Global Artificial Intelligence in Construction Market Size, Trend & Opportunity Analysis Report, by Component (Solution, Services), Application (Project Management, Field Management, Risk Management, Asset Management), and Forecast, 2025–2035
Description
Market Definition and Introduction
The global artificial intelligence (AI) in construction market, valued at USD 3.6 billion in 2024, is projected to ascend to a staggering USD 32.08 billion by 2035, expanding at a remarkable CAGR of 22.00% throughout the forecast period (2025–2035). Thus has risen the surge-an unparalleled expansion- urgent in the need for the sector to optimize operations, boost productivity, reduce overruns, and ultimately future-proof large-scale infrastructure development. AI is now seen as the game changer in an industry characterized by low margins and ever-shifting timelines by allowing real-time predictive analytics, automating mundane activities, and empowering data-backed decision-making at every stage of the construction lifecycle-from design to build.
With growing complexity in modern infrastructure, construction firms are investing in AI-powered solutions for optimized project management, real-time tracking of labor productivity, and ensuring compliance with both safety and sustainability standards. These smart tools mitigate risk and also provide operational foresight while seamlessly integrating with BIM systems and IoT sensors. Thus, contractors are relying on computer vision for site monitoring, predictive analytics for the anticipation of project delays, and generative design for the judicious allocation of resources.
Further, the global push for green building and sustainable infrastructure has encouraged stakeholders to embrace AI for not only optimizing material usage but also simulating energy performance. However, big engineering and construction (E&C) companies have set up AI labs or entered partnerships with technology leaders to explore several applications ranging from neural networks, deep learning, and natural language processing to intelligent procurement, real-time asset tracking, and autonomous construction machinery. This journey of AI deep into the DNA of construction signifies the transition of the construction industry from digitization to actually being an intelligent, execution driven.
Recent Developments in the Industry
Autodesk's Strategic Expansion into AI-Driven Construction Technologies
In March 2025, Autodesk Inc. declared an investment of several million dollars in AI-driven solutions for preconstruction planning and generative design. The investment follows their acquisition of an AI-based start-up enhancing construction simulation workflows and increasing preemptive decision-making powers.
Trimble Introduces AI to Construction Lifecycle Management
In February 2025, Trimble, Inc. introduced its new suite of AI-connected tools, designed to link field and office operations with autonomous data collection, real-time analytics, and robotic automation. The solution empowers contractors with tools to minimize delays, enhance site safety, and automate compliance documentation.
NVIDIA and Bentley Systems Team Up to Accelerate AI in Digital Twins
In January 2025, NVIDIA Corporation collaborated with Bentley Systems to put NVIDIA's AI-accelerated computing platform into action for infrastructure digital twins. This helps large construction projects develop real-time 3D simulations powered by AI, which can lend themselves to predictive maintenance, asset visualization, and real-world risk assessments.
Market Dynamics
Rapid Infrastructure Urbanization to Accelerate Demand for AI-Powered Project Optimization
Governments across the globe are implementing smart city initiatives and heavily investing in transportation, energy, and housing infrastructure, adding more pressure on construction firms to build faster, safer, and cheaper. AI may be termed as a force multiplier, effectively converting raw data from thousands of sensors, drones, and digital models into actionable insights that support design optimization, schedule adherence, and waste reduction.
Increasing Reliance by Contractors Predominantly on Predictive Analytics, Minimizing Risk and Downtime
AI risk management platforms have helped contractors take risks within the traditional uncertain terrain of construction. Such artificial intelligence incorporates historical data and site conditions and considers workforce behavior to proactively flag risk. Traffic Control and Aviation systems are recommending preemptive adjustments in resource allocation or sequencing that reduce the probability of equipment failures, safety incidents, or regulatory noncompliance.
Labor Shortages and Skill Shortages have increased Automation and Robotics.
The current shortage of skilled labor across the construction markets worldwide has compelled further adoption of AI-powered automation and robotics in construction. From bricklaying robots to AI-augmented crane operation, it balances out the human resource gap and improves precision while minimizing fatigue errors. Scheduling and productivity monitoring are much more improved significantly through the application of AI's intelligent systems in order to use available manpower optimally.
Digital Twin Technology Provides Real-Time Performance Assessments as Well as an Analysis of Life Cycle
AI-enabled digital twins are changing the asset management game regarding real-time simulation of the progress of construction. These virtual replicas keep track of what happened in construction progress, identify bottlenecks, and simulate what will happen thereafter to optimize resource use and project delivery. In the end, this creates an end-to-end digital thread to connect planning, design, execution, and operations for long-term value creation.
