Title: Do AI and data science models help construction projects mitigate risks, improve productivity and quality management practices? An outlook from the project organisation's perspective

Authors: M. Nagarajan; R. Ganapathi

Addresses: Alagappa Institute of Management, Alagappa University, Karaikudi. 630 003, Tamil Nadu State, India ' Directorate of Distance Education, Alagappa University, Karaikudi. Tamil Nadu State. India

Abstract: Quality, productivity and risk management in construction projects is always critical. The profitability of the project is lesser as compared to the overall performance of the construction project as opined by respondents. Project quality, project cost control and on-time delivery are positively and significantly related to the overall performance and profitability of construction firms. Further, the overall performance is positively and significantly influencing profitability in construction projects. Furthermore, it is suggested that construction firms or respondents should regularly assess various risks associated with construction projects at all stages and adopt efficient and appropriate risk management practices for attaining a higher degree of performance and profitability. The proposed artificial neural network model will be effective in improving risk management and improve project performance. AI algorithms and data science techniques with deployed models will help to solve the productivity, risk and quality management issues in construction projects.

Keywords: artificial intelligence; machine learning; construction projects; project performance; risk management practices; profitability; quality.

DOI: 10.1504/IJPQM.2026.153321

International Journal of Productivity and Quality Management, 2026 Vol.47 No.4, pp.485 - 503

Received: 02 Jan 2024
Accepted: 13 Jan 2024
Published online: 01 May 2026 *

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