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Market Snapshot

CAGR:7.11

2023

2032

Source: Market Expertz

Study Period	2019-2032
Base Year	2023
Forcast Year	2023-2032
CAGR	7.11

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Report Overview

The Artificial Intelligence (AI) in Construction Market is poised to witness substantial growth, projected to achieve a Compound Annual Growth Rate (CAGR) of 6.78% from 2022 to 2032. The market size is anticipated to expand by USD 8,932.56 million. The evolution of this market hinges on a variety of factors, including the drive for increased efficiency in construction processes, the need for accurate project management, and the integration of innovative technologies to enhance safety and productivity. Artificial Intelligence in construction entails the utilization of machine learning algorithms and data-driven insights to optimize construction workflows and decision-making processes, ultimately transforming the industry's landscape.

Artificial Intelligence (AI) in Construction Market Overview:

Drivers:

A pivotal driver propelling the growth of the AI in Construction Market is the pursuit of enhanced project efficiency. Construction projects often face complexities and challenges that AI algorithms can address, from predicting potential delays to optimizing resource allocation. By harnessing AI-powered solutions, construction companies can streamline processes, mitigate risks, and ensure timely project completion.

Furthermore, the demand for accurate project management solutions is fostering the integration of AI in construction. AI-driven tools can analyze vast amounts of project data, enabling better forecasting, resource allocation, and risk assessment. Such capabilities translate into improved decision-making and project outcomes, ultimately boosting the adoption of AI in the construction sector.

Trends:

The integration of Building Information Modeling (BIM) with AI is a noteworthy trend driving the AI in Construction Market. BIM, a digital representation of a construction project, when coupled with AI algorithms, enables real-time data analysis and simulations. This synergy enhances project visualization, collaboration, and problem-solving, leading to optimized construction processes and better-informed decisions.

Additionally, the surge in demand for AI-powered predictive maintenance solutions is impacting the market growth. Construction equipment and machinery are pivotal components of any project, and AI-driven predictive maintenance can foresee potential failures, enabling proactive maintenance and minimizing downtime.

Restraints:

One of the primary challenges hindering the growth of the AI in Construction Market is the industry's traditionally slow adoption of new technologies. The construction sector has been relatively conservative in embracing technological advancements, and integrating AI requires overcoming resistance to change, addressing workforce training needs, and ensuring seamless implementation.

Data privacy and security concerns also pose a restraint to AI adoption in construction. Handling sensitive project data and ensuring its protection from cyber threats is crucial for widespread AI adoption in the industry. Compliance with data protection regulations and the establishment of secure AI-driven systems are paramount to overcoming this challenge.

AI in Construction Market Segmentation By Application:

The project planning and management segment is expected to experience significant growth during the forecast period. AI-powered tools can analyze historical project data, anticipate potential bottlenecks, and optimize resource allocation. This results in streamlined project planning, improved timelines, and enhanced cost-efficiency, addressing some of the long-standing challenges in the construction industry.

Furthermore, the quality control and defect detection segment is gaining traction. AI-powered visual recognition and image analysis technologies can identify defects, deviations, and quality issues in construction materials and components. This translates to improved construction quality, reduced rework, and enhanced client satisfaction.

AI in Construction Market Segmentation By Type:

The AI-powered predictive analytics segment is witnessing substantial growth owing to its ability to forecast potential project delays, resource shortages, and cost overruns. By analyzing historical project data and external factors, predictive analytics can offer valuable insights for proactive decision-making and risk management.

Regional Overview:

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North America is expected to contribute significantly to the global AI in Construction Market, with a projected contribution of 38%. The region's tech-savvy construction companies, coupled with a strong inclination towards innovation, are driving AI adoption. Additionally, government initiatives promoting smart city projects and sustainable construction practices are fueling the demand for AI-driven solutions in the construction sector.

The COVID-19 pandemic in 2020 disrupted construction operations, leading to a temporary slowdown in AI adoption. However, with the gradual resumption of construction activities in 2021, the market is expected to rebound, fueled by the need for digital solutions that ensure operational continuity during similar disruptions.

