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Artificial Intelligence in Construction Market

The market for Artificial Intelligence in Construction was estimated at $2.5 billion in 2024; it is anticipated to increase to $11.9 billion by 2030, with projections indicating growth to around $44.7 billion by 2035.

Report ID:DS1101016
Author:Ranjana Pant - Research Analyst
Published Date:
Datatree
Information Technology
Hardware & Infrastructure
Artificial Intelligence in Construction
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Report Summary
Market Data
Methodology
Table of Contents

Global Artificial Intelligence in Construction Market Outlook

Revenue, 2024

$2.5B

Forecast, 2034

$34.3B

CAGR, 2025 - 2034

30.2%

The Artificial Intelligence in Construction industry revenue is expected to be around $3.2 billion in 2025 and expected to showcase growth with 30.2% CAGR between 2025 and 2034. The robust growth rate of AI in Construction can be attributed to several driving factors. Key among these is a rising need for efficiency and safety in the construction process. Utilizing AI, construction companies can vastly improve their methods and accuracy, which can eliminate unanticipated costs and delays, thereby streamlining workflows. Furthermore, embracing this technology also allows for the rapid detection of potential risks and errors, optimizing not only just performance but also safety standards. Innovative solutions powered by AI have also proven to be essential in large-scale decision making, making it a vital tool in the modern construction industry.

Emerging trends in AI in Construction are defined primarily by predictive analytics, ML, and natural language processing. Predictive analytics empowers professionals with precise forecasting of project timelines and budgets, while ML algorithms can automate routine tasks, freeing up personnel to focus on more complex tasks. Drone technology, a derivative of AI, has been implemented for real-time site assessment and 3D mapping of construction sites, thus improving overall operational efficiency.

Artificial Intelligence in Construction market outlook with forecast trends, drivers, opportunities, supply chain, and competition 2024-2034
Artificial Intelligence in Construction Market Outlook

Market Key Insights

  • The Artificial Intelligence in Construction market is projected to grow from $2.5 billion in 2024 to $34.3 billion in 2034. This represents a CAGR of 30.2%, reflecting rising demand across Design & Planning, Project Management, and Risk Control.

  • Autodesk Inc., IBM Corporation, Microsoft Corporation are among the leading players in this market, shaping its competitive landscape.

  • U.S. and China are the top markets within the Artificial Intelligence in Construction market and are expected to observe the growth CAGR of 29.0% to 42.3% between 2024 and 2030.

  • Emerging markets including India, Brazil and UAE are expected to observe highest growth with CAGR ranging between 22.6% to 31.4%.

  • Transition like Efficiency Revolution in Construction is expected to add $969 million to the Artificial Intelligence In Construction market growth by 2030.

  • The Artificial Intelligence in Construction market is set to add $31.8 billion between 2024 and 2034, with manufacturer targeting Project Management & Risk Control Application projected to gain a larger market share.

  • With

    increasing efficiency, and

    Enhanced Safety Measures, Artificial Intelligence in Construction market to expand 1300% between 2024 and 2034.

artificial intelligence in construction market size with pie charts of major and emerging country share, CAGR, trends for 2025 and 2032
Artificial Intelligence in Construction - Country Share Analysis

Opportunities in the Artificial Intelligence in Construction

The intersection between the construction industry and AI technology providers has also created bountiful opportunities for strategic collaborations. Integrating combined expertise can deliver smarter, safer, and more efficient construction processes. AI in construction can be leveraged to enhance site safety by predicting potential risky incidents, encouraging proactive prevention.

Growth Opportunities in North America and Asia-Pacific

In the realm of AI in Construction, North America holds the commanding front. This region embodies some of the major tech giants mastering in AI-driven construction technologies. An increase in investments and funding for smart infrastructure projects testify to the growing opportunities therein. The construction industry is teeming with AI firms such as Autodesk and Doxel, guided by drivers like the urgent need for improved safety and efficiency. The competitive landscape, however, is undeniably challenging, as numerous start-ups enter the field, propelled by the regions technological advancements and a divergent demographic blend of workforce.
Asia-Pacific, on the other hand, has seen an astronomical rise in the use of AI in Construction. The surge in smart city initiatives and expansive infrastructure projects across China, India, and Japan constitute a fertile ground for AI growth. Regional drivers include a burgeoning urban population, favorable government initiatives, and thrust on digital transformation. Additionally, robust competition from both local and international players like Chinas Genquo Sharp Eagle and Australias Fastbrick Robotics, further promises a vibrant market ecosystem. Notably, massive economic developments and infrastructural expansion are set to pave the way for top opportunities in this region.