Regulatory Push for Smart Safety and Sustainability Amplifying AI Integration
Major economies' regulatory agencies are pushing for more transparent, safe, and sustainable construction practices. AI tools for compliance, including real-time audits of safety conditions, environmental impact simulations, and carbon tracking, are now integral to regulatory reporting. These tools provide traceable, tamper-resistant audit trails to support sustainable certifications and legal defensibility.
Attractive Opportunities in the Market
Surge in Smart Cities – Government investments in connected infrastructure propel AI adoption across projects.
Field Automation Boom – Computer vision and robotics revolutionize on-site construction accuracy and safety.
AI-Enhanced Project Scheduling – Predictive tools streamline timelines and optimize resource deployment.
Risk Prevention Systems – AI reduces construction delays by forecasting equipment failure and weather impact.
Autonomous Construction Equipment – Self-driving machinery reduces human error and labor costs.
Cloud-Based Collaboration – SaaS-based AI platforms enable real-time stakeholder engagement and insights.
Sustainability Compliance – AI helps track and reduce carbon footprints during construction lifecycles.
Digital Twins and BIM – Integration of AI with BIM offers real-time construction intelligence and simulations.
Report Segmentation
By Component:
Solution, Services
By Application: Project Management, Field Management, Risk Management, Asset Management
By Region: North America (U.S., Canada, Mexico), Europe (UK, Germany, France, Spain, Italy, Spain, Rest of Europe), Asia-Pacific (China, India, Japan, Australia, South Korea, Rest of Asia-Pacific), LAMEA (Brazil, Argentina, UAE, Saudi Arabia (KSA), Africa Rest of Latin America)
Key Market Players
Autodesk Inc., Oracle Corporation, IBM Corporation, Trimble Inc., Procore Technologies, Microsoft Corporation, SAP SE, Bentley Systems, ALICE Technologies, and NVIDIA Corporation.
Report Aspects
Base Year: 2024
Historic Years: 2022, 2023, 2024
Forecast Period: 2025–2035
Report Pages: 293
Dominating Segments
Solutions segment leads construction firms seeking customized AI platforms for end-to-end optimization.
The solutions segment of AI in construction dominates, as companies are investing in end-to-end project management platforms, predictive analytics, and computer vision systems. These AI-based platforms are being made essential for managing scheduling conflicts, tracking equipment, and real-time design changes. With the increasing complexity of construction activities, there is a heightened demand for customized and scalable AI software solutions.
Project management thus comes out as the most potent application for AI in construction across the globe.
AI's impact is most felt in project management, wherein contractors can identify scheduling conflicts, cost deviations, and workflow inefficiencies before they happen. AI-based cost analysis tools allow project managers to visualize the construction progress on real-time dashboards, track milestones, and redirect resources for optimal delivery, thereby transforming traditional reactive management into proactive leadership.
Risk management adoption increases with AI tools lowering onsite uncertainty and accident counts.
High-risk construction environments give risk management a premium application segment, where AI tools are now being used to avert safety incidents and predict project vulnerabilities. AI cuts the risk incurred by undertakings through environmental analyses and predictions of mechanical failures, thereby ensuring resilience in operations and safety among workers, while at the same time lowering insurance premiums and legal liabilities.
As field management tools-solidly gaining importance-demand a real-time overview of onsite activities.
Field management is being transformed by AI-powered wearables, drones, and sensor analytics, giving supervisors real-time visibility of site operations. These tools ensure compliance with tasks, monitor site hazards, and highlight anomalies that may arise to drastically reduce rework and boost quality assurance practices.
Asset management transformed through predictive maintenance and digital tracking over the entire life cycle.
In such asset-intensive construction operations, AI is changing asset management via predictive maintenance methodology, lifecycle tracking, and usage optimization. In this manner, these features increase the uptime of the equipment and prolong the economic life of costly construction assets, while at the same time aiding in improving bottom-line performance.
Key Takeaways
AI Dominates Project Planning – Predictive scheduling reduces overruns and enhances ROI.
Solutions Segment Leads – AI platforms automate end-to-end construction workflows.
Field Data Becomes Gold – Real-time analytics optimize worker safety and productivity.
Sustainability & Safety Synergies – AI ensures regulatory compliance and ESG performance.
Smart Equipment Emerges – Autonomous machinery redefines construction precision.
Risk Intelligence Tools – AI minimizes site hazards and construction disruption.
Digital Twin Growth – Asset simulations optimize building lifecycle management.
Collaborative Platforms Soar – Cloud AI drives transparency across stakeholders.
Asia-Pacific Investment Boom – Regional infrastructure push drives AI adoption.