AI in Construction Market Customer Landscape:

The AI in Construction Market report encompasses the customer adoption lifecycle, ranging from early adopters to late adopters. It delves into regional variations in adoption rates and provides insights into key factors influencing purchase decisions and sensitivity to pricing. This information aids companies in tailoring their growth strategies to suit customer needs and preferences.

Major AI in Construction Market Companies:

Market players are implementing various strategies, including collaborations, acquisitions, geographic expansions, and product launches, to bolster their market presence.

Autodesk Inc.: The company offers AI-powered construction solutions such as Autodesk BIM 360, which enhances project collaboration, data management, and decision-making through AI-driven insights.
IBM Corporation: IBM Watson Construction Insights leverages AI to analyze project data, identify risks, and provide actionable insights for better project management and decision-making.
Oracle Corporation: Oracle's AI-driven solutions, such as Oracle Construction Intelligence Cloud Service, optimize project management by analyzing data to enhance forecasting, resource allocation, and project timelines.

The competitive landscape of the market includes detailed analyses of 15 key market players, including:

Skanska AB
Trimble Inc.
Bentley Systems, Incorporated
SAP SE
eSUB Construction Software
AECOM
Construction Robotics
NVIDIA Corporation

Qualitative and quantitative analyses assist clients in understanding the market dynamics and strengths of key players. Data is assessed to categorize companies based on focus and dominance in the AI in Construction Market.

Segment Overview:

The AI in Construction Market report projects revenue growth globally, regionally, and at the country level, providing insights into trends and opportunities from 2019 to 2032.

Application Outlook (USD Million, 2019 - 2032)

Project Planning and Management
Equipment Monitoring and Maintenance
Quality Control and Defect Detection
Risk Management
Others

Type Outlook (USD Million, 2019 - 2032)

AI-Powered Predictive Analytics
Natural Language Processing
Computer Vision
Others

Geography Outlook (USD Million, 2019 - 2032)

North America

The U.S.
Canada

Europe

U.K.
Germany
France
Rest of Europe

APAC

China
India

South America

Chile
Argentina
Brazil

Middle East & Africa

Saudi Arabia
South Africa
Rest of the Middle East & Africa

TABLE OF CONTENTS: GLOBAL ARTIFICIAL INTELLIGENCE (AI) IN CONSTRUCTION MARKET

Chapter 1. MARKET SYNOPSIS

1.1. Market Definition

1.2. Research Scope & Premise

1.3. Methodology

1.4. Market Estimation Technique

Chapter 2. EXECUTIVE SUMMARY

2.1. Summary Snapshot, 2016 – 2027

Chapter 3. INDICATIVE METRICS

3.1. Macro Indicators

Chapter 4. ARTIFICIAL INTELLIGENCE (AI) IN CONSTRUCTION MARKET SEGMENTATION & IMPACT ANALYSIS

4.1. Artificial Intelligence (AI) in Construction Segmentation Analysis

4.2. Industrial Outlook

4.3. Price Trend Analysis

4.4. Regulatory Framework

4.5. Porter’s Five Forces Analysis

4.5.1. Power Of Suppliers

4.5.2. Power Of Buyers

4.5.3. Threat Of Substitutes

4.5.4. Threat Of New Entrants

4.5.5. Competitive Rivalry

Chapter 5. ARTIFICIAL INTELLIGENCE (AI) IN CONSTRUCTION MARKET BY Component INSIGHTS & TRENDS

5.1. Segment 1 Dynamics & Market Share, 2019 & 2027

5.2. Services

5.2.1. Market Estimates And Forecast, 2016 – 2027 (USD Million)

5.2.2. Market Estimates And Forecast, By Region, 2016 – 2027 (USD Million)

5.3. Solutions

5.3.1. Market Estimates And Forecast, 2016 – 2027 (USD Million)

5.3.2. Market Estimates And Forecast, By Region, 2016 – 2027 (USD Million)

Chapter 6. ARTIFICIAL INTELLIGENCE (AI) IN CONSTRUCTION MARKET BY Organization Size INSIGHTS & TRENDS

