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We are a global management consultancy that delivers exceptional outcomes and sustainable change
Globally, the construction industry generates over $10 trillion in spending each year. It is no wonder that the construction industry is considered one of the largest and most vital sectors. This figure is expected to continue growing at a rate of 4.2% until 2023. The increasing demand for buildings and the growing global population is making the construction industry more critical than ever before as construction projects multiply worldwide.
Technology plays a critical role in enabling this spending, with rapid advancements touching all aspects of the ecosystem. Rapid technological advancements, including machine learning, artificial intelligence, the Internet of Things, drones, virtual reality, augmented reality, big data, cloud computing, blockchain, and robotics, are driving a rapid transformation of the construction industry.
The 2020 report, The Next Normal in Construction: How Disruption is Shaping the World’s Largest Ecosystem, highlighted a growing focus on solutions that incorporate artificial intelligence (AI).
Today, AI is being used to conduct predictive maintenance, monitor safety in construction sites, automate routine tasks, optimize energy usage, and avoid budget overruns.
AI in construction holds the potential to help players realize value throughout project lifecycles, including design, bidding, financing, procurement, construction, operations, asset management, and business model transformation.
AI can streamline workflows, reduce risk, enhance project quality, and even improve the personalized experience that each stakeholder in construction projects may have. AI can benefit the construction industry as a whole by addressing some of its toughest challenges, such as safety concerns, labor shortages, and cost and schedule overruns. As the pace of innovation accelerates, AI is becoming increasingly beneficial in identifying patterns, insights, and opportunities early on in project lifecycles.
As market barriers to entry continue to lower and AI, machine learning (ML), and analytics continue to advance, AI’s significance and the allocation of resources directed towards it will likely play a more substantial role in construction in the future. Therefore, construction firms that adopt AI are better positioned to improve their efficiency, reduce waste, and ensure customer satisfaction—all while minimizing risk and increasing profits.
Read on to discover how AI is used in construction and the ten main benefits of incorporating it into your operations.
Don’t miss out on the potential benefits of AI in your construction operations. With so much to gain, it’s no surprise that AI is quickly becoming a cornerstone in the construction industry.
Artificial intelligence (AI) is a comprehensive term for when a machine replicates human cognitive abilities, such as problem-solving, pattern recognition, and learning.
AI has the potential to revolutionize various industries, from healthcare to finance, by automating complex tasks and providing insights that improve decision-making processes.
Machine learning is a subset of AI that employs statistical techniques to allow computer systems to “learn” from data without direct programming. Machine learning algorithms can be supervised, unsupervised, or semi-supervised, each with its own unique applications. Supervised algorithms are trained on labeled data, unsupervised algorithms are used for clustering and anomaly detection, and semi-supervised algorithms combine the two techniques.
As it receives more data, the machine improves its understanding and generates insights. The more data a machine learning algorithm receives, the better it can identify patterns and improve its accuracy in predicting outcomes.
As a Trimble machine learning engineer, Bob Banfield explains, “Machine learning comprises many algorithms.
There are many different machine learning algorithms, each with its own strengths and weaknesses. Some common types include decision trees, k-nearest neighbors, random forests, and logistic regression.
For example, if you wanted to know whether or not you are at risk of contracting a particular disease, a learning algorithm would proceed through a tree of questions such as ‘How old are you?’ and ‘Do you exercise?’ If you say yes, you go down one path; if you say no, you go down another.
One of the main advantages of machine learning is its ability to automate repetitive tasks and processes, freeing up time for humans to focus on more high-level tasks.
This is a valid machine learning algorithm.
In addition to reducing the workload of humans, machine learning algorithms can also help companies save money by identifying areas for optimization and reducing waste.
It’s similar to the game 20 Questions you used to play as a child, except that in machine learning, these questions are automatically created.”
In construction, the ‘questions’ and algorithms used are significantly more complex. In the construction industry, machine learning is being used to improve safety, efficiency, and productivity. For example, algorithms can analyze data from sensors and other sources to predict equipment failures before they occur, reducing downtime and maintenance costs.  For example, a machine learning program can track and evaluate progress in a grading plan to detect scheduling hazards early.
Machine learning can also be used to optimize construction schedules by analyzing historical data and current conditions to identify potential delays and other risks.
The algorithms may ask questions about cut-and-fill volume estimations, machine uptime and downtime, weather patterns, prior projects, and other inputs to generate a risk score and decide if alerts are needed.
As machine learning technology continues to advance, its applications in construction and other industries will only continue to grow, improving processes and outcomes for both businesses and consumers.
