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PUBLISHER: Astute Analytica | PRODUCT CODE: 1881351

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PUBLISHER: Astute Analytica | PRODUCT CODE: 1881351

Global Digital Twin for Buildings Market: By Component, Type, Application, Industry - Market Size, Industry Dynamics, Opportunity Analysis and Forecast for 2025-2033

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The global digital twin for buildings market is undergoing rapid expansion, reflecting a growing recognition of the technology's transformative potential across the construction and facilities management sectors. Valued at US$ 2.07 billion in 2024, the market is projected to soar to an impressive US$ 26.23 billion by 2033. This represents a compound annual growth rate (CAGR) of 32.6% during the forecast period from 2025 to 2033, underscoring the accelerating adoption and increasing importance of digital twin solutions worldwide.

The primary forces driving this remarkable growth are the pressing demands for enhanced operational efficiency, predictive maintenance, and sustainability within the built environment. Building owners and managers are increasingly seeking ways to optimize resource use, reduce energy consumption, and minimize downtime, all while maintaining occupant comfort and safety. Digital twins provide a sophisticated platform to achieve these goals by creating highly detailed, real-time digital replicas of physical buildings that enable continuous monitoring and analysis.

Noteworthy Market Developments

Key market players in the digital twin for buildings sector are dominated by large technology and engineering firms such as Siemens, Autodesk, IBM, and Microsoft. These companies compete fiercely by offering comprehensive portfolios that encompass not only software solutions but also hardware components like sensors and drones, alongside a wide array of services. Their strategic focus lies in integrating digital twin technology with other emerging technologies, notably artificial intelligence (AI), to enhance the intelligence and responsiveness of digital models.

In November 2025, a significant development unfolded with the launch of The Digital Twin Appstore at the Smart City Expo World Congress in Barcelona. This innovative platform consolidates verified offerings from an expanding network of vendors and organizations, creating a centralized marketplace for digital twin tools, services, and datasets. Another notable advancement occurred in October 2025 when Jensen Huang, the founder and CEO of NVIDIA, introduced NVIDIA Omniverse DSX. This platform represents a comprehensive, open blueprint specifically engineered for designing and operating gigawatt-scale AI factories.

Core Growth Drivers

A significant demand driver in the digital twin for buildings market is the urgent need to retrofit existing buildings to enhance sustainability and improve efficiency. As awareness of environmental issues intensifies and regulatory pressures mount, governments and corporations are prioritizing the modernization of aging infrastructure to meet contemporary energy and performance standards. Retrofitting older buildings presents a unique challenge, as many were not originally designed with energy efficiency or smart technology integration in mind. Digital twin technology offers a powerful solution by enabling detailed monitoring, analysis, and optimization of building systems without requiring complete reconstruction.

Emerging Opportunity Trends

A tremendous opportunity is emerging in the integration of generative artificial intelligence (AI) with digital twin technology, transforming the capabilities of building management systems far beyond basic monitoring. This fusion enables the creation of predictive, self-optimizing buildings that can adapt dynamically to changing conditions and demands. By incorporating generative AI algorithms, digital twins can simulate thousands of operational scenarios, providing a level of insight and foresight that was previously unattainable. These advanced models allow building owners and managers to anticipate future needs and challenges, enabling proactive decision-making that enhances efficiency, comfort, and sustainability.

Barriers to Optimization

The high initial investment and implementation costs associated with digital twin technology present a significant challenge that could hamper the overall growth of the market. Developing and deploying digital twin solutions requires substantial financial resources, particularly due to the need for advanced hardware, such as IoT sensors, data storage infrastructure, and high-performance computing capabilities. These upfront expenditures can be prohibitive for many organizations, especially small and medium-sized enterprises that may lack the capital to invest in such sophisticated technology. The complexity of integrating digital twins into existing building management systems also adds to the financial burden, often requiring specialized expertise and extensive customization.

Detailed Market Segmentation

By component, the software component dominates the digital twins for buildings market, holding the largest share at 77.30%, and is also projected to experience the fastest growth with a remarkable CAGR of 32.80% during the forecast period. This commanding position is driven by the development of sophisticated software platforms that seamlessly integrate cutting-edge technologies such as the Internet of Things (IoT), artificial intelligence (AI), and advanced analytics. These platforms enable the creation of dynamic and manageable digital replicas of physical buildings, allowing for real-time monitoring, simulation, and optimization of building performance.