6.1. Segment 2 Dynamics & Market Share, 2019 & 2027

6.2. Small and Medium-Sized Enterprises

6.2.1. Market Estimates And Forecast, 2016 – 2027 (USD Million)

6.2.2. Market Estimates And Forecast, By Region, 2016 – 2027 (USD Million)

6.3. Large Enterprises

6.3.1. Market Estimates And Forecast, 2016 – 2027 (USD Million)

6.3.2. Market Estimates And Forecast, By Region, 2016 – 2027 (USD Million)

Chapter 7. ARTIFICIAL INTELLIGENCE (AI) IN CONSTRUCTION MARKET REGIONAL OUTLOOK

7.1. Artificial Intelligence (AI) in Construction Market Share By Region, 2019 & 2027

7.2. NORTH AMERICA

7.2.1. North America Artificial Intelligence (AI) in Construction Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.2.2. North America Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.2.3. North America Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.2.4. North America Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.2.5. U.S.

7.2.5.1. U.S. Artificial Intelligence (AI) in Construction Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.2.5.2. U.S. Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.2.5.3. U.S. Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.2.5.4. U.S. Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.2.6. CANADA

7.2.6.1. Canada Artificial Intelligence (AI) in Construction Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.2.6.2. Canada Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.2.6.3. Canada Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.2.6.4. Canada Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.3. EUROPE

7.3.1. Europe Artificial Intelligence (AI) in Construction Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.3.2. Europe Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.3.3. Europe Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.3.4. Europe Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.3.5. GERMANY

7.3.5.1. Germany Artificial Intelligence (AI) in Construction Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.3.5.2. Germany Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.3.5.3. Germany Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.3.5.4. Germany Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.3.6. FRANCE

7.3.6.1. France Artificial Intelligence (AI) in Construction Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.3.6.2. France Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.3.6.3. France Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.3.6.4. France Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.3.7. U.K.

7.3.7.1. U.K. Artificial Intelligence (AI) in Construction Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.3.7.2. U.K. Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.3.7.3. U.K. Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.3.7.4. U.K. Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.4. ASIA-PACIFIC

7.4.1. Asia Pacific Artificial Intelligence (AI) in Construction Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.4.2. Asia Pacific Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.4.3. Asia Pacific Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.4.4. Asia Pacific Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.4.5. CHINA

7.4.5.1. China Artificial Intelligence (AI) in Construction Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.4.5.2. China Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.4.5.3. China Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.4.5.4. China Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.4.6. INDIA

7.4.6.1. India Artificial Intelligence (AI) in Construction Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.4.6.2. India Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.4.6.3. India Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.4.6.4. India Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.4.7. JAPAN

7.4.7.1. Japan Artificial Intelligence (AI) in Construction Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.4.7.2. Japan Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.4.7.3. Japan Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.4.7.4. Japan Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.4.8. AUSTRALIA

7.4.8.1. Australia Artificial Intelligence (AI) in Construction Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.4.8.2. Australia Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.4.8.3. Australia Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.4.8.4. Australia Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.5. MIDDLE EAST AND AFRICA (MEA)

7.5.1. Mea Artificial Intelligence (AI) in Construction Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.5.2. Mea Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.5.3. Mea Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.5.4. Mea Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

7.6. LATIN AMERICA

7.6.1. Latin America Artificial Intelligence (AI) in Construction Market Estimates And Forecast, 2016 – 2027, (USD Million)

7.6.2. Latin America Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 1, 2016 –2027, (USD Million)

7.6.3. Latin America Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 2, 2016 –2027, (USD Million)

7.6.4. Latin America Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Production Process, 2016 –2027, (USD Million)

7.6.5. Latin America Artificial Intelligence (AI) in Construction Market Estimates And Forecast By Segment 3, 2016 –2027, (USD Million)