Regulatory Compliance – AI tools align with evolving safety and environmental norms.
Regional Insights
North America is favored by potent Tech Ecosystems and Regulations on the AI in Construction Market
North America is the majority shareholder of this market with enormous investments in smart infrastructure, tech-savvy construction companies, and sophisticated regulatory frameworks in place for enforcing them. Within the U.S. construction sector, AI is finding acceptance for use, from planning to project maintenance, helped by tight cooperation between construction giants and Silicon Valley innovators.
Europe AI Improvements with an Eye on Sustainable Construction and Digital Compliance
Europe is taking great strides when it comes to AI in construction, particularly in Germany, the UK, and Scandinavia. Heavy focus on climate-positive building practices, worker safety, and data management is fast-tracking the uptake of AI in digital twins, risk analysis, and sustainable asset management.
AI with Mega Projects and Pro-Construction Policy to Lead Growth in the Asia-Pacific Region
Considering the forecast period, the Asia-Pacific will witness the highest growth, supported by huge infrastructure developments in China, India, and Southeast Asia. This growing interest in AI-based solutions is in tandem with government-initiated digitization drives, rapid urbanization, and the rise of domestic AI startups within construction tech.
Middle East & Latin America Start Strategic AI Integration for National Development Goals
Despite still being in the early stage, the Middle Eastern and Latin American countries are starting to pilot AI tools in public works, energy, and housing projects. Aims are to modernize project execution, provide visibility in complex builds, and align with national agendas for digitization.
Africa's pathway into AI construction via urbanization and funding of digital Infrastructure
AI in construction is gradually entering Africa with the speedy urbanization of the continent being one of its driving forces, along with funding from international developers. The growth of smart cities initiated by global contractors is creating favorable conditions for AI technologies, particularly in project monitoring and workforce management.
Core Strategic Questions Answered in This Report
Q. What is the expected growth trajectory of artificial intelligence in the construction market from 2024 to 2035?
The global artificial intelligence in construction market is projected to expand from USD 3.6 billion in 2024 to USD 32.08 billion by 2035, growing at a CAGR of 22.00%. This exponential growth reflects rising demand for AI-enhanced project execution, cost control, and risk management in complex construction environments.
Q. Which key factors are fuelling the growth of artificial intelligence in the construction market?
Several factors are accelerating this market’s growth:
Surging demand for smarter project delivery and predictive analytics.
Increasing labor shortages are triggering automation.
Rise in infrastructure investments globally.
Advancements in robotics, machine learning, and real-time data visualization.
Adoption of AI to achieve compliance, reduce waste, and enhance sustainability metrics.
Q. What are the primary challenges hindering the growth of artificial intelligence in the construction market?
Key challenges include:
High implementation costs and long ROI cycles.
Limited digital literacy among on-site workers.
Data integration complexity across legacy systems.
Concerns over data security and IP rights.
Resistance to change in traditional construction workflows.
Q. Which regions currently lead the artificial intelligence in construction market in terms of market share?
North America currently leads the market due to strong technological capabilities and widespread digital infrastructure. Europe follows with a solid commitment to sustainable construction practices and AI-compliance frameworks.
Q. What emerging opportunities are anticipated in the artificial intelligence in construction market?
The market is rife with opportunities:
Increased demand for smart cities and infrastructure automation.
AI-driven sustainability tools and compliance monitors.
Autonomous construction vehicles and robotics.
Digital twin integration for lifecycle asset management.
APAC mega projects driving massive AI deployment.
Key Benefits for Stakeholders
The report offers a quantitative assessment of market segments, emerging trends, projections, and market dynamics for the period 2024 to 2035.
The report presents comprehensive market research, including insights into key growth drivers, challenges, and potential opportunities.
Porter's Five Forces analysis evaluates the influence of buyers and suppliers, helping stakeholders make strategic, profit-driven decisions and strengthen their supplier-buyer relationships.
A detailed examination of market segmentation helps identify existing and emerging opportunities.
Key countries within each region are analysed based on their revenue contributions to the overall market.
The positioning of market players enables effective benchmarking and provides clarity on their current standing within the industry.
The report covers regional and global market trends, major players, key segments, application areas, and strategies for market expansion.
The global artificial intelligence (AI) in construction market, valued at USD 3.6 billion in 2024, is projected to ascend to a staggering USD 32.08 billion by 2035, expanding at a remarkable CAGR of 22.00% throughout the forecast period (2025–2035). Thus has risen the surge-an unparalleled expansion- urgent in the need for the sector to optimize operations, boost productivity, reduce overruns, and ultimately future-proof large-scale infrastructure development. AI is now seen as the game changer in an industry characterized by low margins and ever-shifting timelines by allowing real-time predictive analytics, automating mundane activities, and empowering data-backed decision-making at every stage of the construction lifecycle-from design to build.