By type, the informative twin is expected to maintain its dominant position within the global digital twins for buildings market, projected to generate the highest market revenue share of 27.51%. This type of digital twin plays a crucial role by creating a comprehensive digital representation of a building's physical assets, which is continuously updated with real-time data to facilitate ongoing monitoring and analysis. The value of an informative twin lies in its dynamic nature, as it goes beyond static modeling by reflecting the current state of the building throughout its lifecycle.

By application, the resource management and logistics segment accounts for 21.87% of the market. This significant share underscores the increasing recognition of digital twins as powerful tools for enhancing operational efficiency and providing predictive oversight across building management processes. The clear return on investment in these areas is a major factor driving adoption, as organizations seek to optimize resource use, reduce downtime, and extend the lifespan of critical infrastructure components.

By industry, the construction industry is poised to become a major consumer of digital twin technology within the buildings market, reflecting a growing trend toward digital transformation in how projects are designed, planned, and executed. One of the most notable impacts of this shift is the integration of artificial intelligence (AI) with Building Information Modeling (BIM) workflows, which is expected to streamline project delivery times throughout 2025 and beyond. By enhancing BIM with AI capabilities, construction teams can automate complex analyses, detect potential issues early, and optimize design parameters more efficiently than ever before.

Segment Breakdown

By Component

  • Software
  • Cloud
  • On-premise
  • Services
  • Professional
  • Managed

By Type

  • Descriptive twin
  • Informative twin
  • Predictive twin
  • Comprehensive twin
  • Autonomous twin

By Application

  • Automated Progress Monitoring
  • As-executed Vs. As-planned Models
  • Resource Management and Logistics
  • Safety Monitoring
  • Quality Assessment
  • Optimization Of Equipment Usage
  • Monitoring And Tracking Of Workers

By Industry

  • Manufacturing
  • Aerospace & Defense
  • Oil & Gas
  • Utilities
  • Healthcare & Life Sciences
  • Automotive
  • Construction
  • IT & Telecom
  • Retail
  • Consumer Goods & Packaging
  • Transportation
  • Smart Cities
  • Other

By Region

  • North America
  • The U.S.
  • Canada
  • Mexico
  • Europe
  • Western Europe
  • The UK
  • Germany
  • France
  • Italy
  • Spain
  • Rest of Western Europe
  • Eastern Europe
  • Poland
  • Russia
  • Rest of Eastern Europe
  • Asia Pacific
  • China
  • India
  • Japan
  • Australia & New Zealand
  • South Korea
  • ASEAN
  • Rest of Asia Pacific
  • Middle East & Africa (MEA)
  • Saudi Arabia
  • South Africa
  • UAE
  • Rest of MEA
  • South America
  • Argentina
  • Brazil
  • Rest of South America

Geography Breakdown

  • North America holds a commanding position in the digital twin for buildings market, controlling a dominant 46.82% share, which is largely fueled by robust investments from both public and private sectors. This region's leadership is underpinned by a growing recognition of the value digital twins bring to building design, operation, and maintenance, driving widespread adoption across various projects and initiatives. In 2024, the U.S. General Services Administration (GSA) took a significant step by mandating the use of digital twin technology for 10 of its new federal building projects.
  • Meanwhile, in Canada, a major smart city initiative in Toronto is pushing the boundaries of digital twin deployment by planning to install 50,000 Internet of Things (IoT) sensors across 25 downtown commercial buildings by 2025. This ambitious project aims to create a highly connected urban environment where digital twins can provide real-time data and analytics to optimize building performance, energy consumption, and occupant comfort.

