Artificial intelligence of large models as a driver of transformation of qualitative productivity in the construction industry: mechanisms, ways and practical research using the example of DeepSeek
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Abstract
The study presents a comprehensive analysis of the impact of artificial intelligence of large models on the transformation of qualitative performance parameters in the construction industry. The application of modern AI technologies is considered as a new paradigm of the technological development of the construction industry, which forms fundamentally different mechanisms for organizing the design, construction of facilities and management of construction processes. The research methodology is based on a synthesis of quantitative and qualitative approaches, including a multifactorial analysis of the economic efficiency of construction projects, an assessment of organizational and technological transformations, and modeling of production processes. The empirical base consists of data on the implementation of DeepSeek solutions in 47 construction companies of various scales for the period 2020-2023. The results demonstrate a significant correlation between the integration of AI systems based on large models and a reduction in design time (by an average of 42.7%), while reducing construction and installation costs (by 18.3%). The nonlinear nature of the dependence of performance indicators on the degree of digital maturity of construction organizations (coefficient of determination R2=0.81) is revealed. It is established that the maximum economic effect (ROI>187%) is achieved with the system integration of AI solutions with information modeling technologies (BIM) and automated construction management systems. Four key mechanisms of the influence of large models on the construction industry have been identified: generative design, predictive defect and risk analysis, algorithmic optimization of building materials logistics, and component robotics of installation operations.
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References
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