Artificial Intelligence in Construction Market Size & Share 2023 to 2032
Market Size by Component (Solution, Services), by Application (Project Management, Field Management, Risk Management, Asset Management), Deployment Model, Organization Size.
Report ID: GMI6024
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Published Date: June 2023
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Report Format: PDF
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Authors:
Preeti Wadhwani, Aishvarya Ambekar
AI in Construction Market Size
AI in Construction Market size valued at over USD 2.5 billion in 2022 and is anticipated to grow at a CAGR of 20% between 2023 and 2032. The industry growth is owing to improving efficiency and productivity through the optimization of project scheduling, resource allocation, and task management, leading to reduced timelines & costs.
Artificial Intelligence in Construction Market Key Takeaways
Market Size & Growth
Key Market Drivers
Challenges
Data-driven decision-making leverages AI's ability to analyze large volumes of construction data, enabling informed & proactive planning and resource optimization. Furthermore, AI enhances safety in construction operations through real-time monitoring, hazard detection, and compliance enforcement. It also enables quality control and defect detection, ensuring high construction standards and reducing rework.
The high cost of investment and operation is a significant obstacle hampering AI in construction market growth. Developing and implementing AI technologies in construction projects require substantial financial resources including the cost of acquiring AI systems, hardware, software, and specialized expertise. Moreover, operational & maintenance expenses can be substantial including the need for skilled personnel, regular updates, and infrastructure requirements. The high cost of investment and operation makes it challenging for small- & medium-sized construction companies to adopt AI solutions.
COVID-19 Impact
The COVID-19 crisis disrupted several industries including manufacturing & construction, transportation & logistics, and mining. The global shutdown affected outdoor industrial operations and hampered supply chains, restricting the adoption and implementation of AI technologies in the construction industry. The pandemic also highlighted the need for contactless operations, remote monitoring, and digital solutions, which accelerated the interest & investment in AI for construction. With the resumption of industrial operations post-pandemic, the demand for AI and IoT surged across various industries including construction.
AI in Construction Market Trends
The integration of Internet of Things (IoT) devices and sensors is creating demand for AI in construction. These connected devices collect real-time data on construction sites, equipment, and worker activities. This data, when combined with AI algorithms, provides valuable insights for optimizing construction processes, improving safety, and enhancing decision-making. Furthermore, the use of AI-powered drones and robotics in construction is gaining traction. These trends are driving the industry toward smart and automated construction practices, leading to increased efficiency, productivity, and quality in construction projects.
AI in Construction Market Analysis
The AI in construction market from solution segment dominated around USD 1.5 billion revenue in 2022. AI-powered solutions encompass a range of technologies and tools designed specifically for the construction industry. These solutions typically include components such as machine learning algorithms, computer vision, natural language processing, and data analytics platforms. The growth of AI solutions in construction is driven by their ability to automate processes, optimize resource allocation, enhance safety, and improve decision-making. These components work in synergy to provide comprehensive and tailored solutions that address the unique challenges & requirements of the construction industry, leading to increased efficiency, productivity, and overall project success.
The project management segment held over 35% of the AI in construction market share in 2022. AI technologies are being leveraged to streamline and optimize various aspects of project management. Machine learning algorithms can analyze historical project data to generate accurate cost estimates, predict project timelines, and identify potential risks & delays. AI-powered tools and platforms assist in resource allocation, scheduling & task management, and improving project efficiency & productivity. Furthermore, AI-driven analytics enable real-time monitoring of project progress, allowing for proactive decision-making and effective resource allocation. The growth of AI in project management is revolutionizing how construction projects are planned, executed, and managed, leading to improved outcomes and reduced project risks.
North America AI in construction market accounted for 30% of the revenue share in 2022. The region benefits from advanced technological infrastructure and a strong focus on innovation. The construction industry in North America is increasingly adopting AI-driven solutions to improve operational efficiency, project management, and safety. The key factors driving growth include the demand for sustainable & smart construction practices, the need for cost reduction, and a supportive regulatory environment. Additionally, strategic partnerships between technology providers, construction companies, and research institutions further fuel the growth of AI in construction across North America.
AI in Construction Market Share
Major companies operating in the AI in construction market are:
AI in Construction Industry News:
The Artificial Intelligence in construction market research report includes in-depth coverage of the industry with estimates & forecast in terms of revenue (USD Million) from 2018 to 2032, for the following segments:
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Market, By Component
Market, By Deployment Model
Market, By Organization Size
Market, By Application
Market, By End User
The above information has been provided for the following regions and countries:
Research methodology, data sources & validation process
This report draws on a structured research process built around direct industry conversations, proprietary modelling, and rigorous cross-validation and not just desk research.
Our 6-step research process
1. Research design & analyst oversight
At GMI, our research methodology is built on a foundation of human expertise, rigorous validation, and complete transparency. Every insight, trend analysis, and forecast in our reports is developed by experienced analysts who understand the nuances of your market.
Our approach integrates extensive primary research through direct engagement with industry participants and experts, complemented by comprehensive secondary research from verified global sources. We apply quantified impact analysis to deliver dependable forecasts, while maintaining complete traceability from original data sources to final insights.
2. Primary research
Primary research forms the backbone of our methodology, contributing nearly 80% to overall insights. It involves direct engagement with industry participants to ensure accuracy and depth in analysis. Our structured interview program covers regional and global markets, with inputs from C-suite executives, directors, and subject matter experts. These interactions provide strategic, operational, and technical perspectives, enabling well-rounded insights and reliable market forecasts.
3. Data mining & market analysis
Data mining is a key part of our research process, contributing nearly 20% to the overall methodology. It involves analysing market structure, identifying industry trends, and assessing macroeconomic factors through revenue share analysis of major players. Relevant data is collected from both paid and unpaid sources to build a reliable database. This information is then integrated to support primary research and market sizing, with validation from key stakeholders such as distributors, manufacturers, and associations.
4. Market sizing
Our market sizing is built on a bottom-up approach, starting with company revenue data gathered directly through primary interviews, alongside production volume figures from manufacturers and installation or deployment statistics. These inputs are then pieced together across regional markets to arrive at a global estimate that stays grounded in actual industry activity.
5. Forecast model & key assumptions
Every forecast includes explicit documentation of:
✓ Key growth drivers and their assumed impact
✓ Restraining factors and mitigation scenarios
✓ Regulatory assumptions and policy change risk
✓ Technology adoption curve parameter
✓ Macroeconomic assumptions (GDP growth, inflation, currency)
✓ Competitive dynamics and market entry/exit expectations
6. Validation & quality assurance
The final stages involve human validation, where domain experts manually review filtered data to identify nuances and contextual errors that automated systems might miss. This expert review adds a critical layer of quality assurance, ensuring data aligns with research objectives and domain-specific standards.
Our triple-layer validation process ensures maximum data reliability:
✓ Statistical Validation
✓ Expert Validation
✓ Market Reality Check
Trust & credibility
Verified data sources
Trade publications
Security & defense sector journals and trade press
Industry databases
Proprietary and third-party market databases
Regulatory filings
Government procurement records and policy documents
Academic research
University studies and specialist institution reports
Company reports
Annual reports, investor presentations, and filings
Expert interviews
C-suite, procurement leads, and technical specialists
GMI archive
13,000+ published studies across 30+ industry verticals
Trade data
Import/export volumes, HS codes, and customs records
Parameters studied & evaluated
Every data point in this report is validated through primary interviews, true bottom-up modelling, and rigorous cross-checks. Read about our research process →