With growing complexity in modern infrastructure, construction firms are investing in AI-powered solutions for optimized project management, real-time tracking of labor productivity, and ensuring compliance with both safety and sustainability standards. These smart tools mitigate risk and also provide operational foresight while seamlessly integrating with BIM systems and IoT sensors. Thus, contractors are relying on computer vision for site monitoring, predictive analytics for the anticipation of project delays, and generative design for the judicious allocation of resources.
Further, the global push for green building and sustainable infrastructure has encouraged stakeholders to embrace AI for not only optimizing material usage but also simulating energy performance. However, big engineering and construction (E&C) companies have set up AI labs or entered partnerships with technology leaders to explore several applications ranging from neural networks, deep learning, and natural language processing to intelligent procurement, real-time asset tracking, and autonomous construction machinery. This journey of AI deep into the DNA of construction signifies the transition of the construction industry from digitization to actually being an intelligent, execution driven.
Recent Developments in the Industry
Autodesk's Strategic Expansion into AI-Driven Construction Technologies
In March 2025, Autodesk Inc. declared an investment of several million dollars in AI-driven solutions for preconstruction planning and generative design. The investment follows their acquisition of an AI-based start-up enhancing construction simulation workflows and increasing preemptive decision-making powers.
Trimble Introduces AI to Construction Lifecycle Management
In February 2025, Trimble, Inc. introduced its new suite of AI-connected tools, designed to link field and office operations with autonomous data collection, real-time analytics, and robotic automation. The solution empowers contractors with tools to minimize delays, enhance site safety, and automate compliance documentation.
NVIDIA and Bentley Systems Team Up to Accelerate AI in Digital Twins
In January 2025, NVIDIA Corporation collaborated with Bentley Systems to put NVIDIA's AI-accelerated computing platform into action for infrastructure digital twins. This helps large construction projects develop real-time 3D simulations powered by AI, which can lend themselves to predictive maintenance, asset visualization, and real-world risk assessments.
Market Dynamics
Rapid Infrastructure Urbanization to Accelerate Demand for AI-Powered Project Optimization
Governments across the globe are implementing smart city initiatives and heavily investing in transportation, energy, and housing infrastructure, adding more pressure on construction firms to build faster, safer, and cheaper. AI may be termed as a force multiplier, effectively converting raw data from thousands of sensors, drones, and digital models into actionable insights that support design optimization, schedule adherence, and waste reduction.
Increasing Reliance by Contractors Predominantly on Predictive Analytics, Minimizing Risk and Downtime
AI risk management platforms have helped contractors take risks within the traditional uncertain terrain of construction. Such artificial intelligence incorporates historical data and site conditions and considers workforce behavior to proactively flag risk. Traffic Control and Aviation systems are recommending preemptive adjustments in resource allocation or sequencing that reduce the probability of equipment failures, safety incidents, or regulatory noncompliance.
Labor Shortages and Skill Shortages have increased Automation and Robotics.
The current shortage of skilled labor across the construction markets worldwide has compelled further adoption of AI-powered automation and robotics in construction. From bricklaying robots to AI-augmented crane operation, it balances out the human resource gap and improves precision while minimizing fatigue errors. Scheduling and productivity monitoring are much more improved significantly through the application of AI's intelligent systems in order to use available manpower optimally.
Digital Twin Technology Provides Real-Time Performance Assessments as Well as an Analysis of Life Cycle
AI-enabled digital twins are changing the asset management game regarding real-time simulation of the progress of construction. These virtual replicas keep track of what happened in construction progress, identify bottlenecks, and simulate what will happen thereafter to optimize resource use and project delivery. In the end, this creates an end-to-end digital thread to connect planning, design, execution, and operations for long-term value creation.
Regulatory Push for Smart Safety and Sustainability Amplifying AI Integration
Major economies' regulatory agencies are pushing for more transparent, safe, and sustainable construction practices. AI tools for compliance, including real-time audits of safety conditions, environmental impact simulations, and carbon tracking, are now integral to regulatory reporting. These tools provide traceable, tamper-resistant audit trails to support sustainable certifications and legal defensibility.
Attractive Opportunities in the Market
Surge in Smart Cities – Government investments in connected infrastructure propel AI adoption across projects.
Field Automation Boom – Computer vision and robotics revolutionize on-site construction accuracy and safety.
