全球建筑数位孪生市场：依组件、类型、应用和产业划分－市场规模、产业趋势、机会分析和预测（2025-2033 年）

全球建筑数位孪生市场持续快速成长，反映出人们对这项技术在建筑和设施管理领域变革潜力的认识不断提高。 2024 年，该市场规模为 20.7 亿美元，预计到 2033 年将呈指数级增长，达到惊人的 262.3 亿美元。这意味着 2025 年至 2033 年的复合年增长率 (CAGR) 为 32.6%，凸显了数位孪生解决方案在全球范围内的加速普及和日益增长的重要性。

推动这一显着成长的主要因素是对提高建筑环境营运效率、预测性维护和永续性的迫切需求。建筑物业主和管理者正日益寻求优化资源利用、降低能耗和最大限度减少停机时间的方法，同时确保居住者的舒适和安全。数位孪生技术透过创建实体建筑的详细即时模型，并实现持续的监测和分析，为实现这些目标提供了一个先进的平台。

市场趋势

建筑数位孪生市场由西门子、欧特克、IBM 和微软等领先的科技和工程公司引领。这些公司透过提供包含软体解决方案、感测器和无人机等硬体组件以及各种服务的综合产品组合来展开激烈竞争。它们的战略重点是将数位孪生技术与其他新兴技术（尤其是人工智慧 (AI)）相集成，以提高数位模型的智慧和回应能力。

2025 年 11 月，在巴塞隆纳举行的智慧城市博览会上，一项重要进展诞生： "数位孪生应用商店" 正式上线。这个创新平台汇集了来自不断成长的供应商和机构网路的经过验证的产品，创造了一个集中式的数位孪生工具、服务和资料集市场。此外，NVIDIA 创始人兼首席执行官黄仁勋于 2025 年 10 月发布了“NVIDIA Omniverse DSX”，这是一个专为设计和运营千兆瓦级 AI 工厂而设计的全面开放蓝图。

核心成长驱动因子

推动建筑数位孪生市场发展的关键因素之一是迫切需要透过改造现有建筑来提高永续性和效率。日益增强的环保意识和监管压力正促使政府和企业优先考虑老旧基础设施的现代化改造，并确保其符合现代能源和性能标准。改造面临独特的挑战，因为许多老旧建筑最初的设计并未考虑能源效率或智慧技术整合。数位孪生技术能够对建筑系统进行详细的监控、分析和优化，从而提供强大的解决方案，而无需彻底的重建。

新的机会与趋势

生成式人工智慧 (AI) 与数位孪生技术的整合为建筑管理系统提供了巨大的机遇，使其功能远超基本的监控。这种融合使得创建能够预测未来、自我最佳化的建筑成为可能，这些建筑可以动态地适应不断变化的环境和需求。透过整合生成式人工智慧演算法，数位孪生可以模拟数千种运行场景，提供前所未有的洞察力和远见。这些先进的模型使建筑业主和管理者能够预测未来的需求和挑战，并做出积极主动的决策，从而提高效率、舒适度和永续性。

优化障碍

数位孪生技术相关的高昂初始投资和实施成本是可能阻碍整体市场成长的重大挑战。开发和部署数位孪生解决方案需要大量资金，因为它需要物联网感测器、资料储存基础设施和高效能运算能力等先进硬体。这种前期投资对许多组织来说可能是一个障碍，尤其是缺乏投资此类先进技术所需财力的中小企业 (SME)。将数位孪生技术整合到现有楼宇管理系统中的复杂性也增加了财务负担，通常需要专业知识和大量的客製化工作。

目录

第一章：研究架构

• 研究目标
• 产品概述
• 市场区隔

第二章：研究方法

• 质性研究
  • 一手和二手资料来源
• 量化研究
  • 一手和二手资料来源
• 依地区划分的原始调查受访者
• 研究假设
• 市场规模估算
• 资料三角验证

第三章：摘要整理：全球楼宇数位孪生市场

第四章：全球建筑数位孪生市场概论

• 产业价值链分析
• 建筑数位孪生市场主要趋势
• PESTLE 分析
• 波特五力分析
  • 供应商议价能力
  • 买方议价能力
  • 替代品威胁
  • 新进入者威胁
  • 竞争强度
• 市场动态与趋势
  • 成长因素
  • 阻碍因素与推动因素
  • 挑战
  • 主要趋势
• 新冠疫情对市场成长趋势的影响评估
• 市场成长与展望
  • 市场收入估计与预测（2019-2032）
• 竞争格局概览
  • 市场集中度
  • 公司市占率分析（价值，2023 年）
  • 竞争格局图

第五章 全球建筑数位孪生市场分析：依组件划分

• 主要发现
• 市场规模及预测，2019-2032 年
  • 软体
  • 服务

第六章 全球建筑数位孪生市场分析：依类型划分

• 主要发现
• 市场规模及预测，2019-2032 年
  • 描述性孪生
  • 资讯性孪生
  • 预测性孪生数位孪生
  • 综合型数位孪生
  • 自主型数位孪生

第七章 全球建筑数位孪生市场依应用领域分析

• 主要见解
• 市场规模及预测（2019-2032）
  • 自动化进度监控
  • 效能与规划模型
  • 资源管理与物流
  • 安全监控
  • 品质评估
  • 设备利用率最佳化
  • 劳动力监控和追踪

第八章 全球建筑数位孪生市场依产业垂直领域分析

• 主要发现
• 市场规模及预测（2019-2032）
  • 製造业
  • 航空航太与国防
  • 石油与天然气
  • 公用事业
  • 医疗保健与生命科学
  • 汽车
  • 建筑
  • IT与电信
  • 零售
  • 消费品与包装
  • 交通运输
  • 智慧城市
  • 其他

第九章 全球建筑数位孪生市场分析：依地区划分

• 主要见解
• 市场规模及预测（2019-2032）
  • 北美
  • 欧洲
  • 亚太地区
  • 南美
  • 中东和非洲

第十章：北美建筑数位孪生市场分析

第十一章：欧洲建筑数位孪生市场分析

第十二章：亚太地区建筑数位孪生市场分析

第十三章：南美洲建筑数位孪生市场分析

第十四章：中东与非洲建筑数位孪生市场分析

第15章 企业简介

• ABB
• Accenture PLC
• Ansys, Inc.
• Priori Technologies, Inc.
• Bentley Systems, Incorporated
• Cisco Systems, Inc.
• Dassault Systems, 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

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

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