Unlike in finance, healthcare, retail or marketing, the role of artificial intelligence in  the construction industry is still relatively small. However, a recent research report by Market Research Future paints a vivid picture of an industry transformed by modern technology. The report forecasts global AI in the construction market to reach approximately $2,011.4 million by 2023, growing with a 35 percent CAGR from 2017–2023.

Construction Companies Are Eyeing AI 

The reason the construction industry is so keen on adopting the latest AI technologies has much to do with the current labor shortage in the industry. According to the U.S. Bureau of Labor Statistics, there were approximately 183,000 construction job openings in May 2017. A year later, the number jumped to 243,000, an increase of nearly 33 percent. 

To make the situation even worse, it’s estimated that 15 million construction workers will retire or leave the industry within the next decade. Clearly, the situation won’t resolve itself, which is why the industry is shifting its focus to emerging technologies to help alleviate future capacity and productivity concerns. 

What does the future of AI in construction look like? Contrary to popular fears, it looks more like cooperation than competition, which becomes clear when you look at some of the most interesting artificial intelligence applications in the construction industry from leading AI companies. 

Generative Design

Building information modeling, a process involving the generation and management of digital representations of physical and functional characteristics of places to give architects, engineers and other construction professionals the insights to efficiently plan, construct and manage buildings has been around since the new millennium.  

Now, one of the most popular BIM software applications, Autodesk Revit, is able to aid the building design process in a completely new way thanks to a powerful AI-enabled add-on, called GenMEP, which has the ability to automatically design the routing of mechanical, electrical and plumbing systems within buildings while taking into account the complexity in different building geometries and shapes.

The process through which GenMEP figures out the most optimal routing of MEP systems is called generative design, and it can be used to instantly generate multiple CAD-ready solutions based on certain input parameters and design goals, mimicking nature's evolutionary approach to design.

“[Generative design] usually starts with clearly specifying the design goals and then explore innumerable possible permutations of a solution to find the best option,” explains Anand Rajagopal, a data scientist at Autodesk. “In addition to solving vexing practical challenges, generative design could also raise the efficiency and economy of the overall development process by producing designs that improve scheduling and coordination between multiple stakeholders.”

Risk Management

According to the Occupational Safety and Health Administration, construction workers are five times more likely to be killed on the job than other laborers. The combination of uneven terrain, fatigue, tight deadlines and heavy construction equipment is so dangerous that the fatal injury rate for the construction industry is higher than the national average for all industries. Since 2010, construction struck-by deaths have been on the rise, but multiple AI companies would like to put a stop to this trend and apply the benefits of artificial intelligence to increase construction safety. 

One example of such a company is Suffolk. This Boston-based general contractor has amassed a huge database of jobsite photos to create predictive algorithms designed to manage construction risks. The ultimate goal is to transform the construction industry by building smart, and that’s already possible thanks to Suffolk’s partnership with Smartvid.io, a collaborative platform to manage and analyze industrial media using deep learning.

“Over the past couple years, it has become super easy to capture photos and videos on jobsites; now with Smartvid.io and Procore working together, we’re able to easily organize all this visual data and—better yet—use AI to find insights related to quality and safety on our job sites,” said Ajoy Bhattacharya, the senior director of innovation and new technology at Suffolk Construction.

Artificial Intelligent Assistants

Another example of how AI in construction can help improve worker safety and productivity is the use of an AI assistant for safety meetings. Leveraging recent advancements in the fields of natural language processing and machine learning, customizable AI assistants like Hendrix.ai, are transforming safety meetings with the ability to identify and extract key details unique to the organization, providing greater visibility, communication and access to information across teams and worksites. 

Speech-to-text accuracy is light years ahead of where it was just a few years ago thanks to massive increases in computing power and improvements in deep learning techniques, which is evident from the impeccable accuracy of Apple’s Siri, Amazon’s Alexa, Google’s Assistant and other personal virtual assistants. 

In addition to being keen listeners, artificial intelligent assistants are also sharp observers that can review existing safety-related documentation, extract relevant information, such as details surround an incident, and analyze and correlate that information with additional data sets, like weather conditions at the time of the incident, for unparalleled insights into potential causes and opportunities for improving worksite safety as a whole.

It’s becoming clear that the construction industry is about to undergo a major productivity revolution. New artificial intelligence applications seem to emerge nearly every day, and most large construction companies have already started reaping the benefits of artificial intelligence and turning this cutting-edge technology into a strong competitive advantage. Other companies in the construction industry should get onboard this productivity revolution or risk being left behind.