Artificial Intelligence in Construction Market Size & Share 2026-2035

Artificial Intelligence in Construction Market Size

The global artificial intelligence in construction market was estimated at USD 3.9 billion in 2025. The market is expected to grow from USD 4.7 billion in 2026 to USD 25.6 billion in 2035, at a CAGR of 20.6% according to latest report published by Global Market Insights Inc.

The construction sector is confronting one of its most sustained workforce deficits in decades. Federal labor statistics indicate that open construction positions in the United States alone exceeded 400,000 in 2024, with similar shortfalls reported across Western Europe and Australia.^{[1]Bureau of Labor Statistics, https://www.bls.gov} The structural driver is demographic: a large share of skilled trades workers is approaching retirement, while recruitment into the trades has not kept pace with infrastructure pipeline growth. AI-enabled automation spanning autonomous progress tracking, generative scheduling, and robotic layout tools is filling the productivity gap in measurable ways. Projects that deploy AI-driven scheduling and labor optimization report up to 15–18% reductions in crew idle time, a direct response to constrained workforce availability. The longer-term consequence is a market where AI is no longer positioned as a productivity enhancement but as a structural workforce substitute in specific, repeatable construction tasks.

Public infrastructure investment programs across North America, the European Union, and Southeast Asia are increasingly conditioning procurement eligibility on digital delivery standards that presuppose AI adoption. The US Infrastructure Investment and Jobs Act (IIJA), enacted in 2021, allocated approximately USD 1.2 trillion for roads, bridges, ports, and broadband a pipeline that continues to drive procurement activity through 2026 and beyond.^{[2]World Bank, https://www.worldbank.org} European Commission mandates under the Construction Product Regulation (CPR) update and the BIM Adoption Framework are similarly pushing public-sector contractors toward AI-assisted design and project control environments.^{[3]European Commission, https://ec.europa.eu} World Bank infrastructure lending for digital connectivity and smart urban development in emerging markets has further expanded the addressable public-sector market. The net effect is a procurement environment in which AI capabilities are transitioning from competitive differentiator to baseline requirement across large public contracts.

Construction remains among the highest-risk industries globally, with fatal injury rates that are disproportionate to workforce size. The International Labour Organization estimates that construction accounts for approximately 17% of all occupational fatalities worldwide despite representing roughly 7% of the global workforce.^{[4]International Labour Organization (ILO), https://www.ilo.org} This structural exposure is concentrating regulatory and procurement pressure on real-time hazard detection and compliance reporting two functions where computer vision and AI monitoring systems have demonstrated measurable outcomes. OSHA data confirms that the most cited construction violations fall protection, hazard communication, and scaffolding are directly addressable through AI-assisted monitoring with automated alert thresholds.^{[5]Occupational Safety and Health Administration (OSHA), https://www.osha.gov} The commercial implication is direct: general contractors operating under performance-based safety covenants in public contracts have strong economic incentives to deploy AI monitoring to reduce incident frequency and associated liability exposure.

Cost overruns remain systemic across large-scale construction projects. OECD analysis of infrastructure delivery performance indicates that major projects in OECD member countries overrun budgets by an average of 28% at completion, driven by scope changes, supply chain disruptions, and productivity variance. AI-based project management platforms address these root causes directly: machine learning models trained on historical project data generate baseline cost forecasts with narrower confidence intervals, while real-time integration with materials procurement and subcontractor scheduling flags budget variances before they compound. The transition from reactive to predictive project controls has measurable financial value, and large general contractors operating in competitive-bid environments are translating that value into procurement decisions, accelerating the commercial pipeline for AI project management tools.

Artificial Intelligence in Construction Market Trends

Generative AI is advancing from experimental proof-of-concept to operational deployment in pre-construction and project execution workflows at a pace that reflects both technology maturation and an urgent commercial need. The structural driver is document volume: a large infrastructure project generates hundreds of thousands of files specifications, RFIs, submittals, change orders, safety reports across a project lifecycle, and the cost of manual review compounds with scale. AI copilot platforms that can parse natural language queries against project document repositories, flag conflicting specifications, and draft initial responses to RFIs are delivering direct labor cost savings in project administration. Procore Technologies' February 2025 launch of Procore Copilot an AI-powered assistant embedded within its platform for natural language querying, document summarization, and automated project insights exemplifies the commercial direction that leading software vendors are pursuing.