AI-Enhanced Project Scheduling – Predictive tools streamline timelines and optimize resource deployment.
Risk Prevention Systems – AI reduces construction delays by forecasting equipment failure and weather impact.
Autonomous Construction Equipment – Self-driving machinery reduces human error and labor costs.
Cloud-Based Collaboration – SaaS-based AI platforms enable real-time stakeholder engagement and insights.
Sustainability Compliance – AI helps track and reduce carbon footprints during construction lifecycles.
Digital Twins and BIM – Integration of AI with BIM offers real-time construction intelligence and simulations.
Report Segmentation
By Component:
Solution, Services
By Application: Project Management, Field Management, Risk Management, Asset Management
By Region: North America (U.S., Canada, Mexico), Europe (UK, Germany, France, Spain, Italy, Spain, Rest of Europe), Asia-Pacific (China, India, Japan, Australia, South Korea, Rest of Asia-Pacific), LAMEA (Brazil, Argentina, UAE, Saudi Arabia (KSA), Africa Rest of Latin America)
Key Market Players
Autodesk Inc., Oracle Corporation, IBM Corporation, Trimble Inc., Procore Technologies, Microsoft Corporation, SAP SE, Bentley Systems, ALICE Technologies, and NVIDIA Corporation.
Report Aspects
Base Year: 2024
Historic Years: 2022, 2023, 2024
Forecast Period: 2025–2035
Report Pages: 293
Dominating Segments
Solutions segment leads construction firms seeking customized AI platforms for end-to-end optimization.
The solutions segment of AI in construction dominates, as companies are investing in end-to-end project management platforms, predictive analytics, and computer vision systems. These AI-based platforms are being made essential for managing scheduling conflicts, tracking equipment, and real-time design changes. With the increasing complexity of construction activities, there is a heightened demand for customized and scalable AI software solutions.
Project management thus comes out as the most potent application for AI in construction across the globe.
AI's impact is most felt in project management, wherein contractors can identify scheduling conflicts, cost deviations, and workflow inefficiencies before they happen. AI-based cost analysis tools allow project managers to visualize the construction progress on real-time dashboards, track milestones, and redirect resources for optimal delivery, thereby transforming traditional reactive management into proactive leadership.
Risk management adoption increases with AI tools lowering onsite uncertainty and accident counts.
High-risk construction environments give risk management a premium application segment, where AI tools are now being used to avert safety incidents and predict project vulnerabilities. AI cuts the risk incurred by undertakings through environmental analyses and predictions of mechanical failures, thereby ensuring resilience in operations and safety among workers, while at the same time lowering insurance premiums and legal liabilities.
As field management tools-solidly gaining importance-demand a real-time overview of onsite activities.
Field management is being transformed by AI-powered wearables, drones, and sensor analytics, giving supervisors real-time visibility of site operations. These tools ensure compliance with tasks, monitor site hazards, and highlight anomalies that may arise to drastically reduce rework and boost quality assurance practices.
Asset management transformed through predictive maintenance and digital tracking over the entire life cycle.
In such asset-intensive construction operations, AI is changing asset management via predictive maintenance methodology, lifecycle tracking, and usage optimization. In this manner, these features increase the uptime of the equipment and prolong the economic life of costly construction assets, while at the same time aiding in improving bottom-line performance.
Key Takeaways
AI Dominates Project Planning – Predictive scheduling reduces overruns and enhances ROI.
Solutions Segment Leads – AI platforms automate end-to-end construction workflows.
Field Data Becomes Gold – Real-time analytics optimize worker safety and productivity.
Sustainability & Safety Synergies – AI ensures regulatory compliance and ESG performance.
Smart Equipment Emerges – Autonomous machinery redefines construction precision.
Risk Intelligence Tools – AI minimizes site hazards and construction disruption.
Digital Twin Growth – Asset simulations optimize building lifecycle management.
Collaborative Platforms Soar – Cloud AI drives transparency across stakeholders.
Asia-Pacific Investment Boom – Regional infrastructure push drives AI adoption.
Regulatory Compliance – AI tools align with evolving safety and environmental norms.
Regional Insights
North America is favored by potent Tech Ecosystems and Regulations on the AI in Construction Market
North America is the majority shareholder of this market with enormous investments in smart infrastructure, tech-savvy construction companies, and sophisticated regulatory frameworks in place for enforcing them. Within the U.S. construction sector, AI is finding acceptance for use, from planning to project maintenance, helped by tight cooperation between construction giants and Silicon Valley innovators.
