This study is about the effectiveness of artificial intelligence (AI) applications in managing risks in construction industry. The aim is to explore the capabilities of AI and automation for a better risk management. Secondary research using Science Direct is conducted to assess the capabilities of AI in risk management. Risks faced in the construction sector such as safety incidents, schedule setbacks, cost overruns, and delays in the delivery of materials. To address these issues effectively, a thorough analysis and implementation of mitigation strategies are essential. Adopting a data-driven strategy, facilitated by AI, machine learning, and sophisticated data collection technologies, can significantly enhance risk management. These tools allow for real-time analysis, offering a substantial benefit in proactively managing risks. Given that construction projects often differ greatly in terms of location, weather, and other factors, risk management must be tailored to each project's specific needs, relying heavily on data analysis and forecasting. AI excels at sifting through large volumes of data to identify trends and make accurate predictions, thereby playing a pivotal role in enhancing risk management strategies through proactive analysis. However, the major finding is that despite the success of the advancements in AI, the construction industry faces challenges in prompt adoption of advanced technologies. These challenges are mostly caused by the cost and time needs to be invested as well as the lack of knowledge about advanced technologies. This requires further studies to find appropriate methods for implementation of advanced technologies for construction industry.
Permanent link to this resource: https://doi.org/10.24384/CS7A-DY50
Isik, Erhan
School of the Built Environment
Year: 2024
© Isik, Erhan