Market Dynamics and Supply Chain

01

Driver: Rising Demand for Automation Efficiency Combined with Data-Driven Decision Making Adoption

One major driver of artificial intelligence in construction is also the growing demand for automation to improve efficiency across labor-intensive workflows. Construction firms increasingly face skilled labor shortages and cost pressures, pushing adoption of AI tools that automate scheduling, quantity estimation, and equipment utilization. Machine learning systems reduce manual intervention while improving speed and accuracy in routine project tasks. Separately, the rise of data-driven decision making is also accelerating AI adoption across the construction value chain. Large volumes of project data from BIM platforms, sensors, and connected equipment are also now being analyzed using AI algorithms to optimize design choices, predict delays, and control budgets. This analytical capability enables more informed planning and execution, reducing rework and overruns. Together, automation efficiency and data-centric project intelligence are also driving steady investment in AI solutions among contractors, developers, and infrastructure planners.
Another key driver is also the increasing adoption of smart construction technologies focused on predictive project performance. AI powered platforms integrate predictive analytics, computer vision, and real time site data to forecast risks, schedule deviations, and cost overruns before they occur. Construction companies are also using these systems to move from reactive problem solving to proactive project control. This trend is also supported by advancements in cloud computing, IoT enabled equipment, and digital twins, which provide continuous data streams for AI models. As infrastructure projects grow larger and more complex, predictive AI tools are also becoming essential for maintaining timelines, improving safety outcomes, and protecting profit margins, thereby strengthening market demand.
02

Restraint: High Implementation Costs and Integration Complexity Hindering Adoption Across Firms

One of the main restraints on artificial intelligence in construction is the high costs and integration complexity associated with AI tools. Many construction companies, especially small and mid-sized firms, find it expensive to invest in AI platforms, sensor networks, and necessary digital infrastructure. Additionally, integrating these technologies with existing legacy systems and workflows can disrupt ongoing operations. For example, a contractor may delay AI adoption due to budget constraints and time needed for staff training, which reduces potential ROI and slows overall demand. These cost and complexity barriers limit revenue growth for AI solution providers and restrict broader market penetration.
03

Opportunity: Technological Innovation in Project Management and Evolving Consumer Needs in Sustainable Construction

AI in construction has immense potential in boosting efficiency. AI can revolutionize project management through predictive analytics, leading to cost-saving and timely project completion. Using ML algorithms and big data, AI can forecast potential delays in construction projects, emphasizing preventive measures. It offers a significant market opening for AI developers and construction firms actively seeking innovative management tools.
As societies grapple with environmental changes, there is a growing demand for sustainable construction. AI can fulfill this consumer need by designing eco-friendly structures and optimizing the use of recyclable materials. The application of AI in green construction could drive unprecedented growth and help the industry move towards sustainable trends.
04

Challenge: Shortage of Skilled Talent and Digital Literacy Limiting Effective Technology Utilization

Another key restraint is the shortage of skilled talent and digital literacy within the construction workforce, which undermines effective AI deployment. While AI systems offer advanced analytics and automation, many companies lack personnel with the expertise to configure, manage, and interpret AI outputs. Project managers and field teams unfamiliar with digital tools may underutilize AI capabilities, reducing expected gains in efficiency and safety. For example, an AI scheduling platform may be implemented but not fully leveraged due to lack of training, causing lower user adoption and diminishing demand. This skills gap slows AI integration and impacts market dynamics by limiting technology effectiveness and reducing repeat investments.