Computer vision deployment on active construction sites has crossed from niche pilot to mainstream procurement consideration among large general contractors globally. The technology stack high-resolution cameras, edge computing nodes, and on-site AI inference modules has declined in unit cost while simultaneously improving detection accuracy, making it financially viable to instrument large sites comprehensively. Leading deployments use computer vision to monitor personal protective equipment (PPE) compliance in real time, detect unauthorized access to exclusion zones, and identify structural anomalies in reinforcement placement and concrete pours. OpenSpace, DroneDeploy, and Buildots are among the construction-native platforms that have commercialized these functions at scale, while broader platform vendors are integrating computer vision modules into their existing project management ecosystems.

The convergence of predictive analytics, digital twin modeling, and connected equipment telematics is creating a data infrastructure that enables real-time project performance management at a level of granularity that was not operationally feasible before 2022. Digital twins persistent virtual representations of physical construction assets can now be updated in near real time from drone surveys, IoT sensor arrays, and BIM model revisions, providing project leads with a continuously current picture of physical progress against design intent. Predictive analytics layers operating on top of these models identify schedule risk, equipment utilization variance, and subcontractor productivity shortfalls before they materialize as visible delays. Bentley Systems' iTwin platform and Hexagon's Connected Construction suite represent commercially deployed examples of this architecture operating on live projects in the infrastructure and industrial construction sectors.

Artificial Intelligence in Construction Market Analysis

Based on component, the market is divided into solutions, services. Solutions dominated the market, accounting for 74% share in 2025 and are expected to grow at a CAGR of 21% through 2026 to 2035.

• AI solutions represented the largest component of the artificial intelligence in construction market. This segment includes software platforms and applications that embed artificial intelligence directly into construction workflows, such as generative design, computer vision-based safety monitoring, AI-powered Building Information Modeling (BIM), predictive project management, autonomous progress tracking, and intelligent cost estimation. The dominance of solutions reflects the industry's increasing shift toward software-driven automation, where contractors, engineering firms, and project owners are leveraging AI to improve productivity, reduce delays, enhance decision-making, and optimize resource utilization across the project lifecycle. Cloud-based deployment models and subscription licensing have further accelerated adoption by making AI capabilities more scalable and accessible across organizations of all sizes.
• The solutions segment is also benefiting from continued integration of AI into broader construction technology ecosystems rather than as standalone applications. Major vendors such as Autodesk, Procore, Bentley Systems, Trimble, and Hexagon are embedding AI across design, project controls, digital twins, field operations, and collaboration platforms, enabling customers to access multiple AI capabilities through unified software environments. At the same time, specialized vendors continue to innovate in areas such as document intelligence, schedule optimization, site monitoring, and reality capture, expanding the range of AI-enabled use cases available to the construction industry. As enterprises increasingly standardize on integrated digital platforms, software solutions continue to represent the primary source of AI-related revenue within the construction sector.
• AI services segment comprises professional services, implementation and systems integration, consulting, customization, training, technical support, and managed AI services that help construction organizations successfully deploy and operate AI technologies. Service providers play a critical role in integrating AI platforms with existing ERP, BIM, project management, and field reporting systems while supporting workforce training and organizational change management. As construction companies expand AI adoption from pilot projects to enterprise-wide implementations, demand for specialized implementation expertise and ongoing AI optimization services continues to increase, making services an essential complement to software solutions despite solutions remaining the dominant revenue contributor.

Based on deployment mode, the market is segmented into cloud, on-premise, hybrid. Cloud segment dominates the market with 56% share in 2025, and the segment is expected to grow at a CAGR of 23.1% from 2026 to 2035.