The multitude of potential applications for machine learning and AI in the construction industry is extensive. Standard industry practices, such as requests for information, open issues, and change orders, can be scrutinized, and managed efficiently by machine learning algorithms. These algorithms can act as intelligent assistants to identify and highlight critical issues that require project manager attention. AI has already been implemented in several applications to filter spam emails and monitor safety in advanced ways.
Despite the best efforts of project teams, megaprojects often exceed budget. To mitigate this risk, Artificial Neural Networks can be utilized to predict potential cost overruns based on a variety of factors such as project scale, contract type and the proficiency of project managers. By leveraging historical data, predictive models can accurately forecast realistic timelines for future projects. Additionally, AI offers the opportunity for remote access to training materials which enable staff to improve their skills and knowledge in a timely manner, ultimately expediting project delivery.
Construction projects entail various risks such as safety, quality, cost, and time. As the project size increases, so do the risks involved due to multiple subcontractors working simultaneously on different trades. Currently, general contractors leverage AI and machine learning solutions to monitor and prioritize risks onsite. This ensures that the project team devotes their limited resources and time to addressing the significant risk factors. With the help of AI, issues are allocated priority automatically, and subcontractors are evaluated based on their risk score to collaboratively work with construction managers towards mitigating risks.
Construction companies are now offering self-driving machinery to maximize efficiency on job sites. Tasks such as pouring concrete, bricklaying, welding, and demolition are being performed by autonomous or semi-autonomous bulldozers. By precise programming, these machines can prepare a job site to exact specifications, freeing up human workers for construction work and shortening project completion time. Project managers can track job site progress in real-time using advanced technologies such as facial recognition and cameras to evaluate worker productivity and procedure compliance.
With the increasing demand for efficiency, construction companies have turned to off-site factories staffed by autonomous robots for assembling building components. This assembly-line approach ensures more efficient completion of structures like walls, leaving human workers to focus on the detail work such as plumbing, HVAC, and electrical systems during on-site fitting of the structure.
In today’s fast-paced world, where a vast amount of data is generated daily, AI systems are presented with endless opportunities to learn and improve their performance. Construction professionals and customers can utilize image data from mobile devices, drone videos, security sensors, building information modeling, and other sources to extract valuable insights with the help of AI and machine learning systems. This presents a significant opportunity to enhance the construction industry’s operations and provide customers with even better services.
AI offers long-term benefits for building managers even after construction. By utilizing sensors, drones, and other wireless technologies to gather valuable information about a structure, advanced analytics and AI-powered algorithms can provide insightful details about the operation and performance of a building, bridge, roads, and other components in the built environment. This implies that AI can be effectively utilized to monitor potential issues, identify necessary preventative maintenance, and even direct human behavior, thereby boosting security and safety measures.
Engineers are embracing the use of robotics, AI, and the Internet of Things to enhance the construction industry.
One example of robotics being used in construction is the deployment of drones to capture aerial images and create detailed maps of construction sites. By utilizing virtual reality goggles and mini-robots equipped with cameras, engineers can efficiently monitor building progress. This technology allows project managers to have a comprehensive view of the work being done without having to physically be on-site.
Additionally, AI is being employed to streamline the routing of electrical and plumbing systems, as well as to develop safety systems for work sites.  Moreover, IoT sensors can be embedded in equipment and materials to monitor their condition and track inventory in real-time.
By tracking real-time worker interactions and potential safety hazards, supervisors can intervene before any problems arise, resulting in fewer job errors and injuries. This data can be used to predict maintenance needs, improve supply chain management, and ultimately reduce costs. Although some predict that AI will completely replace human labor, the construction industry will continue to rely on its human workforce for the foreseeable future. Furthermore, while AI may not necessarily replace human workers, it can augment them by taking over repetitive or dangerous tasks, freeing up employees to focus on more complex projects. Â
Companies that prioritize AI investment to enhance operational efficiency are likely to benefit in the short and long term. As technologies continue to advance and become more accessible, the construction industry will undoubtedly evolve to leverage their benefits and improve efficiency.
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Greaux helps businesses maximize their return on investment by identifying opportunities across their value chain and providing practical and sustainable solutions. Our change management expertise ensures the new ways of working are rapidly adopted by the organization and a new culture of working is achieved.
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Our methodology enables to quickly analyse opportunities in any business and commits to delivering business outcomes.
We will analyse how your company can most effectively improve across your value chain and build a practical program with you to implement sustainable solutions.
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As part of the engagement, Greaux has more than 20 years’ experience in taking projects to full adoption using our behavioural and cultural change methodologies.
This approach guarantees that we leave the organisation and your people with the ability to continue growing value long after the project is delivered.
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