Kelly Boorman is national head of construction and a partner at RSM UK
One of the construction industry’s biggest challenges, particularly in the past four years, has been managing rising costs and shortages of materials and labour. This has been further exacerbated by the industry’s data capture practices, which are often slow to incorporate changes and require human intervention to forecast costings and outcomes. Currently, the early design and planning stages of a project are key to success but require a significant amount of time to asses a project’s viability, allocate resource and funding, mitigate risks, and manage schedules.
“Robotics could advance to perform remote walkarounds and project management of sites”
Given these challenges, it’s logical to explore how the industry could best implement generative AI at the vital design, planning and delivery stages – to reduce overheads, transform the supply chain and ultimately boost financial outcomes. So how could generative AI technology help the construction industry?
Learning from the past
Generative AI allows businesses to leverage algorithms that learn from historical data – meaning organisations can automate the creation of various design options for each phase of a project. Most importantly, this not only speeds up design creation, but optimises designs based on successful outcomes from previous projects, allowing the incorporation of historical insights and efficiency into the creative workflow. Instant changes can be made to the scope and technical outputs of a project, enabling design teams and contractors to respond more efficiently to customer enquiries.
Through the use of 3D infra-red technology, drones, robots, and wearable devices, the industry can now gather data from a variety of locations, including spaces previously inaccessible to humans. This wealth of data sources allows businesses to gain a more comprehensive understanding of the built environment. It also enables them to design the most efficient and sustainable outputs, tailored to their customers’ needs.
Access to this data enables collaboration within the supply chain, too. Generative AI can quickly identify design issues ahead of the build. Organisations can then share this insight and information with their supply chains, allowing them to respond to any necessary changes. We’re also seeing the benefits of generative AI in data and capture storage, with construction businesses using this technology to swiftly adjust contract costings, apply complex pricing models, and adapt flexibly to contract design changes and emerging issues.
Currently, the industry heavily relies on a protractive supply chain from design to delivery, with technical expertise, project managers and manual workers. In the coming decades, these roles could be performed by generative AI. Customers might use generative AI to design their own buildings and assets, while technology could oversee project management and performance reporting, providing real-time activity updates from the comfort of their homes and offices.
Robotics could also advance to perform remote walkarounds and project management of sites, which coupled with site vehicles controlled remotely and supported by routine drone surveying to check on progress, could really change what a construction site looks like and how it operates. As data capture evolves, construction businesses will be able to download the data captured and analyse progress and assess risk remotely.
However, this does pose the question: who in the supply chain will be responsible for owning that data and using it to inform decision making? Or will generative AI take on that responsibility as it develops?
Ultimately, there will be a phased transition. Contractors and suppliers will integrate new technology and pilot modern methods on construction sites over many years. So while a fully remote site managed and controlled by generative AI is some time away, it will become the reality of future construction sites.
Planning regimes, health and safety regulation and data capture all create challenges for generative AI but it remains a great opportunity to boost productivity in the supply chain and tackle labour shortages. Only time will tell which direction the industry will take.
