Description
Global AI in Construction Market Analysis and Forecast Report 2030
Product overview
Designers, engineers, and architects spend many hours working on building design regularly. The process of generating design variations and testing architectural statics and other building criteria (e.g. compliance with building codes, meeting all practical specifications, etc.) is especially time-consuming.
There are several examples of projects that fall due to inaccurate planning, particularly in large construction projects such as infrastructure buildings. This is where generative design, an exploration process based on AI technology, comes into play.
An AI-based system, with access to a database of many previously built building plans, can develop alternative designs based on the knowledge gained from the database plans. Designers and engineers may simply insert design objectives into the generative design software along with parameters such as spatial specifications, efficiency, materials, cost constraints, and many more.
The program, allowed by AI, then explores all possible permutations of a solution, creating alternative designs that meet all of the requirements previously stated.
Market Highlights
Global AI in the construction market is estimated to exceed USD 2638.53 million by 2030 from USD 406 million in 2019 at a CAGR of 18.94% during the forecast period i.e. 2020-2030.
As per their study, the market is anticipated to grow on the back of rising demand for AI-based solutions and platforms, the need for more security measures at construction sites, and the AI’s ability to reduce production costs.
Artificial Intelligence has been very beneficial to the construction industry in recent years, particularly in pre-construction phases such as planning and design, allowing for advanced capabilities in building information modeling and generative design.
Furthermore, major developments in surveillance, monitoring, and maintenance systems that use AI capabilities to predict and warn of adverse circumstances are increasingly increasing the role of AI-based technology in the construction sector.
Global AI in Construction Market: Segments
Machine Learning & Deep Learning segment to grow with the highest CAGR of xx% during 2020-2030
The worldwide market of AI in construction is segmented by technology into Machine Learning & Deep Learning and Natural Language Processing (NLP). Among these, the machine learning & deep learning segmented is estimated to hold the largest market share of xx% in the year 2019.
Due to the growing desire to analyze dark facts and automate enterprise functions, the use of gadget learning and deep learning technology in the creative industry has expanded manifold. Many construction groups deploy primarily AI-based solutions to achieve advantages.
Risk management segment to grow with the fastest CAGR of xx% during 2020-2030
Global AI in the construction market is segmented by application into Project Management, Risk Management, Field Management, Supply Chain Management, Schedule Management, and Others.
Among these, the risk management segment is witnessed to hold the largest market share of xx% in 2019 owing to the ability of artificial intelligence solutions to identify potential risks and fraud. Such risks may be related to quality, safety, time, or even costs.
Cloud deployment segment to grow with the fastest CAGR of xx% during 2020-2030
The worldwide AI in the construction market is segmented by deployment into On-premises and Cloud and Others. Among these, the cloud segment constituted the largest market share of xx% in 2019.
The cloud segment is simple and cost-efficient to use in applications. Flexibility, disaster recovery, automatic software updates, free capital expenditure, increased collaboration, work from anywhere, document control, security, competitiveness, environmental friendly are some of the key factors to boost the segment’s growth.
Global AI in Construction Market: Drivers and Restraints
Prevent Cost Overruns
Most megaprojects go over budget despite employing the best project teams. Artificial Neural Networks are used on projects to predict cost overruns based on factors such as project size, contract type, and the competence level of project managers. Historical data such as planned start and end dates are used by predictive models to envision realistic timelines for future projects.
AI helps staff remotely access real-life training material which helps them enhance their skills and knowledge quickly. This reduces the time taken to onboard new resources onto projects. As a result, project delivery is expedited.
Risk Mitigation
Every construction project has some risk that comes in many forms such as quality, safety, time, and cost risk. The larger the project, the more risk, as multiple sub-contractors are working on different trades in parallel on-job sites.
There are AI and machine learning solutions today that general contractors use to monitor and prioritize risk on the job site, so the project team can focus their limited time and resources on the biggest risk factors. AI is used to automatically assign priority to issues. Sub-contractors are rated based on a risk score so construction managers can work closely with high-risk teams to mitigate risk.
Global AI in Construction Market: Regions
North America expected to grow with the fastest CAGR of xx% during 2020-2030
The worldwide AI in the construction market is segmented by region into North America, Latin America, Europe, Middle East & Africa, and Asia Pacific. Among these, North America held the largest market share of xx% in the year 2019.
The change in the political scenario, of the U.S. and the region’s severe construction labor shortage, following a substantial rise in construction work activities, fuel the construction sector’s need for automation. The nation is one of the most influential building-tech startup hubs.
Thus, in the construction sector, the rapid adoption of AI is expected to overcome these hurdles, making it the fastest-growing AI region in the construction market.
The global AI in the construction market is further segmented by region into:
North America Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR – United States and Canada
Latin America Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR – Mexico, Argentina, Brazil, and Rest of Latin America
Europe Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR – United Kingdom, France, Germany, Italy, Spain, Belgium, Hungary, Luxembourg, Netherlands, Poland, NORDIC, Russia, Turkey, and Rest of Europe
MENA Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR – North Africa, Israel, GCC, South Africa, and Rest of MENA
APAC Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR – India, China, South Korea, Japan, Malaysia, Indonesia, New Zealand, Australia, and Rest of APAC
Global AI in Construction Market: Key players
IBM Corporation
Company Overview
Business Strategy
Key Product Offerings
Financial Performance
Key Performance Indicators
Risk Analysis
Recent Development
Regional Presence
SWOT Analysis
Dassault Systems SE
Building System Planning Inc.
Doxel Inc.
Autodesk Inc.
NVIDIA Corporation
Volvo AB
Komatsu Ltd.
Smartvid.io Inc.
Others
Market report on global AI in the construction market also consists of the following analysis:
AI in Construction Market Segments
By Technology
Machine Learning & Deep Learning
Normal Language Processing (NLP)
By Application
Project Management
Risk Management
Field Management
Supply Chain Management
Schedule Management
Others
By Deployment
On-premises
Cloud
By Region
North America
Latin America
Europe
Middle East & Africa
Asia Pacific
AI in Construction Market Dynamics
AI in Construction Market Size
Supply & Demand
Current Trends/Issues/Challenges
Competition & Companies Involved in the Market
Value Chain of the Market
Market Drivers and Restraints
FAQs on Global AI in Construction Market
Which segment is anticipated to hold the largest market share?
At what CAGR is the market anticipated to grow between 2020 and 2030?
Who are the key players in the worldwide AI in the construction market?
What could be the challenging factors for the growth of the global AI in the construction market?
What are the growth drivers for the AI in construction market across the globe?
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