The global artificial intelligence (AI) in construction market size was valued at USD 398.6 million in 2018 and is anticipated to exhibit a CAGR of 34.0% from 2019 to 2025. Artificial intelligence has evolved with improved safety standards and assist in predicting hazards at construction sites before they take place. Therefore, the construction companies have leveraged the artificial intelligence technology in terms of predictive maintenance and risk management solutions. Also, the AI in the construction industry is highly adopted for the development of industrial internet of things (IIoT) based applications for construction sites. IIoT assists project managers with efficient outputs and reduced labor costs, which boosts the demand for artificial intelligence in the industry. Construction companies are focusing on investments in IIoT applications development to implement industry 4.0 and support full automation at their job sites.
Construction companies consider safety as one of the major project management factors. Injuries and fatalities at job sites are the ongoing issues at an alarming rate. For instance, in 2017, the U.S. Department of Labor has reported that the death rate of construction workers is five times the death rate of other workers in the private sector. Also, struck-by deaths are increasing substantially, which has pushed the site managers and companies to address workplace injuries. Furthermore, in 2017, around 39% of construction deaths occurred due to unexpected falls at job sites in the U.S., and AI provides increased visibility and predictive maintenance to prevent injuries from these sudden falls. AI-enabled cameras can monitor the whole area around the job site and allow project managers to observe and analyze real-time activities in case some issues are detected. With the help of artificial intelligence, on-site visibility and awareness can be increased to reduce unexpected falls and incidents.
Artificial intelligence has been proven efficient in helping the workers execute tasks more safely. For instance, the University of Waterloo (Canada) researched artificial intelligence in the industry and found that AI technology helps expert bricklayers learn advanced techniques to limit the joint loads. Thus, artificial intelligence has helped bricklayers learn to maximize the output while minimizing the tear on their bodies. Also, AI enables companies to rely on off-site factories or construction sites, staffed by autonomous robots. For instance, wall structures can be built based on assembly-line-style by autonomous robots more efficiently than the human workers at the job site.
Furthermore, AI neural networks are used for construction projects to identify cost overruns. Its predictive model uses historical data such as project start and end dates to envision realistic timelines for upcoming projects. Cost overruns are predicted based on several factors, such as contract type, project size, and the competence level of the project managers. Project managers can plan the project schedule and estimate the original cost and budget with the help of real-time feedback provided by the AI platform. Besides, artificial intelligence helps the company staff access real-life training material to enhance their knowledge and skills quickly.
The offering segment is classified into solution and service. The solution segment is expected to have a larger market share among offerings. Major players, including IBM, Microsoft, and Oracle are offering artificial intelligence solutions for the industry. AI solutions boost on-site efficiency by providing major construction applications, such as risk management, project planning, schedule management, and supply chain management.
Also, artificial intelligence solutions address the problem of skilled labor shortage through the automation of tasks. These solutions can perform time-intensive tasks, such as cost estimation, program creation, resource management, and risk management. Most of the construction companies have adopted AI solutions for risk management and better safety at the job site. For instance, PCL Constructors Inc. and ICONICS, Inc. have used artificial intelligence platforms at the construction site to build smart buildings.
The application segment is classified into asset management, project management, risk management, schedule management, supply chain management, and others. The project management segment is expected to have a significant market share among applications. Several companies adopt the project management application for each phase of the construction, such as pre-construction, construction-stage, and post-construction. It helps the company boost its productivity and efficiency by automating the building processes, such as proposal management, planning and designing, sourcing and contract management, and virtual design and construction.
Also, AI-enabled project management application is beneficial in handling over-budget construction projects by capturing the real-image data from the job site and providing accurate precisions for the budget by calculating the original hours taken to complete the tasks. It is also adopted for post-construction tasks, such as real estate management and intelligent buildings and facilities management. It helps to maintain the assets and facilities operations of the job site. Therefore, companies are focusing on bringing AI-enabled project management applications.
The stage segment is classified into pre-construction, construction-stage, and post-construction. The pre-construction segment is expected to have a significant market share among other stages in the industry. AI-enabled applications are highly adopted for the pre-construction stage by several companies since this stage involves the prior project management tasks, such as schedule management and cost management. It covers all the planning and design-related tasks, such as opportunity and proposal management, cost management, sourcing and contract management, and virtual design and construction.
Cost management is one of the significant pre-construction stage tasks and construction companies prefer artificial intelligence for this task. AI-enabled cameras at the job site provide the real-time feedback by capturing the actual amount of time and resources spent on a project, based on which cost and budget are decided for the upcoming projects. Artificial intelligence helps the project managers predict the budget on the right precision based on contract type and project start and end dates. Furthermore, AI helps to create a virtual design of the model to be constructed, which is also a significant task at the pre-construction stage. Thus, the pre-construction stage in AI for the industry is expected to lead among other stages.
The deployment type segment is bifurcated into the cloud and on-premises. The cloud segment is expected to have a significant market share among both deployment types owing to the increasing investments in IoT-based applications. Several AI in construction solutions providers is investing in cloud and IoT-based products and services through mergers and acquisitions. The investments are aimed at creating a computer-aided virtual environment (CAVE), to provide general contractors, architects, and customers with a virtual experience of their building.
