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Analysis / Business

How Artificial Intelligence Is Helping Build The Construction Industry

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The construction industry has already witnessed the use of artificial intelligence within its workplace. Machines are used to carry out physical tasks such as bricklaying, and are used to support project planning phases. Indeed, machines have their own complex form of understanding via algorithms that allow them to collect information and use it to solve problems and tasks. From design to construction, we’re with Oasys, specialists in column design software, looking at the ways the construction industry is beginning to use AI effectively to complete projects.   

Artificial intelligence: the four categories

We are exploring the four main components of artificial intelligence in use within the construction industry:

Design & planning

The planning stage of construction benefits from the help of AI, collecting data for plans. Autonomous equipment is considered as AI as it is aware of its surroundings and is capable of navigation without human input. In the planning stages, AI machinery can survey a proposed construction site and gather enough information to create 3D maps, blueprints and construction plans. Before the use of robotics, planning processes took weeks to complete. Now, it can be done in a day. This helps to save firms both time and money in the form of labour.

Project management

AI can also take on administrative duties, helping with managing projects. For example, workers can input sick days, vacancies and sudden departures into a data system and it will adapt the project accordingly. The AI will understand that the task must be moved to another employee and will do so on its own accord.


Engineers are now told how to finish certain tasks and projects via AI databases. For example, if engineers were working on a proposed new bridge, AI systems would be able to advise and present a case for how the bridge should be constructed. This is based on past projects over the last 50 years, as well as verifying pre-existing blueprints for the design and implementation stages of the project. By having this information to hand, engineers can make crucial decisions based on evidence that they may not have previously had at their disposal. Vehicles can now be left to work autonomously at dangerous heights, with the driver outside of the vehicle. Using sensors and GPS, the vehicle can calculate the safest route.

Post – construction

The impact of AI doesn’t end with the project, as many buildings involve AI systems long after the completion of construction. In the US alone, $1.5 billion was invested in 2016 by companies looking to capitalise on this growing market. Wynn hotels, for example, said it would install an AI system in the form of Amazon Echo to each of its Las Vegas hotel rooms by the end of 2017. These devices can be used for aspects of the room such as lighting, temperature and any audio-visual equipment contained in the room. These systems can also be used within domestic settings, allowing homeowners to control aspects of their home through voice commands and systems that control all electronic components from one device.

BIM: building information modelling & retrospective assessment

A building’s whole history from construction to demolition, can be catalogued using building information modelling (BIM). The information gathered by BIM can be accessed and reported by a Virtual assistant (VA). By combining VAs alongside NFC (near-field communication), VAs can be given additional information to the building itself in real-time from various sensors in the building. For example, if there were structural problems with a building, then VAs could inform engineers specifically where the problem was and how it can be fixed.

In place of once-expensive and time-consuming labour, the construction industry now has the option of AI and VA methods. As the future of AI becomes more of a reality within construction, only time will tell how reliant upon intelligent machines we will have to be in order to construct innovative building designs.

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Professor Peter Debney is a chartered engineer with over 30 years of engineering experience. He is a Member of the Institute of Structural Engineers and a Royal Academy of Engineering Visiting Professor at Bradford University, where he teaches design and computational engineering. Peter is the application specialist for the pedestrian and structural programs at Oasys, the software house of Arup. Peter has particular interests in nonlinear analysis, optimisation, and artificial intelligence applications.