AI: Improving the Digital Toolbox of Construction
The construction industry has been ‘behind the bit’ in the deployment of artificial intelligence solutions. Despite a growing focus on the impact of AI powered solutions within the industry, a report by McKinsey showed that few construction firms or owners currently have the capabilities—including the personnel, processes, and mechanisms—to implement such tools. As the construction and engineering landscape is transformed by the advance of technology, firms need to position themselves as the engineers of the future, embracing these emerging technologies.
Optimization of Risk Management
AI powered solutions such as predictive analytics, have the capability to reform everything from planning and design, to maintenance and risk management. Forecasting project risk such as structural complications, the application of predictive analytics has the potential of saving construction firms millions of dollars. Utilizing predictive data and machine learning to predict potential high-risk complications, can provide actionable insights for the challenges that construction managers and contractors face every day in terms of risk-mitigation.
Automation of Project Management
Deploying robotic process automation within automation can track project progress, in real-time against original plans, budget, and schedule. Utilizing this progressive information can also track efficiency and suggest deviations to keep a project on plan. AI-powered solutions used to measure the progress of a project, can also apply machine learning algorithms to measure the quality of work, measuring against design plans to detect faults and discrepancies.
Enhancing Employee Productivity
Employee productivity can also be improved through the use of AI solutions. Tracking the movement of resources across a site produces data that can then be analyzed to suggest solutions that reorganize the location of resources, improving accessibility and reducing downtime. Artificial intelligence powered solutions help improve productivity, which shortens construction times, lowers costs and therefore increases potential profits on every project. Applying predictive analytics to examine the hours spent on labor, production progress and idle time, allows for logistic determination and more accurate task scheduling.
The Bottom Line
The integration of AI and machine learning technologies into the planning, design and production workflows of the construction industry, will see increased completion of projects, both on schedule and on budget. Early implementation will set the direction of the industry, securing the place those firms at the front-line of integrating AI applications into the construction industry.