A decade ago, construction was near the bottom of the list of industries that had adopted technology in a significant way. It was a bad rap for the industry, but it also effectively threw down the gauntlet. There’s been a huge shift in the industry as construction companies realize that technology needs to be a core part of their business.

The companies I talk to say they need to reduce risk and build more predictability into their projects. If they can do that, they can be more productive and achieve better margins. Adopting construction-management technology is the first step toward managing risk. When all project-related documents are captured digitally—including things like change orders, RFIs (requests for information), submittals, and issue reports—significant information is amassed and grows with each new project. Machine-learning tools can automate the process, helping find the root causes of persistent problems. From quality issues to safety risks, companies can use big data to identify construction trends and drive better outcomes on future projects.

Adopting construction technology doesn’t stop at automating construction management. Contractors are looking to technology to help deliver better outcomes across the board for their employees, their companies, and their clients. It’s possible to amass enough information in just one to three years to predict the risk factors and make changes to improve performance on future projects.

If contractors use machine learning to benchmark KPIs (key performance indicators) for quality and safety and set goals with a net-positive impact on the business, margins will improve. Ultimately, profits will improve, too. Quality and safety are two of the biggest factors that impact productivity on the jobsite and, therefore, profitability. Anything a general contractor can do to reduce risk, to make sure workers leave the jobsite safely every day, will have a huge impact on its bottom line.

When multiple companies and project teams come together to execute a complex project, there is potential for multiple points of failure. These issues can originate at the design stage and propagate through on-site construction, where they may not be discovered until it’s too late to fix.

Whether it’s a design error that has to be corrected or construction that has to be reworked, mistakes pose real safety concerns on the jobsite. Quality affects safety, and safety affects quality. The challenge is to prevent issues from occurring in the first place.

The solution is identifying the root causes using the abundant data captured by construction technology. Machine-learning tools can predict, flag, and prioritize quality and safety issues that need to be addressed, preventing problems on future projects. Any construction company will tell you that it needs to reduce risk and make projects less complex and more predictable. Technology is the way to do that—preventing frustrating holding patterns and getting the business on a safer and faster flight path.

Construction isn’t just about the manual labor and equipment on the jobsite; technology is a valuable tool in a firm’s toolbox. That’s the mind-set that wins jobs, drives productivity, and delivers better projects. It’s also the attitude the construction industry will need to adopt to meet the tremendous demand for buildings and infrastructure through 2040.

Jim Lynch is vice president and general manager of Autodesk Construction Solutions, where he leads Autodesk’s efforts to create and deliver products and services, which provide the foundation for a digital construction workflow.