Chapter 8. COMPETITIVE LANDSCAPE

8.1. Market Share By Manufacturers

8.2. Strategic Benchmarking

8.2.1. New Product Launches

8.2.2. Investment & Expansion

8.2.3. Acquisitions

8.2.4. Partnerships, Agreement, Mergers, Joint-Ventures

8.3. Vendor Landscape

8.3.1. North American Suppliers

8.3.2. European Suppliers

8.3.3. Asia-Pacific Suppliers

8.3.4. Rest Of The World Suppliers

Chapter 9. COMPANY PROFILES

9.1. IBM

9.1.1. Company Overview

9.1.2. Financial Performance

9.1.3. Product Insights

9.1.4. Strategic Initiatives

9.2. Renoworks Software

9.2.1. Company Overview

9.2.2. Financial Performance

9.2.3. Product Insights

9.2.4. Strategic Initiatives

9.3. Microsoft

9.3.1. Company Overview

9.3.2. Financial Performance

9.3.3. Product Insights

9.3.4. Strategic Initiatives

9.4. Autodesk

9.4.1. Company Overview

9.4.2. Financial Performance

9.4.3. Product Insights

9.4.4. Strategic Initiatives

9.5. SAP

9.5.1. Company Overview

9.5.2. Financial Performance

9.5.3. Product Insights

9.5.4. Strategic Initiatives

9.6. Oracle

9.6.1. Company Overview

9.6.2. Financial Performance

9.6.3. Product Insights

9.6.4. Strategic Initiatives

9.7. Alice Technologies

9.7.1. Company Overview

9.7.2. Financial Performance

9.7.3. Product Insights

9.7.4. Strategic Initiatives

9.8. Building System Planning

9.8.1. Company Overview

9.8.2. Financial Performance

9.8.3. Product Insights

9.8.4. Strategic Initiatives

9.9. eSUB

9.9.1. Company Overview

9.9.2. Financial Performance

9.9.3. Product Insights

9.9.4. Strategic Initiatives

9.10. Askporter

9.10.1. Company Overview

9.10.2. Financial Performance

9.10.3. Product Insights

9.10.4. Strategic Initiatives

RESEARCH METHODOLOGY

A research methodology is a systematic approach for assessing or conducting a market study. Researchers tend to draw on a variety of both qualitative and quantitative study methods, inclusive of investigations, survey, secondary data and market observation.

Such plans can focus on classifying the products offered by leading market players or simply use statistical models to interpret observations or test hypotheses. While some methods aim for a detailed description of the factors behind an observation, others present the context of the current market scenario.

Now let’s take a closer look at the research methods here.

Secondary Research Model

Extensive data is obtained and cumulated on a substantial basis during the inception phase of the research process. The data accumulated is consistently filtered through validation from the in-house database, paid sources as well reputable industry magazines. A robust research study requires an understanding of the overall value chain. Annual reports and financials of industry players are studied thoroughly to have a comprehensive idea of the market taxonomy.

Primary Insights

Post conglomeration of the data obtained through secondary research; a validation process is initiated to verify the numbers or figures. This process is usually performed by having a detailed discussion with the industry experts.

However, we do not restrict our primary interviews only to the industry leaders. Our team covers the entire value chain while verifying the data. A significant number of raw material suppliers, local manufacturers, distributors, and stakeholders are interviewed to make our findings authentic. The current trends which include the drivers, restraints, and opportunities are also derived through the primary research process.

Market Estimation

The market estimation is conducted by analyzing the data collected through both secondary and primary research. This process involves market breakdown, bottom-up and top- down approach.

Moreover, while forecasting the market a comprehensive statistical time series model is designed for each market. Macroeconomic indicators are considered to understand the current trends of the market. Each data point is verified by the process of data triangulation method to arrive at the final market estimates.

Final Presentation

The penultimate process results in a holistic research report. The study equips key industry players to undertake significant strategic decisions through the findings. The report encompasses detailed market information. Graphical representations of the current market trends are also made available in order to make the study highly comprehensible for the reader.

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Artificial Intelligence Ai In Construction Market Size, Type Analysis, Application Analysis, End-Use, Industry Analysis, Regional Outlook, Competitive Strategies And Forecasts, 2023-2032