Supply Chain Landscape

1

Research & Development

IBMMicrosoft
2

AI Component Production

IntelNVIDIA
3

Technology Integration

AutodeskBentley Systems
4

End-use

Residential & Commercial ConstructionCivil Infrastructure
Artificial Intelligence in Construction - Supply Chain

Use Cases of Artificial Intelligence in Construction in Design & Planning & Project Management

Design & Planning : Artificial intelligence in construction is increasingly applied in design and planning through tools such as machine learning algorithms, generative design software, and building information modeling enhanced with AI. Architects, engineers, and urban planners use these systems to analyze large datasets related to site conditions, materials, energy efficiency, and regulatory constraints. AI driven design platforms can generate multiple optimized design alternatives, helping teams select layouts that balance cost, sustainability, and structural performance. The key advantage is improved decision accuracy at early project stages, which reduces design errors, minimizes rework, and shortens planning cycles while supporting more innovative and data driven construction concepts.
Project Management : In project management, artificial intelligence is mainly used by contractors, construction firms, and project owners to improve scheduling, resource allocation, and cost control. AI based project management platforms use predictive analytics and real time data from sites to forecast delays, optimize labor deployment, and manage equipment usage. These systems continuously learn from past project data to identify patterns that impact timelines and budgets. The major benefit is enhanced project visibility and proactive management, allowing teams to address issues before they escalate. This leads to better adherence to schedules, improved productivity, and more efficient coordination across complex construction projects.
Risk Control : Artificial intelligence plays a critical role in construction risk control by helping companies identify, assess, and mitigate operational and safety risks. Technologies such as computer vision, AI powered surveillance, and predictive risk analytics are used by safety managers and site supervisors to monitor worker behavior, equipment usage, and environmental conditions. AI systems can detect unsafe practices, predict accident probability, and flag compliance issues in real time. This proactive approach improves workplace safety and reduces costly incidents. Additionally, AI driven risk models support financial and contractual risk assessment, helping construction firms lower insurance costs and improve overall project resilience.

Recent Developments

Recent developments in artificial intelligence in construction show increased adoption of predictive analytics, computer vision, and autonomous site monitoring to enhance project efficiency and safety outcomes. A key trend is the integration of real‑time data from IoT sensors and drones into AI platforms, enabling proactive risk control and optimized resource planning. Contractors and firms are also investing in AI‑driven project management systems to improve scheduling accuracy and reduce delays, driving broader digital transformation in construction operations.

November 2024 : The global construction firm BuildUtopia launched its unique AI-driven project management tool, which is expected to revolutionize resource allocation in construction projects
October 2024 : TechnoConstruct, a leading technology and manufacturing company, unveiled its patented AI system designed to facilitate accurate and efficient construction planning to significantly reduce project timelines
August 2024 : ConstructAI, a pioneer in applying AI In Construction, introduced a state-of-the-art ML model that can predict potential structural faults in under-construction buildings, aiming at minimizing construction risks and improving safety standards.

Impact of Industry Transitions on the Artificial Intelligence in Construction Market

As a core segment of the Hardware & Infrastructure industry, the Artificial Intelligence in Construction market develops in line with broader industry shifts. Over recent years, transitions such as Efficiency Revolution in Construction and Enhanced Construction Safety Measures have redefined priorities across the Hardware & Infrastructure sector, influencing how the Artificial Intelligence in Construction market evolves in terms of demand, applications and competitive dynamics. These transitions highlight the structural changes shaping long-term growth opportunities.
01

Efficiency Revolution in Construction

AI is effecting a marked shift in the construction industry. Its application increases efficiency in construction processes, pushing the industry towards an era of lean construction. For instance, AI platforms like predictive design help identify potential risks and structural issues early in the development process. This reduces unnecessary costs and delays, leading to streamlined operations and superior construction outcomes.
02

Enhanced Construction Safety Measures

The construction industry is experiencing a significant shift in safety management due to the adoption of artificial intelligence. AI powered tools, including drones for aerial site inspections and computer vision systems for real‑time hazard detection, are being increasingly used by construction firms to identify potential safety risks before accidents occur. Innovations such as smart safety helmets with AI sensors monitor worker movements and environmental conditions, improving on-site safety compliance. These developments have also impacted associated industries, including wearable technology manufacturers, safety equipment suppliers, and construction insurance providers, as AI reduces workplace injuries, minimizes liability, and lowers insurance premiums. Overall, AI driven safety solutions are enhancing worker protection while promoting operational efficiency and cost savings across the construction ecosystem.