No matter how you look at it, heavy and civil construction is very often a labor-intensive, hands-on sector where large and complex projects—bridges, dams, powerplants and wastewater treatment plants—require much human involvement to get over the finish line.

But just because these projects require excavation, concrete work, steelwork, installation, and other heavy lifts doesn’t mean the firms handling them wouldn’t benefit from advanced automation tools. In fact, heavy and civil contractors can use automation and technology to improve efficiency, operate safer jobsites and improve overall project quality.

Take artificial intelligence (AI), for example. The building of smart machines that perform tasks that usually require human intelligence, AI can help contractors improve project planning and scheduling, perform project risk assessments, improve quality control, and manage project materials. Still in the early stages of adoption by construction as a whole, AI could change the way projects are planned, managed and executed.

Here are five AI tools that heavy and civil firms are already using on jobsites today:

1. Job scheduling. The Artificial Intelligence Construction Engineering (ALICE) is an AI construction scheduling platform that optimizes project schedules by applying AI algorithms to project resources and constraints. The program generates schedule sequence options in minutes and lets users quantify the cost and time impact of different decisions by running analyses of different scenarios. For example, ALICE can tell the schedule and budget impacts of adding an additional crew or piece of equipment. ALICE users have reported tangible reductions in project direction as well as labor and cost savings.
2. Submittal and closeout process. Pype wants to help contractors increase productivity and reduce risk by automating submittal and closeout workflows. Pype AutoSpecs uses machine learning algorithms to read and extract specs to generate submittal logs, and Pype Closeout enhances closeout through user-friendly, centralized dashboards with automated document collection features.
3. Quality control. Using data gathered from autonomous drones and rovers outfitted with high-definition cameras and lidar, Doxel AI’s algorithms analyze the data against the building information modeling (BIM) models, schedules, and estimates. The program automatically inspects installed work and provides information on the percentage of the project completed, which informs billings decisions, scheduling, sequencing, and other project management decisions.
4. Estimating. An AI-enhanced preconstruction technology platform, Togal.AI uses machine learning algorithms fine-tuned for automatically detecting, measuring, comparing, and labeling project spaces and features on design drawings. As one contractor stated, “Togal.AI found a way to automate take-offs in a way that will allow our team to focus on scoping, pricing and value engineering.” These kinds of features will help companies save time and money on their already short-staffed projects.
5. Safety monitoring. Newmetrix is an AI platform that uses computer vision or visual recognition and predictive analytics to analyze photos and videos taken from construction sites. It identifies safety hazards and provides feedback to the user regarding best practices. Suffolk Construction recently reported that after 12 months of implementing the program, it reduced recordable incidents by 28% and cut lost time by 35 percent.

As the construction industry continues to evolve, understanding AI’s capabilities and constraints—coupled with an openness to embrace innovation and think creatively—will help contractors remain competitive and address some of their toughest challenges. By integrating AI into their operations, heavy and civil firms can begin to effectively bridge the gap between conventional best practices and the innovations that will shape the future of construction.