Europe AI Improvements with an Eye on Sustainable Construction and Digital Compliance
Europe is taking great strides when it comes to AI in construction, particularly in Germany, the UK, and Scandinavia. Heavy focus on climate-positive building practices, worker safety, and data management is fast-tracking the uptake of AI in digital twins, risk analysis, and sustainable asset management.
AI with Mega Projects and Pro-Construction Policy to Lead Growth in the Asia-Pacific Region
Considering the forecast period, the Asia-Pacific will witness the highest growth, supported by huge infrastructure developments in China, India, and Southeast Asia. This growing interest in AI-based solutions is in tandem with government-initiated digitization drives, rapid urbanization, and the rise of domestic AI startups within construction tech.
Middle East & Latin America Start Strategic AI Integration for National Development Goals
Despite still being in the early stage, the Middle Eastern and Latin American countries are starting to pilot AI tools in public works, energy, and housing projects. Aims are to modernize project execution, provide visibility in complex builds, and align with national agendas for digitization.
Africa's pathway into AI construction via urbanization and funding of digital Infrastructure
AI in construction is gradually entering Africa with the speedy urbanization of the continent being one of its driving forces, along with funding from international developers. The growth of smart cities initiated by global contractors is creating favorable conditions for AI technologies, particularly in project monitoring and workforce management.
Core Strategic Questions Answered in This Report
Q. What is the expected growth trajectory of artificial intelligence in the construction market from 2024 to 2035?
The global artificial intelligence in construction market is projected to expand from USD 3.6 billion in 2024 to USD 32.08 billion by 2035, growing at a CAGR of 22.00%. This exponential growth reflects rising demand for AI-enhanced project execution, cost control, and risk management in complex construction environments.
Q. Which key factors are fuelling the growth of artificial intelligence in the construction market?
Several factors are accelerating this market’s growth:
Surging demand for smarter project delivery and predictive analytics.
Increasing labor shortages are triggering automation.
Rise in infrastructure investments globally.
Advancements in robotics, machine learning, and real-time data visualization.
Adoption of AI to achieve compliance, reduce waste, and enhance sustainability metrics.
Q. What are the primary challenges hindering the growth of artificial intelligence in the construction market?
Key challenges include:
High implementation costs and long ROI cycles.
Limited digital literacy among on-site workers.
Data integration complexity across legacy systems.
Concerns over data security and IP rights.
Resistance to change in traditional construction workflows.
Q. Which regions currently lead the artificial intelligence in construction market in terms of market share?
North America currently leads the market due to strong technological capabilities and widespread digital infrastructure. Europe follows with a solid commitment to sustainable construction practices and AI-compliance frameworks.
Q. What emerging opportunities are anticipated in the artificial intelligence in construction market?
The market is rife with opportunities:
Increased demand for smart cities and infrastructure automation.
AI-driven sustainability tools and compliance monitors.
Autonomous construction vehicles and robotics.
Digital twin integration for lifecycle asset management.
APAC mega projects driving massive AI deployment.
Key Benefits for Stakeholders
The report offers a quantitative assessment of market segments, emerging trends, projections, and market dynamics for the period 2024 to 2035.
The report presents comprehensive market research, including insights into key growth drivers, challenges, and potential opportunities.
Porter's Five Forces analysis evaluates the influence of buyers and suppliers, helping stakeholders make strategic, profit-driven decisions and strengthen their supplier-buyer relationships.
A detailed examination of market segmentation helps identify existing and emerging opportunities.
Key countries within each region are analysed based on their revenue contributions to the overall market.
The positioning of market players enables effective benchmarking and provides clarity on their current standing within the industry.
The report covers regional and global market trends, major players, key segments, application areas, and strategies for market expansion.
