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5 Real-World Use Cases for AI in the Construction Industry

Possibly the most revolutionary change we discussed in our 2019 Trends blog post centered around the impact of artificial intelligence (AI) and machine learning on the construction industry. AI and and machine learning techniques are becoming more prevalent in engineering and construction, as a way to optimize operations and identify potential time and cost savings.

And reducing the cost of construction is critical – According to a 2017 study by Mckinsey and Company, individuals and businesses spend $10 trillion per year on construction-related activities.

In the study Mckinsey and Company looked at potential use cases of AI for the construction industry, from pre-construction to operations and asset management. They found a growing focus on using AI to help companies in the industry overcome challenges related to cost, scheduling and safety. Predictive analytics are being applied by newcomers in the space who are creating applications that collect thousands to billions of data points from various source systems, such as equipment sensors, project management software and other tools used by construction firms. These startups are developing tools to apply AI and machine learning to the data to optimize decision making around workloads, staffing and jobsite efficiencies.

What is AI? It’s a term to describe when a machine or software mimics human cognitive functions, such as problem-solving or pattern recognition. Machine Learning is a subset of AI, and refers to the ability of a machine to get progressively better at completing tasks by continuously analyzing and re-analyzing new data. In construction, data can be collected and fed into machine learning algorithms before and during construction, to improve schedules and planning, enable more precise materials ordering, prioritize maintenance, prevent downtime, and track and assess labor productivity.

There are innumerable applications for AI-based tools and software. Here are a few real-world scenarios in which AI and machine learning algorithms can help construction firms operate more efficiently and cost-effectively.

  1. Iterative Design via 3D Modeling. AI and machine learning algorithms are being used to enable designers to explore variations of a building’s design prior to execution. By producing 3D models of mechanical, electrical, plumbing and other systems, firms can ensure various design elements don’t interfere with each other and work harmoniously with the building’s architecture — before schedules are set and materials are ordered. 3D modeling tools enable iterations based on new input collected during the planning process, leading to the best-possible outcomes. Machine learning algorithms can be applied to 3D models captured by drones and cameras to detect design errors, eliminating costly rework and design flaws.
  1. Enhanced jobsite productivity. Drones have garnered a lot of attention from construction firms looking to reduce time spent on site surveys, or enhance marketing activities with aerial footage of construction projects. Companies are also beginning to deploy AI-driven machinery for completing difficult or repetitive tasks, such as demolition or welding. Equipment sensors can alert project managers to potential failures, so problems can be addressed early, helping to avoid downtime and project delays. And offsite construction is often facilitated by AI-powered robots that construct building components via assembly line more efficiently than humans can. According to the Mckinsey report, construction firms could boost productivity by as much as 50% using predictive analytics.
  2. Jobsite safety. Image recognition and classification algorithms can mine data collected from construction cameras mounted throughout the jobsite, to help inform training and safety practices or identify potentially unsafe worker behavior. They can also help project managers identify and analyze safety hazards, before injuries can occur and lead to lost productivity and costs.
  3. Scheduling. AI-based project management applications can apply AI and machine learning algorithms to various data collected by people, sensors, drones, cameras and other sources. Then can analyze jobsite progress in real-time, and track it against original schedules, make adjustments as needed, and keep projects on-time and under budget.
  4. Combatting the labor shortage. The construction industry has been squeezed by a labor shortage for the past few years, and AI is one way to loosen the grip. AI can be used to optimize labor and machinery distribution across jobsites. AI can also help predict attrition rates, identify leaders, assess employee satisfaction and keep workers engaged, eliminating attrition costs and optimizing the use of individuals’ skillsets.

A new report from Narrative Science and the National Business Research Institute found 61% of businesses implemented AI in 2017— up from just 38% in 2016. That’s a huge jump and indicates that AI is coming into the mainstream. The E&C industry is a bit late to the game; but that could work in its favor. It will benefit from the work of other industries in developing AI-powered technology. Expect to see an uptick in the use of AI and machine learning, as firms continue to realize tangible benefits.