Leading Market Participants

  • ABB
  • Accenture PLC
  • Ansys, Inc.
  • Priori Technologies, Inc.
  • Bentley Systems, Incorporated
  • Cisco Systems, Inc.
  • Dassault Systemes, Inc.
  • DHL International GmbH.
  • DXC Technology Company
  • GE Digital (Predix)
  • IBM Corporation
  • Microsoft Azure
  • Oracle Corporation
  • PTC Inc.
  • Robert Bosch GmbH
  • SAP SE
  • Siemens AG
  • Other Major Players
Product Code: AA0923603

Table of Content

Chapter 1. Research Framework

  • 1.1. Research Objective
  • 1.2. Product Overview
  • 1.3. Market Segmentation

Chapter 2. Research Methodology

  • 2.1. Qualitative Research
    • 2.1.1. Primary & Secondary Sources
  • 2.2. Quantitative Research
    • 2.2.1. Primary & Secondary Sources
  • 2.3. Breakdown of Primary Research Respondents, By Region
  • 2.4. Assumption for the Study
  • 2.5. Market Size Estimation
  • 2.6. Data Triangulation

Chapter 3. Executive Summary: Global Digital Twins for Buildings Market

Chapter 4. Global Digital Twins for Buildings Market Overview

  • 4.1. Industry Value Chain Analysis
  • 4.2. Key Trends in Digital Twins for Buildings Market
  • 4.3. PESTLE Analysis
  • 4.4. Porter's Five Forces Analysis
    • 4.4.1. Bargaining Power of Suppliers
    • 4.4.2. Bargaining Power of Buyers
    • 4.4.3. Threat of Substitutes
    • 4.4.4. Threat of New Entrants
    • 4.4.5. Degree of Competition
  • 4.5. Market Dynamics and Trends
    • 4.5.1. Growth Drivers
    • 4.5.2. Restraints
    • 4.5.3. Challenges
    • 4.5.4. Key Trends
  • 4.6. Covid-19 Impact Assessment on Market Growth Trend
  • 4.7. Market Growth and Outlook
    • 4.7.1. Market Revenue Estimates and Forecast (US$ Bn), 2019 - 2032
  • 4.8. Competition Dashboard
    • 4.8.1. Market Concentration Rate
    • 4.8.2. Company Market Share Analysis (Value %), 2023
    • 4.8.3. Competitor Mapping

Chapter 5. Global Digital Twins for Buildings Market Analysis, By Component

  • 5.1. Key Insights
  • 5.2. Market Size and Forecast, 2019 - 2032 (US$ Bn)
    • 5.2.1. Software
      • 5.2.1.1. On-premise
      • 5.2.1.2. Cloud
    • 5.2.2. Services
      • 5.2.2.1. Professional
      • 5.2.2.2. Managed

Chapter 6. Global Digital Twins for Buildings Market Analysis, By Type

  • 6.1. Key Insights
  • 6.2. Market Size and Forecast, 2019 - 2032 (US$ Bn)
    • 6.2.1 Descriptive twin
    • 6.2.2 Informative twin
    • 6.2.3 Predictive twin
    • 6.2.4 Comprehensive twin
    • 6.2.5 Autonomous twin

Chapter 7. Global Digital Twins for Buildings Market Analysis, By Application

  • 7.1. Key Insights
  • 7.2. Market Size and Forecast, 2019 - 2032 (US$ Bn)
    • 7.2.1. Automated Progress Monitoring
    • 7.2.2. As-executed Vs. As-planned Models
    • 7.2.3. Resource Management and Logistics
    • 7.2.4. Safety Monitoring
    • 7.2.5. Quality Assessment
    • 7.2.6. Optimization Of Equipment Usage
    • 7.2.7. Monitoring And Tracking Of Workers

Chapter 8. Global Digital Twins for Buildings Market Analysis, By Industry

  • 8.1. Key Insights
  • 8.2. Market Size and Forecast, 2019 - 2032 (US$ Bn)
    • 8.2.1. Manufacturing
    • 8.2.2. Aerospace & Defense
    • 8.2.3. Oil & Gas
    • 8.2.4. Utilities
    • 8.2.5. Healthcare & Life Sciences
    • 8.2.6. Automotive
    • 8.2.7. Construction
    • 8.2.8. IT & Telecom
    • 8.2.9. Retail
    • 8.2.10. Consumer Goods & Packaging
    • 8.2.11. Transportation
    • 8.2.12. Smart Cities
    • 8.2.13. Others

