Artificial intelligence in the construction sector according to Buildots

But what about the construction sector? Robotic technology falls far short of being able to handle the complex environment and conditions of a construction project, and ChatGPT is of little use when it comes to installing Placoplâtre.

So what can AI bring to this sector? The answer is, of course, data and analytics.

The data gap

A construction company has mountains of data. Health and safety records, financial reports, HR data and, in recent years, with the introduction of digital tools such as Procore, even information on the most common quality issues. The only missing piece, however, is the data describing the actual construction process.

How many glass panels can the tower crane lift in a day? How long does it take to install duct pipes on one floor? What is the ideal number of workers to install Placoplâtre in an apartment?

All of these questions, and even simpler questions like "How many switches are installed on the project? We are missing information because we don't have data to analyze.

This lack of data is easily explained. The construction process includes tens of thousands of tasks, performed by hundreds of people from dozens of different companies. It is virtually impossible to collect data on such a process, which, for the most part, is conducted manually in a physical, not digital (and sometimes temporary) environment. This means that these dozens of companies are all required to contribute, to instruct hundreds of people to report on what is happening, and then they must consistently deliver on those expectations. It's practically impossible. Another way to collect the data is to send someone from the GC team to do it, but that means sending someone who is overworked and extremely busy with management tasks to collect precise data. This would take hours and is completely unrealistic.

Is data really important?

One could say that the data we are currently missing is not that important. After all, the industry has been carrying out projects without such data for decades. The problem, we all know, is productivity. A recent study conducted by Buildots showed the missing link between productivity and results, namely the efficiency of project execution.

The results of the analysis of 64 construction projects showed how inefficient modern construction is. Statistics such as average floor space utilization rates of just 46%, meaning half of a project remains unused at any given time, are nothing short of staggering.

The basic rule is that “you can't manage what you can't measure”, and this is the central problem. Without measurements, without data, any attempt to tackle these inefficiencies is almost doomed to failure.

AI for data collection

The good thing about computers is that they don't have opinions, they don't get tired, and they can work overtime without any problem. If we can simply set up an AI to follow all the tasks mentioned, it will do so with a pinpoint level of accuracy and won't get bored or distracted by other matters.

At Buildots, we've built an AI system that can accurately track the installation of items on site, providing exact completion percentages and deviations from design. It does this by researching every item in every room, installed by any subcontractor, and comparing the reality on the job site to the design and schedule.

Buildots is of course just one solution among others. There are other technologies that collect a variety of data directly on the job site. These include, for example, solutions that track the exact performance and activities of the tower crane, or provide information on the exact time workers spend on installation compared to other tasks (such as as the transport of materials to the site).

It would take an army of human resources to keep track of all of these elements, and it still wouldn't be enough. In an average week, these systems can determine the status of tens of thousands of items per project. No human being is capable of this and should not be.

The lack of analysis

Construction is one of the most complex processes in the world. Sure, building a wall may not be that complex, but it is extremely difficult to ensure that the entire process is done correctly and moving in the right direction.

With so many things going on and different dependencies, it is often very difficult to identify not only the current gaps, but also their root cause. Is the drywall installation delayed because there wasn't enough work this week, or because the electrical work delayed it and caused the rate of drywall installation to drop?

If reaching each conclusion requires sitting down and questioning what happened over many weeks, often involving several different parties, we often try to avoid this lengthy process, opting instead for work based on instinct and intuition. It is this intuition of construction professionals that gets projects done, but it has its limits, particularly as construction becomes more complex and average levels of experience in the industry decline rapidly.

Artificial Intelligence for Analytics

Once again, AI is the perfect answer to this challenge. AI can quickly and automatically analyze all the information and come to the conclusion we were looking for - allowing project managers to use these conclusions and make the right decisions. Of course, this assumes that the information exists, hence the need to collect data.

Using AI for this purpose not only allows for more conclusions, but also for conclusions that are easy to act on. In effect, data becomes a third party that shows the entire project team the objective truth of what is happening and what has happened. So instead of discussions and opinions, the team only has facts, allowing them to process them more effectively.

Closing the experience gap

The construction industry also faces a major challenge globally: there aren't enough experienced project managers, and people are often assigned to roles for which they are not yet fully qualified. AI can ensure that everyone has access to the right information, enabling experienced executives to use their experience effectively and enabling them to support those who report to them, helping them not only succeed in their role, but also to learn quickly.

AI for construction is still in its infancy, but major benefits can already be reaped. Understanding how to use AI and what problems it can help solve can enable construction companies to increase their efficiency and profitability, and help the entire industry address the major challenges it faces.