Table of Contents
285 Pages
- Chapter 1. Market Snapshot
- 1.1. Market Definition & Report Overview
- 1.2. Market Segmentation
- 1.3. Key Takeaways
- 1.3.1. Top Investment Pockets
- 1.3.2. Top Winning Strategies
- 1.3.3. Market Indicators Analysis
- 1.3.4. Top Impacting Factors
- 1.4. Application Ecosystem Analysis
- 1.4.1. 360’ Analysis
- Chapter 2. Executive Summary
- 2.1. CEO/CXO Standpoint
- 2.2. Strategic Insights
- 2.3. ESG Analysis
- 2.4 Market Attractiveness Analysis (top leader’s point of view on market)
- 2.5.key Findings
- Chapter 3. Research Methodology
- 3.1 Research Objective
- 3.2 Supply Side Analysis
- 3.1.1. Primary Research
- 3.1.2. Secondary Research
- 3.3 Demand Side Analysis
- 3.1.3. Primary Research
- 3.1.4. Secondary Research
- 3.2. Forecasting Models
- 3.2.1. Assumptions
- 3.2.2. Forecasts Parameters ()
- 3.3. Competitive breakdown
- 3.3.1. Market Positioning
- 3.3.2. Competitive Strength
- 3.4. Scope of the Study
- 3.4.1. Research Assumption
- 3.4.2. Inclusion & Exclusion
- 3.4.3. Limitations
- Chapter 4. Chapter 4. Application Landscape
- 4.1. Market Dynamics
- 4.1.1. Drivers
- 4.1.2. Restraints
- 4.1.3. Opportunities
- 4.2. Porter’s 5 Forces Model
- 4.2.1. Bargaining Power of Buyer
- 4.2.2. Bargaining Power of Supplier
- 4.2.3. Threat of New Entrants
- 4.2.4. Threat of Substitutes
- 4.2.5. Competitive Rivalry
- 4.3. Value Chain Analysis
- 4.4. PESTEL Analysis
- 4.5. Pricing Analysis and Trends
- 4.6. Key growth factors and trends analysis
- 4.7. Market Share Analysis (2025)
- 4.8. Top Winning Strategies (2025)
- 4.9. Trade Data Analysis (Import Export)
- 4.10. Regulatory Guidelines
- 4.11. Historical Data Analysis
- 4.12. Analyst Recommendation & Conclusion
- Chapter 5. Global Artificial Intelligence in Construction Market Size & Forecasts by Component 2025-2035
- 5.1. Market Overview
- 5.1.1. Market Size and Forecast By Component 2025-2035
- 5.2. Solution
- 5.2.1. Market definition, current market trends, growth factors, and opportunities
- 5.2.2. Market size analysis, by region, 2025-2035
- 5.2.3. Market share analysis, by country, 2025-2035
- 5.3. Services
- 5.3.1. Market definition, current market trends, growth factors, and opportunities
- 5.3.2. Market size analysis, by region, 2025-2035
- 5.3.3. Market share analysis, by country, 2025-2035
- Chapter 6. Global Artificial Intelligence in Construction Market Size & Forecasts by Application 2025–2035
- 5.1. Market Overview
- 6.1.1. Market Size and Forecast By Component 2025-2035
- 6.2. Project Management
- 6.2.1. Market definition, current market trends, growth factors, and opportunities
- 6.2.2. Market size analysis, by region, 2025-2035
- 6.2.3. Market share analysis, by country, 2025-2035
- 6.3. Field Management
- 6.3.1. Market definition, current market trends, growth factors, and opportunities
- 6.3.2. Market size analysis, by region, 2025-2035
- 6.3.3. Market share analysis, by country, 2025-2035
- 6.4. Risk Management
- 6.4.1. Market definition, current market trends, growth factors, and opportunities
- 6.4.2. Market size analysis, by region, 2025-2035
- 6.4.3. Market share analysis, by country, 2025-2035
- 6.5. Asset Management
- 6.5.1. Market definition, current market trends, growth factors, and opportunities
- 6.5.2. Market size analysis, by region, 2025-2035
- 6.5.3. Market share analysis, by country, 2025-2035
- Chapter 7. Global Artificial Intelligence in Construction Market Size & Forecasts by Region 2025–2035
- 7.1. Regional Overview 2025-2035
- 7.2. Top Leading and Emerging Nations
- 7.3. North America Artificial Intelligence in Construction Market
- 7.3.1. U.S. Artificial Intelligence in Construction Market
- 7.3.1.1. Component breakdown size & forecasts, 2025-2035
- 7.3.1.2. Application breakdown size & forecasts, 2025-2035
- 7.3.2. Canada Artificial Intelligence in Construction Market
- 7.3.2.1. Component breakdown size & forecasts, 2025-2035
- 7.3.2.2. Application breakdown size & forecasts, 2025-2035
- 7.3.3. Mexico Artificial Intelligence in Construction Market
- 7.3.3.1. Component breakdown size & forecasts, 2025-2035
- 7.3.3.2. Application breakdown size & forecasts, 2025-2035
