AI in Smart Buildings and Infrastructure Market Report 2025

The AI in smart buildings and infrastructure market size has grown exponentially in recent years. It will grow from $29.52 billion in 2024 to $35.92 billion in 2025 at a compound annual growth rate (CAGR) of 21.7%. The growth during the historic period can be attributed to the increasing need for better building utilization, higher demand for public safety and security, a surge in the adoption of smart building solutions due to the COVID-19 pandemic, a growing focus on improving indoor air quality (IAQ) for health and well-being, and the rising use of IoT and automation in building management.

The AI in smart buildings and infrastructure market size is expected to see exponential growth in the next few years. It will grow to $78.15 billion in 2029 at a compound annual growth rate (CAGR) of 21.4%. The growth during the forecast period can be attributed to the demand for enhanced asset reliability, performance, and space utilization, the expansion of AI and IoT applications in smart buildings, the increasing need for smart infrastructure in both commercial and residential buildings, government initiatives, digital transformation trends in emerging markets, and the growing demand for energy-efficient buildings. Key trends in the forecast period include technological advancements, the integration of machine learning, natural language processing, computer vision, and AI-driven predictive maintenance.

The increasing demand for energy-efficient and sustainable building solutions is expected to drive the growth of AI in smart buildings and infrastructure. Energy-efficient and sustainable building solutions aim to design and implement systems that reduce energy consumption, minimize environmental impact, and enhance long-term sustainability in buildings. This growing demand is largely due to heightened environmental concerns and the effects of climate change. Such solutions help decrease carbon footprints, lower energy costs, and ensure compliance with stricter government regulations on sustainability. AI contributes to optimizing energy consumption in smart buildings by automating climate control, lighting, and predictive maintenance, leading to improved efficiency and sustainability. For example, in March 2024, the Department for Energy Security and Net Zero in the UK reported that 318,600 energy efficiency measures were installed in 2023 across properties in Great Britain through government support programs, a 49% increase from 2022. As a result, the rising need for energy-efficient and sustainable building solutions is fueling the growth of AI in the smart buildings and infrastructure market.

Companies in the AI in smart buildings and infrastructure market are focusing on advancements such as AI-driven analytics and control systems to improve energy efficiency, operational effectiveness, and sustainability. AI-driven analytics uses artificial intelligence to analyze data, identify patterns, and provide valuable insights that optimize operations, improve decision-making, and enhance building performance. For instance, in June 2022, Siemens AG launched Building X, an AI-powered platform designed to optimize energy usage, automate building operations, and enhance occupant experiences in net-zero buildings. This platform integrates various building systems into a central hub, using AI-driven analytics to boost efficiency and sustainability. Its open architecture allows third-party integration, creating a more expansive ecosystem of smart building solutions within Siemens Xcelerator, aimed at driving digital transformation in buildings.

In December 2024, Trane Technologies Plc, an industrial machinery manufacturing company based in Ireland, acquired BrainBox AI, a Canadian AI technology company specializing in smart building solutions and HVAC energy efficiency. This acquisition enhances Trane Technologies' advanced building management and digital capabilities by leveraging BrainBox AI's AI technology to reduce energy consumption and greenhouse gas emissions in commercial buildings.

Major players in the AI in smart buildings and infrastructure market are Google LLC, Microsoft Corporation, Amazon Web Services Inc., Robert Bosch GmbH, Hitachi Ltd., Siemens AG, Intel Corporation, Panasonic Corporation, International Business Machines Corporation (IBM), Cisco Systems Inc., Oracle Corporation, Schneider Electric SE, Honeywell International Inc., ABB Ltd, NEC Corporation, Johnson Controls International plc, Samsung SDS, Autodesk Inc., Terminus Group, GridPoint Inc., Verdigris Technologies, BuildingIQ Inc., and Built Robotics.

North America was the largest region in the AI in smart buildings and infrastructure market in 2024. The regions covered in AI in smart buildings and infrastructure report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa. The countries covered in the AI in smart buildings and infrastructure market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The artificial intelligence (AI) in smart buildings and infrastructure refers to the integration of AI technologies into the design, operation, and management of buildings and urban infrastructure. This enables automation, efficiency, sustainability, and enhanced user experience through data-driven decision-making.

The primary types of AI in smart buildings and infrastructure are software, hardware, and services. Software for AI in smart buildings and infrastructure involves systems that enhance automation, efficiency, security, and sustainability. These software solutions leverage artificial intelligence (AI) to optimize operations, improve user experiences, and reduce costs. Various technologies involved, such as machine learning, natural language processing, computer vision, robotic process automation, and others, cater to applications including building automation, energy management, security and surveillance, predictive maintenance, smart parking, and more. These serve end-user industries such as commercial buildings, residential buildings, industrial buildings, government buildings, healthcare facilities, educational institutions, retail spaces, and others.

The AI in smart buildings and infrastructure market research report is one of a series of new reports that provides AI in smart buildings and infrastructure market statistics, including AI in smart buildings and infrastructure industry global market size, regional shares, competitors with a AI in smart buildings and infrastructure market share, detailed AI in smart buildings and infrastructure market segments, market trends and opportunities, and any further data you may need to thrive in the AI in smart buildings and infrastructure industry. This AI in smart buildings and infrastructure market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The AI in smart buildings and infrastructure market consists of revenues earned by entities providing services such as intelligent automation, predictive maintenance, and energy management. The market value includes the value of related goods sold by the service provider or included within the service offering. The AI in smart buildings and infrastructure market also includes sales of motion sensors, temperature and humidity sensors, smart meters, and cameras. Values in this market are ‘factory gate’ values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

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