Chapter 9. Global Digital Twins for Buildings Market Analysis, By Region

  • 9.1. Key Insights
  • 9.2. Market Size and Forecast, 2019 - 2032 (US$ Bn)
    • 9.2.1. North America
      • 9.2.1.1. The U.S.
      • 9.2.1.2. Canada
      • 9.2.1.3. Mexico
    • 9.2.2. Europe
      • 9.2.2.1. The U.K.
      • 9.2.2.2. Germany
      • 9.2.2.3. France
      • 9.2.2.4. Spain
      • 9.2.2.5. Russia
      • 9.2.2.6. Rest of Europe
    • 9.2.3. Asia Pacific
      • 9.2.3.1. China
      • 9.2.3.2. Japan
      • 9.2.3.3. India
      • 9.2.3.4. Australia & New Zealand
      • 9.2.3.5. Korea
      • 9.2.3.6. ASEAN
      • 9.2.3.7. Rest of Asia Pacific
    • 9.2.4. South America
      • 9.2.4.1. Argentina
      • 9.2.4.2. Brazil
      • 9.2.4.3. Rest of South America
    • 9.2.5. Middle East & Africa
      • 9.2.5.1. UAE
      • 9.2.5.2. Saudi Arabia
      • 9.2.5.3. South Africa
      • 9.2.5.4. Rest of Middle East & Africa

Chapter 10. North America Digital Twins for Buildings Market Analysis

  • 10.1. Key Insights
  • 10.2. Market Size and Forecast, 2019 - 2032 (US$ Bn)
    • 10.2.1. By Component
    • 10.2.2. By Type
    • 10.2.3. By Application
    • 10.2.4. By Industry
    • 10.2.5. By Country

Chapter 11. Europe Digital Twins for Buildings Market Analysis

  • 11.1. Key Insights
  • 11.2. Market Size and Forecast, 2019 - 2032 (US$ Bn)
    • 11.2.1. By Component
    • 11.2.2. By Type
    • 11.2.3. By Application
    • 11.2.4. By Industry
    • 11.2.5. By Country

Chapter 12. Asia Pacific Digital Twins for Buildings Market Analysis

  • 12.1. Key Insights
  • 12.2. Market Size and Forecast, 2019 - 2032 (US$ Bn)
    • 12.2.1. By Component
    • 12.2.2. By Type
    • 12.2.3. By Application
    • 12.2.4. By Industry
    • 12.2.5. By Country/Region

Chapter 13. South America Digital Twins for Buildings Market Analysis

  • 13.1. Key Insights
  • 13.2. Market Size and Forecast, 2019 - 2032 (US$ Bn)
    • 13.2.1. By Component
    • 13.2.2. By Type
    • 13.2.3. By Application
    • 13.2.4. By Industry
    • 13.2.5. By Country

Chapter 14. Middle East & Africa Digital Twins for Buildings Market Analysis

  • 14.1. Key Insights
  • 14.2. Market Size and Forecast, 2019 - 2032 (US$ Bn)
    • 14.2.1. By Component
    • 14.2.2. By Type
    • 14.2.3. By Application
    • 14.2.4. By Industry
    • 14.2.5. By Country

Chapter 15. Company Profile (Company Overview, Financial Matrix, Key Product landscape, Key Personnel, Key Competitors, Contact Address, and Business Strategy Outlook)

  • 15.1. ABB
  • 15.2. Accenture PLC
  • 15.3. Ansys, Inc.
  • 15.4. Priori Technologies, Inc.
  • 15.5. Bentley Systems, Incorporated
  • 15.6. Cisco Systems, Inc.
  • 15.7. Dassault Systems, Inc.
  • 15.8. DHL International GmbH.
  • 15.9. DXC Technology Company
  • 15.10. GE Digital (Predix)
  • 15.11. IBM Corporation
  • 15.12. Microsoft Azure
  • 15.13. Oracle Corporation
  • 15.14. PTC Inc.
  • 15.15. Robert Bosch GmbH
  • 15.16. SAP SE
  • 15.17. Siemens AG
  • 15.18. Other Major Players
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Jeroen Van Heghe

Manager - EMEA

+32-2-535-7543

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Christine Sirois

Manager - Americas

+1-860-674-8796

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