• Cloud deployment dominated the artificial intelligence in construction market in 2025. Cloud-based AI platforms have become the preferred deployment model for construction companies because they enable centralized project management, seamless collaboration across geographically distributed job sites, continuous software updates, and scalable computing resources without requiring significant on-premise infrastructure. AI applications such as predictive scheduling, computer vision, BIM analytics, digital twins, and project intelligence are increasingly delivered through cloud-native platforms, allowing contractors and project owners to access real-time insights from any location. The widespread adoption of subscription-based Software-as-a-Service (SaaS) models has further accelerated cloud deployment, particularly among large contractors managing multiple concurrent projects.
• Cloud adoption has also been driven by the product strategies of major construction technology vendors. Platforms such as Autodesk Construction Cloud, Procore, Bentley Systems' iTwin ecosystem, and Hexagon's cloud-enabled solutions integrate AI capabilities directly into project management, design collaboration, safety monitoring, and field operations. These platforms allow organizations to consolidate project data from multiple sites, improve decision-making through centralized analytics, and deploy new AI features without complex software upgrades. As construction firms continue their digital transformation initiatives, cloud deployment remains the dominant architecture for AI implementation due to its flexibility, scalability, and lower total cost of ownership.
• The on-premise deployment segment despite the industry's transition toward cloud-based platforms, on-premise deployments remain essential for organizations operating under strict data security, regulatory, or contractual requirements. Government agencies, defense contractors, critical infrastructure projects, and highly regulated industrial facilities often require project data to remain within private networks, making on-premise AI deployments the preferred option. These implementations provide organizations with greater control over sensitive project information while supporting AI applications for project planning, scheduling, document management, and operational analytics within secure enterprise environments.

Based on construction, the market is segmented into residential construction, commercial construction, industrial construction, infrastructure & civil engineering, others. Commercial construction segment dominates the market with 32.3% share in 2025.

• Commercial construction represented the largest construction in the artificial intelligence in construction market. This segment includes office buildings, retail developments, hospitality projects, mixed-use complexes, healthcare facilities, educational institutions, and data centers, where project complexity, tight delivery schedules, and multi-stakeholder coordination drive strong demand for AI-powered solutions. Contractors and developers are increasingly adopting AI for project planning, cost estimation, schedule optimization, Building Information Modeling (BIM), quality control, and real-time project monitoring to improve operational efficiency and reduce construction risks. The growing adoption of cloud-based construction management platforms and digital collaboration tools has further accelerated AI deployment across commercial projects.
• Commercial construction also benefits from increasing investment in sustainable buildings and advanced digital construction practices. AI is being integrated into design optimization, energy performance analysis, compliance management, and predictive maintenance planning to support green building certifications and improve long-term asset performance. Large-scale developments, particularly data centers and smart commercial facilities, require sophisticated coordination of mechanical, electrical, and plumbing (MEP) systems, making AI-driven analytics and automated clash detection increasingly valuable. As commercial developers continue to prioritize productivity, sustainability, and cost efficiency, the segment remains the largest adopter of AI technologies within the construction industry.
• Infrastructure and civil engineering segment includes highways, bridges, tunnels, railways, airports, ports, utilities, water infrastructure, and energy transmission projects, where AI is increasingly deployed to improve project planning, risk assessment, asset monitoring, and construction progress tracking. These projects typically involve long construction timelines, geographically dispersed sites, and extensive regulatory oversight, creating strong demand for AI-enabled geospatial analytics, drone-based inspections, predictive maintenance, and digital twin technologies. Government investment in smart infrastructure and digital transformation initiatives continues to support AI adoption across large-scale civil engineering projects, making infrastructure one of the fastest-growing application areas within the market.

Based on application, the market is segmented into project management & planning, safety & risk management, design optimization & BIM, field & operations management, supply chain & procurement management, others. The project management & planning segment is expected to dominate the market with a share of 28.1% in 2025.

