The growth of IoT devices being deployed in commercial buildings remains strong in 2025, driven by declining hardware costs, enhanced wireless connectivity, increased demand for energy efficiency and operational automation, as well as the rising capabilities of edge computing.
Data from our latest study indicates that the installed base of IoT devices in commercial buildings grew from 1.55 billion in 2022 to just under 2 billion by the end of 2024. This reflects continued enterprise adoption, with many organizations expanding IoT use beyond initial pilot deployments and into scaled implementations.
Looking ahead, our forecast projects that the number of IoT devices deployed in commercial buildings will grow at a CAGR of just over 13%, reaching an installed base of approximately 4.12 billion by 2030.
We expect key trends, such as the increasing integration of digital twin platforms and predictive maintenance, as well as cloud and edge based AI analytics, to further reinforce demand for smart buildings.
IoT Devices on the Edge
The rise of cloud computing served an important need in the smart buildings sector, allowing a much broader number of commercial buildings to access advanced analytics and AI without the capital outlay. However, the evolution of building technology is now bringing that intelligence back to the edge through a new generation of devices and gateways.
“At the edge processing layer, IoT gateways serve as the critical intermediaries that aggregate, process, and transmit data across smart commercial buildings. These devices bridge communication gaps between various IoT sensors, control systems, and external networks, facilitating efficient data flow and interoperability,” explains our latest report on the Building IoT in 2025.
“As buildings increasingly deploy IoT devices, gateways play an essential role in handling protocol translation, data security enforcement, and bandwidth optimization. Their ability to locally process data enhances real-time responsiveness, reducing latency and cloud dependency.”
IoT gateways and the edge processing layer enable data aggregation and protocol translation, converting data from disparate formats into standardized structures. This reduces cost and disruption by allowing new IoT technologies to coexist with existing building management systems and supports IT and OT integration.
Edge processing capabilities empower gateways to analyze and filter raw data locally, instead of sending masses of data to the cloud, reducing bandwidth consumption and improving system performance. Gateways also play a crucial role in the lifecycle management of IoT devices, supporting remote firmware updates, patches, and performance enhancements without the need for physical intervention.
As the first line of defense for IoT networks, gateways also enforce critical security measures. By integrating encryption, authentication, and firewall capabilities, they protect data integrity and prevent unauthorized access. Many IoT gateways may incorporate dual network interfaces, providing failover & redundancy mechanisms that ensure mission-critical applications remain operational during network downtimes.
The increasing computational power of gateways is driving the adoption of AI-based edge processing. Modern gateways are now capable of running machine learning models and computer vision analytics, enabling real-time decision-making without cloud dependencies. This is particularly valuable for anomaly detection in energy consumption and security, as well as predictive maintenance of critical equipment.
“IoT gateways are evolving into intelligent edge nodes, offering containerized applications, microservices hosting, and dynamic software updates. This allows facility managers to deploy new analytics models remotely, improving adaptability and future-proofing investments,” our new report reveals. “Private 5G networks and enhanced IoT connectivity are also driving integration between edge and cloud, ensuring optimal performance for data-intensive applications.”
Edge AI is becoming a key feature of smart buildings, enabling real-time data processing and decision-making within IoT devices themselves, which facilitates a new level of real-time responsiveness. One recent case study of a 32-story office building where AI-enabled HVAC optimization led to a 15.8% reduction in energy consumption over 11 months, saving costs and reducing carbon emissions.
The continuous local real-time monitoring offered by Edge AI drives a sea change of performance improvements in a wide range of smart building applications, including predictive maintenance, occupancy optimization, security, and access control, air quality monitoring, and many more.
As smart buildings become increasingly connected and autonomous, Edge AI is set to play a foundational role. Its capability to reduce latency, minimize cloud reliance, and optimize energy consumption makes it a critical enabler for next-generation smart commercial buildings.
