИЭСМ 1-17, Национальный исследовательский Московский государственный строительный университет,

РФ, г. Москва

Монаенкова Елизавета Алексеевна

студент, ИИЭСМ 1-17, Национальный исследовательский Московский государственный строительный университет,

РФ, г. Москва

ABSTRACT

  AI is transforming construction project management by enhancing efficiency and mitigating risks. The application of AI optimizes processes at all stages—from planning to operation. Special attention is given to optimization, automation, forecasting, and risk reduction. Examples of AI applications, including data analysis and predictive analytics, are discussed. The prospects and challenges of AI development in construction are also examined.

АННОТАЦИЯ

Искусственный интеллект трансформирует управление строительными проектами, повышая эффективность и снижая риски. Применение искусственного интеллекта оптимизирует процессы на всех этапах — от планирования до эксплуатации. Особое внимание уделяется оптимизации, автоматизации, прогнозированию и снижению рисков. Обсуждаются примеры применения ИИ, включая анализ данных и прогнозную аналитику. Также рассматриваются перспективы и проблемы развития ИИ в строительстве.

Keywords: artificial intelligence (AI), construction, management, risks, automation, forecasting.

Ключевые слова: искусственный интеллект (ИИ), строительство, управление, риски, автоматизация, прогнозирование.

The construction industry, which has relied for centuries on time-tested yet often labor-intensive methods, stands on the brink of a revolution. Artificial intelligence (AI) is no longer a futuristic concept but a reality permeating all aspects of construction, from initial design and material procurement to the actual erection of buildings and infrastructure. However, perhaps the most significant impact of AI is on construction project management, where its capabilities in optimization, forecasting, and automation unlock unprecedented opportunities for improving efficiency, reducing costs, and minimizing risks. Therefore, the aim of this work is to identify and analyze the key directions of artificial intelligence (AI) application in construction project management to enhance efficiency, mitigate risks, and optimize processes, as well as to identify existing barriers and prospects for the adoption of these technologies in the construction industry.

From Manual Planning to Intelligent Systems.

In traditional construction management, planning and scheduling are often based on the project manager’s experience and heuristic methods, inevitably leading to inaccuracies, risk underestimation, and subsequent deviations from the schedule and budget. AI fundamentally changes this paradigm by offering intelligent systems capable of processing vast amounts of data and generating more accurate and realistic plans.

Machine learning (ML) algorithms analyze historical data from hundreds or thousands of completed projects, considering a wide range of factors: weather conditions across seasons, labor availability and qualifications, supply chain logistics, material prices, subcontractor relationships, and even the terrain features of the construction site. Based on this information, AI creates detailed schedules that define the optimal sequence of tasks, required resources, and deadlines.

Moreover, unlike the static schedules used in the past, AI enables dynamic adaptation of the plan to changing circumstances. Predictive analytics, powered by machine learning models, forecasts potential delays, resource shortages, or supplier issues. In such cases, the system automatically generates alternative scenarios, offering the project manager options for resource reallocation, priority adjustments, or new contracts to minimize negative impacts on construction progress.

Automation of Monitoring and Quality Control: The AI Perspective.

Ensuring compliance of construction work with project documentation, quality standards, and safety requirements is a key task in construction management. Traditionally, this task is addressed through regular inspections, visual checks, and manual parameter measurements. However, this approach is labor-intensive, subjective, and not always capable of promptly identifying deviations from standards.

AI offers a qualitatively new level of monitoring and quality control, based on automated data collection and analysis using various technologies. Drones equipped with high-sensitivity cameras and sensors scan the construction site, generating 3D models of the terrain and structures. Computer vision algorithms analyze images to detect deviations from the project, such as incorrect geometry of structures, poor welding, uneven masonry, or the use of non-compliant materials.

These systems can also automatically assess work progress, determining the volume of completed operations and comparing them with planned values. Information about detected deviations and violations is immediately relayed to project managers and quality control engineers, enabling prompt corrective actions.

Furthermore, AI is used to analyze large volumes of data collected from sensors installed on equipment and structures. This data allows tracking environmental parameters (temperature, humidity, vibration), monitoring equipment condition (wear and tear, energy consumption), and identifying potential issues at an early stage. For example, AI can detect anomalies in the operation of a concrete mixer, indicating engine failure, or predict the collapse of a load-bearing structure based on deformation and load data analysis.

Construction Site Safety: From Reaction to Prevention.

Construction sites remain one of the most dangerous workplaces, where hundreds of thousands of accidents occur annually, leading to injuries, disabilities, and even fatalities. Traditional safety measures, such as briefings, equipment checks, and adherence to safety rules, are important but often insufficient to prevent all risks.

AI opens new possibilities for enhancing construction safety through proactive hazard identification and prevention. Computer vision systems analyzing video feeds from cameras can automatically detect safety violations, such as the absence of personal protective equipment (helmets, safety harnesses), improper equipment use, or unauthorized entry into hazardous zones.

ML algorithms analyze historical accident data to identify risk factors and patterns leading to injuries. Based on this information, AI creates models to predict the likelihood of accidents under specific conditions. This enables project managers to take preventive measures, such as increasing oversight of hazardous operations, conducting additional safety briefings, or modifying work procedures. Wearable AI devices tracking workers’ physiological parameters can detect signs of fatigue, stress, or poor health, which may reduce concentration and increase the risk of errors leading to injuries. The system alerts the worker and their supervisor about the need for rest or medical attention.

Challenges and Prospects of AI Integration.

The adoption of AI in construction project management is a complex, multi-stage process requiring significant investments, revisions of existing business processes, and the training of skilled personnel.

One of the main challenges is the integration of AI systems with existing information systems, such as project management, accounting, logistics, and human resource management systems. Different systems often use varying data formats and communication protocols, complicating integration.

Another challenge is ensuring the security and confidentiality of data collected and processed by AI systems. Construction projects often contain sensitive information related to financial performance, construction technologies, and trade secrets. Robust mechanisms must be developed to protect data from unauthorized access, leaks, and misuse.

Finally, successful AI implementation requires personnel training to work with new tools and technologies. Project managers must understand AI capabilities and be able to use them effectively for decision-making. Engineers need skills to interpret data generated by AI systems and implement corrective actions. Workers must be trained to operate new equipment and follow recommendations provided by AI systems.

Despite these challenges, the benefits AI can bring to the construction industry are so significant that its widespread adoption is only a matter of time. In the future, we will see more and more construction companies using AI to optimize planning, automate monitoring, enhance safety, reduce costs, and improve construction quality. AI will become an indispensable tool for professionals, enabling them to build more efficiently, safely, and sustainably.

References:

1. Fedorova D.V. Usage of artificial intelligence technologies in construction: current trends and future prospects. The Eurasian Scientific Journal. 2024;16(3): 19SAVN324.
2. Shavshukov, V. M., Oleynik, A. V., & Meshkova, N. L. (2024). Information modeling technology in the construction industry. Journal of Economics, Entrepreneurship and Law, 14(6), 3207-3218.
3. Lanchakov A.B. Innovative technologies and artificial intelligence in the construction sector. Bulletin of Science and Research Center of Construction. 2024;43(4):166-181.
4. Volovik, A. M. (in press). (2025). Rol tekhnologiy II v stroitelnoy otrasli: ustoychivoe razvitie i bezopasnost. Economic security, 8(4).
5. Slepushkin D.V., Burlov D.Yu. Artificial intelligence and automation of design processes in construction: a bibliometric analysis. Vestnik MGSU. 2025;20(3):440-455.