“Will robots take my job?”

If you’ve asked this question lately, you’re far from the only one. A current Google search for answers to this question returns nearly 37 million results (as of publication). So, you’d be forgiven for wondering how AI will impact certain sectors: Are robots the new bricklayers in construction? To find the answer for you, GetApp and Gartner (our parent company) asked small business construction leaders how they’re using AI today.

How popular is AI in construction management?

Gartner surveyed 699 small and midsize business (SMB) leaders in the U.S. between April 19 and May 15, 2017. (You can learn more about this survey in our Methodology section at the end.) We asked respondents —all of whom were required to have significant influence over business decisions— how they’re using new technologies like AI. Then, we asked their plans for using these technologies in the future.

Within our broad sample of respondents, here’s what 118 SMB construction leaders said when we asked how they use AI and machine learning (which is a specific AI technique):

Graph showing how construction leaders use AI and machine learning within their businesses

Nearly one in three respondents —32 percent— said they’re currently using AI and machine learning in construction management. By contrast, nearly one in five respondents (19 percent) said they have no plans to evaluate.

But if current predictions about AI’s impact on construction are correct, the latter group should reconsider this choice. It’s not a question of whether AI will impact construction: It already is. The real question is what your construction business will miss if you choose not to implement AI.

AI’s impact on construction

Most projections about job loss from automation are made at a high level, like McKinsey’s forecast that one in five workers worldwide could lose their jobs to automation by 2030. It’s tougher to find insights on how —and, more importantly, why— automation will impact unique industries.

Once you have those answers, a new question emerges: If automation is inevitable, how can your small business benefit from it?

Let’s start by addressing how —and why— automation is changing construction. At a high level, artificial intelligence (AI) is technology that uses techniques like learning and drawing conclusions to mimic human performance. These techniques include using technology to perform routine tasks that are simple and rule-based – aka automation.

Last month, Construction Robotics unveiled a robot mason named “Semi-Automated Mason” (SAM 100 for short). Construction Robotics claims that SAM 100 can place between 300 and 400 bricks an hour— five times more than the average human. Bricklaying is one example of an ideal task for automation that’s simple, predictable, and thus easy for a robot to learn. Since many construction tasks follow this pattern, it makes financial sense to automate them.

For example, the routine task of operating a bulldozer is undergoing automation now. Noah Ready-Campbell, a former Google engineer, founded Built Robotics to “make construction safer, faster and cheaper.” As he shared this sentiment with a reporter, a bulldozer cruised around him sans a human at the wheel.

You, for one, (should) welcome your robot overlords

If you’re scared by those automation examples, consider the benefits they bring to construction. According to CNBC, this rapidly growing sector:

  • Increased spending to a record $1.257 trillion in November 2017;
  • Added 30,000 jobs in December 2017;
  • Added 210,000 jobs throughout 2017; a 35 percent increase over 2016.

There’s just one problem: Not enough humans are available to work. At the same time that the construction industry is booming, fewer people are joining. A net 190,000 new workers entered the industry in 2017, which is well below the prior three-year average of 284,000 annual additions.

The lack of construction graduates from U.S. trade schools is cited as a culprit. Whatever the reasons, a recent survey by the Associated General Contractors of America found that 70 percent of construction firms are having trouble finding the right talent. Gartner found similar responses when we asked SMB construction owners which three external factors were most significant in shaping their organization’s business goals:

Chart of the 3 most important external factors shaping construction leaders' business goals

Our survey found that availability of skilled workers and advances in technology are the top external factors shaping SMB construction businesses in the U.S. These results support the theory that the application of artificial intelligence in construction management isn’t just inevitable: It’s essential to meet demand for the work.

The best news? This isn’t as overwhelming as it sounds. To help you consider application of artificial intelligence in construction management, we’ve shared three ways that AI helps leaders today by:

Classifying project data

Machine learning is an AI technique that’s programmed to learn from experience. Netflix is one popular example. When you give Netflix signals about which movies and TV shows you like to watch (such as clicking the thumbs-up sign), you give Netflix examples of “correct behavior” that its machines can learn from.

The more data you give Netflix about which content you like and dislike, the more accurately it will give future recommendations. This process is used in construction as well.

Dodge Data & Analytics — a construction analytics and market intelligence firm— uses machine learning and natural language processing (NLP) to classify and extract project data that the company shares with customers. The NLP system can give a confidence rating on each document.

If the system gives some documents high confidence ratings, it can automatically send them to customers. If the NLP system is unsure whether a document is relevant, someone from Dodge Analytics can step in to make the final call.

Greg Gies, director of product marketing at Dodge Data & Analytics, told GetApp that his team uses AI to find information within large amounts of data, including construction specs and project plans. Then, his team uses these insights to help clients make decisions in the pre-construction and bidding processes.

Gies added that rather than automation replacing employees, it will enhance the work of sales, marketing, and business development teams within construction. By automating content discovery, AI saves employees hours of sorting through data.

Sorting and ranking future projects

Businesses use AI today as diverse forms of narrow AI, which means they focus on performing specific tasks. This is one reason why fears about general AI— a machine that can perform any intellectual task that a human can— won’t come true in the near future.

Research shows that we are still a long way off from having machines work without humans. Instead, construction leaders can work with examples of narrow AI to solve distinct problems for colleagues and customers.

“For example, today we’re using AI to enable building product manufacturers, distributors, and subcontractors to easily sort and rank future projects based on the specification behavior of architects and engineers,” Gies explained. As a result, managers can make more informed choices about where to allocate resources.

Evaluating future projects’ profitability

Today, NLP technologies excel at analyzing sentiment and creating knowledge graphs. Once you create an initial knowledge graph, you can reuse it for subsequent tasks as well.

This lets machines learn from prior knowledge instead of having from start to scratch each time. To bring this to life, construction leaders can train AI systems to recognize and code specific data, including features of profitable projects.

Gies told GetApp that this allows AI to learn what makes a project profitable— and help construction leaders predict which future projects are most likely to succeed. Currently, a project’s opportunity is measures in metrics like total project value or total square footage. The challenge is that these metrics are rarely tied to revenue and profitability potential.

The good news is that this can be corrected with machine-generated estimates. “In the future, we’ll enable manufacturers and contractors to evaluate the profitability of future projects based on machine-generated estimates of the actual potential opportunity of a project rather than relying on imperfect metrics,” Gies told GetApp.

Want to learn more about AI?

Read these articles to learn how SMBs use AI across these industries:

Methodology

Gartner conducted an online survey between April 19 and May 15, 2017. The survey received a total of 699 respondents in the U.S. They were all required to have more than 10 employees and annual revenue less than $100 million USD.

Respondents were also required to have significant influence on business decisions. Within this dataset, 127 respondents worked in the construction industry.

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