• Project management and planning represented the largest application segment in the artificial intelligence in construction market. Construction companies are increasingly adopting AI-powered project management solutions to improve schedule forecasting, cost estimation, resource allocation, and project risk management throughout the construction lifecycle. By analyzing historical project data alongside real-time site information, AI enables project teams to identify potential delays, optimize labor and equipment utilization, and improve decision-making before issues escalate into significant cost overruns. As digital project controls become standard practice across commercial, industrial, and infrastructure projects, AI-powered planning platforms continue to represent the largest revenue-generating application within the market.
• The segment has also evolved beyond traditional scheduling to include intelligent document management, contract analytics, automated reporting, and predictive project controls. Leading vendors such as Autodesk, Procore, Oracle, Bentley Systems, and specialized providers including nPlan and SmartPM are embedding AI into construction management platforms to automate routine administrative tasks and provide actionable project insights. These capabilities enable project managers to make faster, data-driven decisions while improving collaboration among owners, contractors, architects, and subcontractors. The continued integration of AI into project execution platforms is strengthening demand for project management applications across organizations of all sizes.
• Field and operations management segment includes AI applications deployed directly on construction sites for progress monitoring, workforce coordination, equipment management, quality inspection, and safety observation. Computer vision, drones, IoT sensors, wearable devices, and edge AI technologies are increasingly being used to provide real-time visibility into site activities, helping contractors improve productivity, reduce rework, and enhance operational efficiency. AI-driven monitoring systems enable continuous tracking of construction progress and resource utilization while supporting faster decision-making under dynamic site conditions.

China dominates the Asia Pacific artificial intelligence in construction market accounting for 47% and generating USD 0.4 billion in 2025.

• China remains the largest construction market in the region, supported by extensive residential, commercial, industrial, and infrastructure development. Continued urbanization, large-scale transportation projects, smart city initiatives, and investments in digital construction technologies are driving demand for AI-powered project management, Building Information Modeling (BIM), computer vision, digital twins, and predictive analytics. Even with AI adoption still developing across parts of the industry, China's vast construction activity translates into substantial AI market opportunities.
• Government initiatives continue to accelerate AI adoption across the construction sector through policies promoting construction digitalization, smart infrastructure, and BIM implementation. National programs encouraging intelligent construction methods, combined with investments in advanced transportation networks, urban redevelopment, and public infrastructure, are encouraging contractors and engineering firms to integrate AI into project planning, safety management, quality control, and asset lifecycle management. Increasing deployment of cloud computing, IoT, drones, and AI-enabled monitoring systems is further supporting digital transformation across China's construction ecosystem.
• The competitive landscape in China is shaped by a combination of domestic technology providers and international construction software vendors. Local companies such as Glodon have strengthened their positions by integrating AI capabilities into BIM, cost management, and construction management platforms tailored to domestic requirements. At the same time, multinational vendors continue to serve international contractors and private developers operating in China through cloud-based project management and engineering software. Data security regulations and localization requirements have encouraged the development of domestic AI ecosystems, resulting in a market where local and global vendors compete across different customer segments while continuing to expand AI adoption throughout the country's construction industry.

US dominates North America artificial intelligence in construction market growing with a CAGR of 19.4% from 2026 to 2035.

• The United States is the largest adopter of AI technologies in construction, supported by widespread digital transformation, advanced Building Information Modeling (BIM) adoption, and the presence of leading construction technology vendors such as Autodesk, Procore, Oracle, Bentley Systems, and Trimble. Strong demand for cloud-based construction management platforms has enabled contractors to integrate AI capabilities into existing project management and engineering workflows with relatively low implementation barriers.
• Federal infrastructure investment programs and large-scale commercial developments continue to accelerate AI adoption across the U.S. construction industry. Major investments in transportation networks, utilities, renewable energy projects, manufacturing facilities, and public infrastructure are encouraging contractors to deploy AI for project planning, schedule optimization, cost forecasting, quality management, and safety monitoring. The expansion of hyperscale data centers and advanced industrial facilities has further increased demand for AI-powered construction technologies capable of managing technically complex and schedule-intensive projects.
• Labor shortages remain one of the most significant factors driving AI adoption in the U.S. construction sector. Contractors are increasingly using AI-powered automation, computer vision, predictive analytics, and digital field management tools to improve workforce productivity, reduce manual inspection efforts, optimize resource allocation, and minimize project delays. AI also supports improved collaboration between project stakeholders by providing real-time insights into construction progress, equipment utilization, and potential project risks.
• The competitive landscape in the United States is characterized by a mature ecosystem of software developers, cloud service providers, engineering firms, and specialized AI startups. Continuous innovation in generative AI, digital twins, robotics, drone-based monitoring, and intelligent project controls is expanding the range of AI applications available to contractors. Supported by strong technology investment, advanced cloud infrastructure, and a highly digitalized construction industry, the United States continues to lead the global market.

