i-manager Publications

Risk Reduction in Construction Projects through Datadriven Technology: A Literature Review

Arun Chandramohan*, Sathish Kumar Raju**, Onkar Krishnakant Chothe***

*-*** NICMAR University of Construction Studies, Hyderabad, Shamirpet, Telangana, India.

Periodicity:July - September'2025

Abstract

The integration of data-driven technologies within construction project management has emerged as a pivotal strategy for risk reduction. Project managers can identify potential risks early by applying advanced analytics, machine learning, and artificial intelligence so that they will take prompt action with proper decision making. This makes it easy to plan for roadblocks as well as resource distribution, thereby enhancing project outcomes. However, importantly, these technologies augment human ability rather than replace it and turning the insights of data into actionable plans requires data analysts, engineers, project managers to work together. Continuously researching and investing in more advanced data-driven tools are key to the evolution of risk management strategies in construction. By reaping the benefits of technology and staying ahead of trends, construction companies can take on complexities and uncertainties with great assurance. This makes us a continuous development and excellence organization. The study highlights the importance of preventing risks by using data-driven technologies to improve communication, decision-making and project efficiency. Suggestions for future research includes moving towards complex predictive analytics models and integrating AI and VR to enhance risk assessment and training, with the aim of developing a safer and more resilient built environment.

Keywords

Artificial Intelligence, Predictive Analytics, Big Data, Risk assessment, Risk Mitigation.

How to Cite this Article?

Chandramohan, A., Raju, S. K., and Chothe, O. K. (2025). Risk Reduction in Construction Projects through Datadriven Technology: A Literature Review. i-manager’s Journal on Civil Engineering, 15(3), 56-69.

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