Cloud deployment provides a more cost-effective deployment method for construction companies. Its scalability and quick adaptability feature make it prominent for large and heavy building projects. Also, AI applications are now deployed in private clouds to address privacy and security issues. Thus, cloud deployment is expected to lead among deployment types for AI applications in the industry.
Based on industry type, artificial intelligence in the construction market is segmented into residential, public infrastructure, heavy construction, and others. Heavy construction is expected to have a significant market share among industry types, owing to increasing accidents and sudden falls at large building sites. Heavy construction involves massive structures and a wide variety of equipment that require project management with diligence and extensive engineering. Several major equipment manufacturers are making investments in self-operating machines to perform site work, excavation, grading, demolition, and paving, among other tasks.
In large enterprises and heavy building sites, tracking the processes is quite challenging. AI-powered solutions and services help to manage task scheduling and reallocation, and other project planning related tasks. Substantial infrastructures such as ports, dams, bridges, roads, coastal engineering, transportation, waterways, and energy infrastructure are adopting the AI solutions since it helps to measure productivity on the job sites while promising project managers a competitive edge with smart visualized data. Also, risk management is ensured with the help of predictive maintenance using AI. Thus, heavy construction is expected to lead among other industry types.
The organization size segment is classified into small and medium-sized enterprises (SMEs) and large enterprises. The large enterprises are expected to have a significant market share among both organization sizes. Large enterprises, including the government and commercial enterprises, are increasingly adopting AI solutions on a large scale, owing to the rising demand for risk management and project management solutions across the segment. Favorable government regulations are motivating large construction enterprises to incorporate AI solutions and services.
Small and medium enterprises are estimated to demonstrate the growth at a healthy rate over the forecast period. Small and medium enterprises are increasingly employing AI solutions owing to the cost-effective nature of the platform. Cloud-based AI solutions are favorable to construction companies as there is no high set-up cost, and it can be started and stopped according to the project’s requirement. Also, the expansion of building firms requires proper management of their databases, which is expected to propel the demand further.
The market for AI in construction in North America accounted for more than 38% share in 2018, owing to the leading industrial automation market in the region. The North America region is characterized by a large number of populations having improved purchasing power, continuous investments in automation, and governments’ increasing focus on having in-house AI in construction equipment production. Also, considerably increasing investments in IIoT and industrial automation in this region is one of the major factors boosting the growth of the market in North America. Most of the tech giants have invested in the regional market and have been preferred for implementing AI-based applications by the companies. For instance, several construction companies, such as PCL Constructers Inc. and ThyssenKrupp AG have used the Microsoft Azure, developed by the U.S. based tech giant Microsoft, to deploy AI-enabled building solutions.
APAC region is expected to demonstrate the highest CAGR in the future. Rising infrastructural investments for various applications, such as risk management, project management, and supply chain management, are boosting the growth of this market in the Asia-Pacific region. Pre-construction AI applications have experienced an increased adoption in emerging economies, such as India and China. Furthermore, the rising demand to create smart cities in these economies is encouraging companies to adopt AI solutions and services.
The key market participants include IBM Corporation; Microsoft Corporation; Oracle Corporation; SAP SE; ALICE Technologies Inc.; eSUB Inc.; Smartvid.io, Inc.; Darktrace; Aurora Construction and Security; and Autodesk Inc.
Vendors in the market are focusing on increasing the customer base to gain a competitive edge in the market. Therefore, vendors are taking several strategic initiatives, such as collaborations, acquisitions and mergers, and partnerships. For instance, in August 2019, Procore Technologies, Inc. acquired the Construction BI, LLC, to bring next-generation AI analytics to the construction industry. In December 2018, Autodesk Inc. acquired two U.S. based construction-tech startups PlanGrid, Inc., and BuildingConnected. These acquisitions were aimed at encouraging construction software development to digitize the whole building process.
The base year for estimation
Actual estimates/Historical data
2014 - 2017
2019 - 2025
Revenue in USD Million and CAGR from 2019 to 2025
North America, Europe, Asia Pacific, South America, MEA
U.S., Canada, Mexico, Germany, U.K., France, China, Japan, India, and Brazil
Revenue forecast, company share, competitive landscape, growth factors, and trends
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This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2014 to 2025. For this study, Grand View Research has segmented the global Artificial Intelligence in Construction market report based on offering, application, stage, deployment type, organization size, industry type, and region:
Offering Outlook (Revenue, USD Million, 2014 - 2025)
Application Outlook (Revenue, USD Million, 2014 - 2025)
Supply Chain Management
Stage Outlook (Revenue, USD Million, 2014 - 2025)
Deployment Type Outlook (Revenue, USD Million, 2014 - 2025)
Industry Type Outlook (Revenue, USD Million, 2014 - 2025)
Organization Size Outlook (Revenue, USD Million, 2014 - 2025)
Small & Medium-sized Enterprises (SMEs)
Regional Outlook (Revenue, USD Million, 2014 - 2025)
The Middle East and Africa (MEA)
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