13th Sep 2024
The impact of artificial intelligence (AI) and machine learning (ML) is a relentless topic of debate for industries with ingrained traditional processes that are now becoming frustratingly outdated and unable to cope with modern day expectations.
For construction, renowned for being a traditional industry that is slow to implement emerging technologies, conversations about AI and machine learning point to many benefits but also challenges for widespread adoption.
AI enables computers and machinery to complete tasks by imitating the way humans think, make decisions and solve problems. Machine learning is a branch of AI. It analyses data to make predictions about outcomes and uses the information to teach computers and machines how to perform tasks. Machine learning accelerates AI processes to a level that couldn’t be achieved by humans.
According to a recent study, AI and machine learning algorithms address challenges that are specific to the construction industry such as estimating costs, monitoring health and safety, predicting risk and enhancing supply chain and logistics processes.
AI and ML algorithms help to optimise project planning by processing enormous volumes of data. The algorithms can suggest alterations to designs that improve energy efficiencies, structural integrity and functionality.
Construction companies that use AI can optimise essential tasks such as project planning, scheduling and resource management to reduce costs and achieve improved efficiencies.
Using BIM (building information modelling), AI and machine learning can provide predictive analytics that tell construction firms when equipment or structures are likely to fail which reduces risk and improves safety.
AI can monitor the quality of construction products or materials and highlight incompatibility with current or proposed systems. The introduction of AI quality control tools, such as that being researched and piloted by Kingston University and UK construction company Galliford Try, are aimed at improving quality and risk management.
A Building Magazine article outlines how AI allows contractors to forecast carbon emissions of projects in the planning stage while ML is used to identify where a change of materials can make huge ongoing reductions in emissions. This also generates savings in the cost of potential rework that would be needed at a later date to bring a building to within emissions guidelines.
In UK construction projects, AI and ML are increasingly used for project management, risk assessment and design optimisation. The adoption of machine learning is the solution to processing the large volume of data that is now unavoidable in construction, and increased automation.
A PBC Today article identifies that the potential for a safer, more efficient and productive industry through emerging AI and machine learning technologies offers a tangible path to wider adoption.
Data privacy concerns have been identified as challenging the use of AI and machine learning in construction, while research has found that the cost of implementation of new technologies is a leading barrier. A legacy-based technology landscape is also limiting the potential for the use of new, emerging technologies.
Likewise, the need for specialised expertise continues to impact wider adoption. An article in Facilities Management Journal cites that, ‘while 76% of leaders report a high level of architectural readiness for AI adoption, concerns about the quality of AI resources, particularly human skills, persist’.
With a keen eye on future potential, there is certainly an appetite for AI and machine learning within the built environment, despite the challenges. In September 2023, Innovate UK launched a £32m AI fund for innovation projects that improve construction productivity through the use of AI and machine learning.
It is expected that the future of AI and machine learning will involve greater integration with BIM, more smart buildings, and the increased use of autonomous construction equipment.
By harnessing the power of emerging technologies, the CCBP aims to improve construction project outcomes across all stages – design, delivery and operation. This focus on technology is key to driving efficiency, accuracy, and collaboration in construction projects.
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