Artificial Intelligence in Construction Market Size Projected to Generate a Revenue of $8,545.80 Mn by 2031Download Sample Reports Overview
The Global Artificial Intelligence in Construction Market Size is predicted to be valued at $ 8,545.80 million by 2031, surging from $496.40 million in 2021, at a noteworthy CAGR of 34.1%.
Impact Analysis of COVID-19 on the Artificial Intelligence in Construction Market
Artificial intelligence in the construction industry has been significantly impacted by COVID-19. Due to the industry's decreasing cash flow, which hampered construction companies' cash liquidity and forced them to cease operations, the artificial intelligence in construction market size was negatively impacted. To prevent the spread of the COVID-19 pandemic, a number of industries and businesses have chosen work-from-home models. This has resulted in a decrease in the use of office space and associated costs, which has a negative impact on the construction industry's access to the global AI in construction market.
Due to these factors, industrial enterprises have given their digital transformation initiatives including the AI-enabled machinery in their production units—less emphasis. To reduce worker density, a number of AI and automation experts have suggested increasing investments in cutting-edge technologies, such as AI, to develop remote operating capabilities, such as industrial robots, process automation, autonomous material movement, and predictive maintenance, and machinery inspection.
Global Artificial Intelligence in Construction Market Analysis
One of the key driving factors for artificial intelligence in the construction market is lowering the risk of workplace accidents. Some of the riskiest occupations in the perilous industries of engineering and construction can be replaced by robots. When properly programmed, they can be made to operate in hazardous conditions and learn through interactions with their surroundings, which will reduce the number of workplace accidents. Although automation was initially employed to boost productivity on construction sites, evidence is accumulating that it can also make the workplace safer. These are the major factors anticipated to boost the artificial intelligence in construction market share during the analysis timeframe.
However, the lack of skilled workers is one of the key challenges. Artificial intelligence-assisted work in the construction sector demands both technical and domain expertise to get the desired results. The entire project prediction and off-site construction work are lost if the worker doesn't have a firm grasp of it, which can cause a sizable loss for the organization and expose it to a number of project-related difficulties. These factors are anticipated to restrict the artificial intelligence in construction market growth in the coming years.
Rapid technological advancements and digital transformation in the construction sector is driving the demand for artificial intelligence (AI) technology in this market. For instance, the use of security sensors, drones, building information systems (BIM), and others is growing rapidly in the construction industry. In order to fully capitalize on the enormous volume of digital data and generate unfair insights, this commonly drives construction companies to use cutting-edge analytics programs. Drone, robot, and autonomous vehicles are largely used in the construction sector is fostering the artificial intelligence in construction market size in the coming years. Large number of construction companies are using AI for surveying building sites, mapping, aerial photography, and automating development tasks. These factors are anticipated to generate excellent opportunity in the artificial intelligence in construction industry.
Global Artificial Intelligence in Construction Market, Segmentation
The global artificial intelligence in construction market is segmented based on offerings, deployment type, organization size, industry type, and region.
The offerings segment is further classified into solutions and services. Among these, the solutions sub-segment accounted for the highest market size in 2021. The market's increasing originality, innovation, and accessibility of AI-based building activity solutions are mostly responsible for the increase in demand for AI-based solutions in the construction sector. Building and construction firms are using AI technology solutions more frequently to complete various building projects. Artificial intelligence (AI) solutions, which have wide range of applications in schedule management, risk management, and supply chain management.
The deployment type segment is further classified into cloud and on-premises. Among these, the cloud sub-segment is anticipated to show the fastest growth during the projected timeframe. Cloud-based AI solutions in the construction sector are affordable and can be deployed easily. Flexibility, greater collaboration, capital expense-free, disaster recovery, automatic software upgrades, work from anywhere, document management, security, competitiveness, and environmental friendliness are a few of the major advantages of using a cloud deployment.
The organization size segment is further classified into small and medium-sized enterprises (SMES) and large enterprises. Among these, the large enterprise sub-segment accounted for the dominant share in the market. Due to the rapid technology advancement in construction equipment mainly integration of big data analytics, cloud storage, Internet of things, artificial intelligence and other technologies, the artificial intelligence in construction industry is likely to experience significant growth. Procore Technologies is one of the large enterprises in artificial intelligence, offering artificial intelligence-enabled solutions to support workers. Business intelligence is created from project data by Procore Technologies. During the timeframe, large enterprises sub-segment of AI in construction is projected to boost the market size in the coming years.
The industry type segment is further classified into residential, institutional commercials, and others. Among these, the institutional commercials sub-segment is anticipated to show the fastest growth during the forecast period. The term "institutional construction" describes the construction of recreation facilities and public structures. Compared to residential buildings, these constructions are subject to tougher rules. They must also have the adaptability to adjust to the shifting demands of their consumers which is anticipated to drive the demand for artificial intelligence in construction for the institutional commercials sub-segment in the coming years.
The artificial intelligence in construction market share in Asia-Pacific is projected to show the fastest growth. The growth of this market in Asia-Pacific is being driven by a rise in infrastructure investments and increase in construction activities. In developing nations such as India and China, pre-construction AI applications have seen a rise in popularity. Companies are being encouraged to adopt AI products and services by the increased desire to build smart cities in these economies. In Asia-Pacific, the Indian government is working efficiently to create a strong growth ecosystem to guarantee the healthy development of AI in India and its applications in numerous areas of governance and social development. These factors are anticipated to propel the Asia-Pacific artificial intelligence in construction market share in the projection period.
Key Players in the Global Artificial Intelligence in Construction Market
Some of the leading artificial intelligence in constructon market players are
- COINS Global
- Beyond Limits Inc.
- Autodesk Inc.
- Renoworks Software Inc.
- Building System Planning Inc.
- Bentley Systems
In May 2020, Project Bonsai, a new AI development platform for industrial systems introduced by Microsoft Corporation, was released. To make the control system autonomous in machinery such as bulldozer blades, robotic arms, underground drills, and forklifts, Project Bonsai is a machine learning service that combines optimization, calibration, and machine learning.