The global construction industry, known for its traditional practices and resistance to change, has historically been slow in embracing digital advancements. However, in recent years, the emergence of artificial intelligence (AI) has showcased its immense potential to revolutionise the construction sector on multiple fronts.
A Merit expert adds, “From managing delays and preventing cost overruns to mitigating construction site risks and enhancing project management, AI has demonstrated its ability to positively impact various aspects of the industry. Furthermore, AI has proven instrumental in addressing persistent challenges such as labour shortages, making it a game-changer for construction professionals worldwide.”
A 2023 report by Mordor Intelligence shows that the AI adoption in global construction is expected to reach USD 9.35 billion in the next five years, growing at a CAGR of 24.30%.
It further adds that organisations in this space have turned to advanced technologies primarily driven by the need to reduce production costs and to meet the growing demand for safety at construction sites.
In our earlier blogs, we looked extensively at how construction technologies like business intelligence and project management software, visualisation tools, data warehousing software, and IoT technologies have been impacting construction projects from the design and planning stage to post-construction stage.
In this blog, we’ll go into the specifics, and share examples of 8 areas where AI has and can bring more efficiency, cost cutting and productivity improvements in construction projects.
AI Application in Site Selection & Planning
AI analyses vast amounts of data, including geographic, environmental, and demographic information, to aid in the process. It considers factors like soil conditions, transportation accessibility, local regulations, and market trends, and identifies optimal locations for construction projects.
GeoSpatial AI optimises site selection with geospatial data
For example, GeoSpatial AI is a site selection and planning tool which uses machine learning algorithms and geospatial data to assist in the decision-making process for site selection. It analyses factors such as land usage, environmental conditions, proximity to amenities, transportation infrastructure, and market trends to provide valuable insights for construction companies in the region.
AI Application in Cost Estimation and Bidding
AI algorithms analyse historical project data, material costs, labour rates, and other relevant factors to generate accurate cost estimates for construction projects. This not only reduces human error but also improves the speed and accuracy of bidding processes.
Esti-mate gestimates costs for contractors
For example, Esti-mate uses AI-powered assists contractors in generating accurate cost estimates for their bids, enabling them to make competitive and profitable offers.
AI Applications in Design & Planning
AI-powered tools enable architects and designers to generate complex designs and visualisations quickly.
By feeding design parameters into AI algorithms, architects can generate multiple design options based on specified criteria, such as building materials, energy efficiency, and structural integrity. This helps in optimising the design process and allows stakeholders to visualise the project before construction begins.
Autodesk’s generative design technology, for example, creates multiple design options for structures based on predefined goals and constraints.
AI Application in Tracking Site Progress
AI-powered systems analyse real-time images or video feeds from construction sites. By leveraging computer vision algorithms, these systems identify and track specific elements, such as completed tasks, installed components, or the overall percentage of completion. This enables project managers to accurately assess site progress in real-time.
3D models created from aerial photography by Pix4D
For example, Pix4D uses AI algorithms and computer vision to measure site progress. It uses aerial imagery captured by drones to create accurate 3D models of construction sites. These models enable stakeholders to remotely assess progress, identify deviations, and make informed decisions regarding project management and resource allocation.
AI Applications in Project Management & Collaboration
AI enhances efficiency, decision-making, and communication. Aconex, for example, is a project management software that utilises AI algorithms for data analysis and predictive analytics. It allows project teams to collect and consolidate project data, such as documentation, drawings, and communications, in a centralised platform. AI algorithms then analyse this data, providing insights on project progress, identifying potential risks, and offering predictive analytics for better decision-making. This helps project managers proactively address issues, optimise resource allocation, and ensure timely project completion.
Additionally, AI-powered chatbots and virtual assistants integrated into project management platforms, such as Synergy and Procore, enhance collaboration by providing real-time communication, automating routine tasks, and answering queries. These AI applications in project management and collaboration enable construction teams to streamline processes, improve project outcomes, and foster effective communication among stakeholders.
AI Applications in Construction Fleet Management
AI optimises operations, improves efficiency, and enhances overall fleet performance. Ctrack, for example, utilises AI algorithms to collect and analyse data from vehicle telematics systems, including GPS tracking, engine diagnostics, and driver behaviour. This allows fleet managers to monitor real-time vehicle locations, track fuel consumption, assess driver performance, and identify maintenance needs. AI algorithms can also generate predictive maintenance schedules, minimising downtime and maximising fleet availability. By leveraging AI, Ctrack enables construction companies to optimise route planning, reduce fuel costs, improve driver safety, and enhance fleet utilisation. Additionally, AI-powered fleet management platforms offer advanced analytics and reporting capabilities, providing valuable insights into fleet performance and enabling data-driven decision-making.
AI Applications in Construction Site Safety
AI enables proactive risk management, real-time monitoring, and accident prevention. Safesite, for example, utilises AI algorithms to analyse data from various sources, including sensors, wearables, and CCTV cameras, to detect and predict potential safety hazards. By monitoring factors such as worker behaviour, equipment usage, and environmental conditions, AI algorithms can identify unsafe practices or conditions and provide real-time alerts to supervisors and workers.
Additionally, AI-powered computer vision systems can detect safety violations, such as workers not wearing appropriate personal protective equipment (PPE) or improper equipment usage.
Furthermore, AI applications in construction site safety offer data analytics and reporting functionalities, allowing companies to identify trends, assess safety performance, and implement targeted safety improvement measures.
AI Applications in Addressing Labour Shortages
AI addresses labour shortages by offering innovative solutions to enhance productivity and fill skill gaps. Robotic construction technologies, such as bricklaying robots like SAM (Semi-Automated Mason) are an example of innovative labour management. SAM is equipped with AI algorithms that can autonomously lay bricks, reducing the need for manual labour and increasing construction efficiency.
Furthermore, AI-powered construction project management platforms, like PlanRadar, enable better resource allocation and workflow management, maximising productivity even with a limited labour force. These platforms leverage AI algorithms to optimise scheduling, streamline communication, and automate processes, helping construction teams accomplish more with fewer workers.
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