Germany dominates the Europe artificial intelligence in construction market, showcasing strong growth potential, with a CAGR of 20% from 2026 to 2035.

• The country's strong engineering expertise, mature construction industry, and widespread adoption of digital construction technologies have positioned it as a leading market for AI-enabled construction solutions. Contractors, engineering firms, and project owners are increasingly adopting AI-powered software for project planning, Building Information Modeling (BIM), cost estimation, quality management, and construction monitoring to improve project efficiency and reduce operational risks.
• Government initiatives promoting digitalization have played a significant role in accelerating AI adoption across Germany's construction sector. Public infrastructure projects increasingly encourage the use of BIM-based project delivery and digital construction practices, creating favorable conditions for AI integration throughout the project lifecycle. Growing emphasis on sustainable buildings, energy-efficient infrastructure, and digital documentation has further expanded demand for AI applications in design optimization, compliance management, predictive analytics, and asset lifecycle management.
• Germany also benefits from a strong domestic ecosystem of construction technology providers. Companies such as Nemetschek Group, RIB Software, and SAP continue to expand AI capabilities across design software, project management platforms, enterprise resource planning, and digital construction workflows. These vendors are integrating generative AI, machine learning, computer vision, and cloud-based analytics into their platforms, enabling construction firms to automate repetitive tasks, improve collaboration, and enhance decision-making throughout project execution.
• Industrial and infrastructure construction remain major drivers of AI adoption in Germany. Significant investments in battery manufacturing plants, semiconductor facilities, renewable energy projects, logistics infrastructure, and transportation networks require advanced project controls, real-time monitoring, and efficient resource management. AI-powered technologies such as digital twins, predictive scheduling, automated quality inspection, and intelligent site analytics are increasingly deployed to manage these technically complex projects, supporting higher productivity, improved project quality, and better risk management across the German construction industry.

Brazil leads the Latin American artificial intelligence in construction industry, exhibiting remarkable growth of 19.8% during the forecast period of 2026 to 2035.

• Brazil is the largest artificial intelligence in construction market in Latin America, supported by its extensive construction industry spanning residential, commercial, industrial, and infrastructure projects. The country's large construction activity presents significant opportunities for AI adoption across project planning, Building Information Modeling (BIM), construction monitoring, predictive analytics, and digital project management. However, adoption remains relatively early due to the fragmented nature of the construction sector, where small and medium-sized contractors account for a large share of industry activity and often face budget and technology adoption constraints.
• Government investment in infrastructure is a major driver supporting AI adoption in Brazil's construction sector. Ongoing projects involving transportation networks, ports, railways, sanitation systems, energy infrastructure, and urban development are increasing demand for AI-powered project management, construction monitoring, predictive analytics, and digital collaboration platforms. Internationally funded infrastructure programs and the growing use of digital project delivery methods are further encouraging contractors to adopt AI-enabled construction technologies to improve project efficiency and cost control.
• The expansion of Building Information Modeling (BIM) across public-sector construction is also strengthening the foundation for AI implementation. National initiatives promoting BIM adoption in government projects are improving data availability and digital workflows, making it easier for construction firms to integrate AI into design, planning, scheduling, quality management, and asset lifecycle management. As BIM adoption continues to expand, AI technologies are becoming increasingly integrated into construction project delivery.
• The competitive landscape in Brazil is gradually evolving as both international software vendors and regional construction technology providers expand their presence in the market. Global companies such as Autodesk, Procore, Bentley Systems, Oracle, and Trimble are strengthening their presence through cloud-based construction platforms and AI-enabled project management solutions, while domestic contractors continue investing in digital transformation. Supported by infrastructure modernization, expanding BIM adoption, and increasing cloud deployment, Brazil is expected to remain the leading AI in Construction market within Latin America.

