How Artificial Intelligence Can Transform Construction

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.

How Artificial Intelligence Can Transform Construction

Read the full article on

Artificial intelligence and machine-learning algorithms have struggled to make sense of chaotic construction jobsites, but recent years have seen industry firms build the vast data lakes and analytics systems necessary for these machines to provide useful advice on how to plan, schedule and execute projects. In some cases, these AI advisors have become a standard part of some firms’ project delivery methods. But it’s still a challenge to convince construction professionals to listen to these AI advisors, and there are emerging questions of how risk will be allocated once algorithm-driven decisions start to steer projects.

One of the more direct uses of AI in construction has been the project scheduling analysis performed by ALICE Technologies’ machine-learning algorithm, ALICE. The company has made inroads into the industry in recent years (ENR 5/28/18 p.22), but founder René Morkos says that construction may be approaching a tipping point when it comes to AI adoption.

“What I always hear from people [in the industry] is that ‘I really like scheduling, but the number crunching is the boring part,’” says Morkos. “Why would anyone in their right mind want to spend time crunching all the constraints on a project? It’s mind-numbingly boring.”

Instead, the ALICE algorithm extrapolates thousands of possible ways of executing a project by running simulations of a project’s 4D schedule and BIM, readjusting as variable inputs are tweaked in the project “recipe.” Users make adjustments to the inputs, and ALICE tells them how it will affect the construction schedule. But Morkos says the idea isn’t to cede decision-making to ALICE. Rather, it’s about automating the process of generating possible alternate schedules.

As more companies make the investment into collecting and properly organizing their project data, Morkos says that technologies like ALICE and other AI-based advisors could lend some firms a real competitive edge. “The fundamental value proposition of the general contractor is changing. This new ecosystem will be all about integrated data systems, and it will be 20 to 30 companies that take home this prize,” he says. “We are incredibly lucky to be living in this golden age of construction technology.”

Planning out staging for the structural concrete on M2, a $150-million, 20-story residential tower within the 5M development in San Francisco, Michael MacBean, project director for key accounts at Pacific Structures, saw the ALICE algorithm as more of an informed second opinion on his own scheduling instincts. “We used it on preconstruction for that project to validate our approach to the project and check our productivity,” he says, noting he got the most out of it by tapping into his own past experience as a project superintendent. “The algorithm is awesome. Its ability to calculate every which way to skin the cat, if you will, gets that much better if you also have human expertise on construction to make it do its best,” says MacBean.

“Why would anyone in their right mind want to spend time crunching all the constraints on a project? It’s mind-numbingly boring.”

René Morkos, PhD Founder + CEO at ALICE Technologies

On the M2 tower, MacBean found ALICE to be a helpful advisor, allowing him to fine-tune his planning without overworking his team. “In a matter of minutes, you can make changes in the way you do your projects. Do you want the crane here or there, do you want eight-hour or 10-hour days, should you recruit 50 workers or 20 workers?”

MacBean was able to validate his approach for the M2 tower and even fine-tune some of the staging for the structural work. “We were able to look closer at how we were cycling formwork on the project, and I was better able to understand my crane demand,” he says. ALICE’s recommendations convinced him to go with a crane-jumped core for formwork instead of a self-climbing core, since the algorithm showed there would be enough crane time available to make it work. “I could have figured that out myself, but it would have taken a very long time. ALICE does some pretty simple math, but it does it very quickly.”

While Pacific Structures and its parent company Build Group are happy so far with ALICE, MacBean says there is a broader industry issue around trusting algorithms. “Selling the idea of putting all this trust in AI isn’t just a Pacific Structures issue, it’s a hurdle for the whole industry,” he says. “It’s a hard thing to talk about. There are a lot of builders across the country with 30-plus years of expertise on how to build.” But MacBean adds that while it can be a slow process to bring AI-based technology like ALICE into construction, it is winning converts among his team.

With the M2 tower erection now going as planned, the next test MacBean has for ALICE will be a high-rise tower in Seattle, currently in the planning phase. For that job, he plans to use ALICE across the entire project, with the whole team engaging with the algorithm’s scheduling recommendations. “Some of these projects are so big, so complex, it can take years for just a couple of humans to consider every way to design and cost it out. But with ALICE, in a few minutes you can have a whole lot of detail on which is the right way to go on a project. That is really powerful to me.”


Continue reading on

See ALICE in action

Request a Demo