- 7.4. Europe Artificial Intelligence in Construction Market
- 7.4.1. UK Artificial Intelligence in Construction Market
- 7.4.1.1. Component breakdown size & forecasts, 2025-2035
- 7.4.1.2. Application breakdown size & forecasts, 2025-2035
- 7.4.2. Germany Artificial Intelligence in Construction Market
- 7.4.2.1. Component breakdown size & forecasts, 2025-2035
- 7.4.2.2. Application breakdown size & forecasts, 2025-2035
- 7.4.3. France Artificial Intelligence in Construction Market
- 7.4.3.1. Component breakdown size & forecasts, 2025-2035
- 7.4.3.2. Application breakdown size & forecasts, 2025-2035
- 7.4.4. Spain Artificial Intelligence in Construction Market
- 7.4.4.1. Component breakdown size & forecasts, 2025-2035
- 7.4.4.2. Application breakdown size & forecasts, 2025-2035
- 7.4.5. Italy Artificial Intelligence in Construction Market
- 7.4.5.1. Component breakdown size & forecasts, 2025-2035
- 7.4.5.2. Application breakdown size & forecasts, 2025-2035
- 7.4.6. Rest of Europe Artificial Intelligence in Construction Market
- 7.4.6.1. Component breakdown size & forecasts, 2025-2035
- 7.4.6.2. Application breakdown size & forecasts, 2025-2035
- 7.5. Asia Pacific Artificial Intelligence in Construction Market
- 7.5.1. China Artificial Intelligence in Construction Market
- 7.5.1.1. Component breakdown size & forecasts, 2025-2035
- 7.5.1.2. Application breakdown size & forecasts, 2025-2035
- 7.5.2. India Artificial Intelligence in Construction Market
- 7.5.2.1. Component breakdown size & forecasts, 2025-2035
- 7.5.2.2. Application breakdown size & forecasts, 2025-2035
- 7.5.3. Japan Artificial Intelligence in Construction Market
- 7.5.3.1. Component breakdown size & forecasts, 2025-2035
- 7.5.3.2. Application breakdown size & forecasts, 2025-2035
- 7.5.4. Australia Artificial Intelligence in Construction Market
- 7.5.4.1. Component breakdown size & forecasts, 2025-2035
- 7.5.4.2. Application breakdown size & forecasts, 2025-2035
- 7.5.5. South Korea Artificial Intelligence in Construction Market
- 7.5.5.1. Component breakdown size & forecasts, 2025-2035
- 7.5.5.2. Application breakdown size & forecasts, 2025-2035
- 7.5.6. Rest of APAC Artificial Intelligence in Construction Market
- 7.5.6.1. Component breakdown size & forecasts, 2025-2035
- 7.5.6.2. Application breakdown size & forecasts, 2025-2035
- 7.6. LAMEA Artificial Intelligence in Construction Market
- 7.6.1. Brazil Artificial Intelligence in Construction Market
- 7.6.1.1. Component breakdown size & forecasts, 2025-2035
- 7.6.1.2. Application breakdown size & forecasts, 2025-2035
- 7.6.2. Argentina Artificial Intelligence in Construction Market
- 7.6.2.1. Component breakdown size & forecasts, 2025-2035
- 7.6.2.2. Application breakdown size & forecasts, 2025-2035
- 7.6.3. UAE Artificial Intelligence in Construction Market
- 7.6.3.1. Component breakdown size & forecasts, 2025-2035
- 7.6.3.2. Application breakdown size & forecasts, 2025-2035
- 7.6.4. Saudi Arabia (KSA Artificial Intelligence in Construction Market
- 7.6.4.1. Component breakdown size & forecasts, 2025-2035
- 7.6.4.2. Application breakdown size & forecasts, 2025-2035
- 7.6.5. Africa Artificial Intelligence in Construction Market
- 7.6.5.1. Component breakdown size & forecasts, 2025-2035
- 7.6.5.2. Application breakdown size & forecasts, 2025-2035
- 7.6.6. Rest of LAMEA Artificial Intelligence in Construction Market
- 7.6.6.1. Component breakdown size & forecasts, 2025-2035
- 7.6.6.2. Application breakdown size & forecasts, 2025-2035
- Chapter 8. Company Profiles
- 8.1. Top Market Strategies
- 8.2. Company Profiles
- 8.2.1. Autodesk Inc.
- 8.2.1.1. Company Overview
- 8.2.1.2. Key Executives
- 8.2.1.3. Company Snapshot
- 8.2.1.4. Financial Performance (Subject to Data Availability)
- 8.2.1.5. Product/Services Port
- 8.2.1.6. Recent Development
- 8.2.1.7. Market Strategies
- 8.2.1.8. SWOT Analysis
- 8.2.2. Oracle Corporation
- 8.2.3. IBM Corporation
- 8.2.4. Trimble Inc.
- 8.2.5. Procore Technologies
- 8.2.6. Microsoft Corporation
- 8.2.7. SAP SE
- 8.2.8. Bentley Systems
- 8.2.9. ALICE Technologies
- 8.2.10. NVIDIA Corporation
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