UAE witnessed substantial growth in the Middle East and Africa artificial intelligence in construction industry in 2025.

• The UAE is the leading artificial intelligence in construction market in the Middle East & Africa, supported by its strong focus on digital transformation, smart city development, and large-scale infrastructure investment. The country's construction sector is characterized by technologically advanced commercial, residential, hospitality, transportation, and mixed-use developments, creating favorable conditions for AI adoption across project planning, Building Information Modeling (BIM), digital twins, construction monitoring, and predictive analytics. Government-led initiatives promoting innovation and digital construction continue to accelerate the integration of AI into project delivery.
• Major infrastructure and urban development programs remain key drivers of market growth. Projects including rail networks, airports, smart cities, renewable energy developments, and mixed-use urban communities are encouraging contractors to deploy AI-powered project management, computer vision, safety monitoring, quality inspection, and real-time progress tracking solutions. Large international and regional contractors operating in the UAE are increasingly adopting cloud-based construction platforms and AI-enabled digital workflows to improve productivity, reduce project risks, and enhance collaboration across complex developments.
• Government policies promoting artificial intelligence, digital infrastructure, and Building Information Modeling have further strengthened the market. National digital transformation strategies, smart city initiatives, and increasing adoption of BIM across public and private construction projects are creating a strong foundation for AI implementation throughout the construction lifecycle. The growing use of cloud computing, IoT, drones, and digital twin technologies is enabling more efficient planning, construction, and asset management across major projects.
• The competitive landscape continues to evolve as global construction technology providers expand their presence alongside regional technology companies. Leading vendors including Autodesk, Procore, Bentley Systems, Oracle, Trimble, and Hexagon are supplying AI-enabled construction management platforms to contractors, developers, and engineering firms across the UAE. Supported by continued investment in smart infrastructure, advanced digital technologies, and innovation-driven construction practices, the UAE is expected to remain the primary market within the Middle East & Africa.

Artificial Intelligence in Construction Market Share

• The top 7 companies in the artificial intelligence in construction industry are Procore Technologies, Bentley Systems, Autodesk, Hexagon, Trimble, Oracle, Nemetschek. collectively accounted for around 32.9% of the global market share in 2025, reflecting a moderately fragmented competitive landscape driven by global logistics integration and end-to-end supply chain capabilities.
• Procore Technologies is a global construction technology provider offering an AI-enabled, cloud-native construction management platform with capabilities spanning project management, document control, field productivity, financial management, predictive analytics, and AI-powered project insights to improve collaboration, safety, and project delivery.
• Bentley Systems is a global infrastructure engineering software provider offering AI-powered digital twin, Building Information Modeling (BIM), and infrastructure engineering solutions that enable predictive asset management, construction planning, project monitoring, and lifecycle optimization across infrastructure projects.
• Autodesk is a global design and engineering software provider offering AI-enabled BIM, generative design, construction management, and project collaboration solutions that enhance design automation, project coordination, cost estimation, and construction productivity throughout the project lifecycle.
• Hexagon is a global digital reality and industrial technology provider delivering AI-driven geospatial, reality capture, autonomous construction, and digital twin solutions that improve site surveying, machine control, construction monitoring, and operational efficiency.
• Trimble is a global technology company offering AI-powered construction management, BIM, positioning, machine control, and connected jobsite solutions that enable intelligent project planning, equipment optimization, field collaboration, and productivity improvement.
• Oracle is a global enterprise software provider offering AI-enabled construction and engineering management solutions through its Oracle Construction and Engineering platform, supporting project controls, scheduling, contract management, risk management, and data-driven decision-making for capital projects.
• Nemetschek is a global software provider specializing in AI-enabled Building Information Modeling (BIM), digital design, engineering, and construction lifecycle solutions that improve project collaboration, workflow automation, sustainability, and digital project delivery across the architecture, engineering, and construction industry.

