DACK Consulting Solutions: AI Technology Transforming Construction

As AI technologies evolve, their role in construction processes will increasingly become indispensable. Organizations must stay ahead of this curve and embrace these changes to tap into newer opportunities for cost savings, productivity gains, and sustainable growth.

Bhavin Lakhani - Project Controls Specialist Lead, PMP, CCM, DACK Consulting Solutions

The construction process, even in the most advanced countries, is largely fragmented and low-tech despite numerous technological breakthroughs. One common misperception regarding artificial intelligence (AI) is that it aims to replace human labor in the construction industry, which has historically resisted technological advancements. AI should be considered as a tool that could support, augment, and enhance some aspects of the processes within the construction industry. The ideal strategy would be to embrace AI to boost efficiency, productivity, and safety in the construction industry.

AI can transform many aspects of the construction process, from project planning and design to on-site construction and post-construction operations, through modern robotics, machine learning algorithms, and data analytics.

How AI can transform construction

Predictive Analytics: By utilizing past project data and experiences, AI algorithms could predict potential future delays, cost overruns, and quality issues. AI algorithms have the potential to analyze supply chain data and suggest optimization in the procurement of materials, inventory management, and logistics.

Risk Management: AI can assist in analyzing various factors like project complexity, market conditions, and stakeholder dynamics, which are vital inputs for assessing project risk. AI-powered risk management systems can provide early warnings for potential problems and suggest mitigation strategies to minimize their impact on project outcomes. Through prediction of material demands, alternative suppliers, and route delivery optimization, AI has the potential to reduce construction costs and minimize delay of the project.


Optimized Scheduling: AI-based scheduling algorithms can assist in the development of the most optimal construction plan by considering site logistics, resource availability, constraints and limitations, and predicted weather conditions. To give a case study in brief, Crossrail, with its innovative rail project running three years behind schedule, needed a solution that could help it achieve a “done status as efficiently as possible. Crossrail implemented AI with the following objectives to accomplish its goal:

• Integrate disparate data into dashboards that look forward to.
• recognize high-risk activities and bottlenecks that need immediate attention.
• confirm the remaining project timeline; and track real-time progress.

With the use of AI-based scheduling, Crossrail accelerated delivery by almost a year, enhanced run-rate by 400%, and prevented delay-related expenses of over 300 million pounds in the UK.

Cost Estimation: Integrating BIM models with AI streamlines the estimating process by allowing seamless transfer of data between BIM model and estimating software, thereby eliminating the need for manual data entry, and reducing the risk of errors. AI can further be utilized to analyze vast amounts of historical project data, including material costs, labor rates, equipment expenses, and project timelines to identify patterns and trends that can be used to develop more accurate estimates based on past project experiences.

For example, before Coastal Construction used AI estimating takeoff software, the Coastal Construction team spent about 50% of their time manually tracing, clicking, and dragging lines on a set of plans to perform a takeoff using on-premises software. AI helped Coastal Construction estimators reduce the time needed to take off from 50% to 10%."

AI was able to scan through floor plans and perform quantity take-offs; identify changes between different versions of the drawings and quantify those modifications, thus saving estimators hours spent on manual take-off software.

AI simplified the workflow by enabling multiple estimators to simultaneously work on a single project from any location or device.

Quality Control: A project expense tracking system powered by AI may have the opportunity to identify cost-saving opportunities and provide a forward-looking outlook for prospective expenses. Analyzing photos and video footage from construction sites using machine learning algorithms for image recognition may permit one to identify defects, hazards to safety, and regulatory compliance issues.

Performance Monitoring: AI-powered monitoring systems can collect and analyze real-time data from sensors, drones, and IoT devices deployed on construction sites that can be utilized to enhance the ability of project managers to identify inefficiencies and proactively improve performance through the monitoring of key performance indicators such as productivity, equipment utilization, and safety compliance, among others.

Decision Support: AI algorithms can assist stakeholders and project managers by analyzing a large amount of data to provide insights and recommendations to assist with various decision-making including the selection of the optimal construction method, choosing the ideal design, and even making decisions for optimizing resource allocation. In general, AI can revolutionize project controls in the construction industry since its use will result in more informed decisions, process efficiency, and a better project outcome in terms of cost, schedule, quality, and safety.