Artificial Intelligence in Construction Market Companies

Major players operating in the artificial intelligence in construction industry are:

• ALICE Technologies
• Trunk Tools
• Document Crunch
• nPlan
• SmartPM
• Procore Technologies
• Autodesk
• Trimble
• Bentley Systems
• Nemetschek 

• The artificial intelligence in construction market is moderately fragmented, with competition spanning enterprise software providers, BIM platform developers, construction management software vendors, computer vision specialists, AI-powered project intelligence companies, digital twin providers, and construction analytics platforms. Market participants are increasingly focused on delivering AI-enabled solutions that integrate project management, BIM, scheduling, safety monitoring, document intelligence, predictive analytics, equipment optimization, and real-time jobsite monitoring. Companies such as Procore Technologies, Autodesk Inc., Oracle Corporation, Trimble Inc., Bentley Systems, Hexagon AB, and Nemetschek Group are expanding their AI capabilities to support intelligent project delivery, connected construction workflows, and data-driven decision-making across the construction lifecycle.
• Specialized AI construction technology providers such as ALICE Technologies, Buildots, OpenSpace, DroneDeploy, Document Crunch, Trunk Tools, SmartPM, nPlan, AI Clearing, Versatile, viAct, and FYLD continue to strengthen their market presence by focusing on AI-driven scheduling optimization, computer vision-based progress tracking, document automation, predictive risk analytics, drone-based site inspections, safety monitoring, and field productivity. Competitive differentiation is increasingly driven by generative AI, computer vision, digital twins, predictive analytics, BIM integration, cloud-native deployment, open API ecosystems, cybersecurity capabilities, and seamless integration with ERP, project management, and collaboration platforms.

Artificial Intelligence in Construction Industry News

In May 2026, Procore Technologies launched an enhanced Procore AI experience by embedding Datagrid technology into its platform, introducing agentic AI capabilities that automate submittal reviews, RFI management, contract analysis, and project document search to improve construction workflows and project execution.

In July 2026, Procore Technologies introduced Digital Coworker packages featuring more than 20 pre-built AI agents and previewed Skills, enabling construction firms to automate scheduling, safety, bidding, change management, and project administration while training AI agents using company-specific knowledge and processes.

In June 2026, Procore Technologies launched its Connected Common Data Environment (CDE), an AI-enabled platform that unifies BIM models, project documentation, asset information, and workflows to support AI-driven collaboration, project coordination, and faster decision-making across construction projects.

In February 2025, Procore Technologies launched Procore Copilot, an AI-powered assistant integrated into the Procore platform that enables natural language queries, automated project insights, document summarization, and workflow assistance to improve project management and construction decision-making.

The artificial intelligence in construction market research report includes in-depth coverage of the industry with estimates & forecasts in terms of revenue (USD Bn) from 2022 to 2035, for the following segments:

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Market, By Component

• Solutions
  • Machine Learning & Deep Learning Solutions
  • Computer Vision Solutions
  • Natural Language Processing (NLP) Solutions
  • Generative AI (GenAI) Solutions
  • Others
• Services
  • Professional Service
  • Managed Service

Market, By Deployment Mode

• Cloud
• On-Premise
• Hybrid

Market, By Construction

• Residential Construction
• Commercial Construction
• Industrial Construction
• Infrastructure & Civil Engineering
• Others

Market, By Application

• Project Management & Planning
• Safety & Risk Management
• Design Optimization & BIM
• Field & Operations Management
• Supply Chain & Procurement Management
• Others

The above information is provided for the following regions and countries:

• North America
  • US
  • Canada
• Europe
  • Germany
  • UK
  • France
  • Italy
  • Spain
  • Russia
  • Norway
  • Netherlands
  • Sweden
• Asia Pacific
  • China
  • India
  • Japan
  • Australia
  • South Korea
  • Singapore
  • Thailand
  • Indonesia
  • Vietnam
• Latin America
  • Brazil
  • Mexico
  • Argentina
• MEA
  • South Africa
  • Saudi Arabia
  • UAE
  • Turkey