The edge AI in smart grids market is projected to surge from $15.5bn in 2025 to $19.5bin in 2026, a rise of 25.7%, according to Research & Markets.

This growth is driven by increasing grid failures, heightened energy efficiency demands, rising renewable energy integration, smart meter proliferation and industrial IoT adoption within utilities. In the foreseeable future, the market is anticipated to reach $48.9bn by 2030, with a CAGR of 25.9%, powered by edge AI deployment for predictive analytics, intelligent relay deployment and AI-driven grid management.

Increased energy demand, influenced by population growth, underpins this market expansion. By processing data locally and in real time, edge AI boosts energy management, enabling rapid decision-making, cutting energy loss and optimising renewable energy integration. Notably, the International Energy Agency reported a 1.4% increase in net electricity generation reaching 922.6TWh in June 2025 within OECD countries, exemplifying this trend.

Leading firms in the edge AI smart grids sector are pioneering AI-enabled IoT edge compute cellular gateways for real-time monitoring, automated control and energy distribution optimisation. For instance, Lantronix introduced its SmartLV gateway in 2024, facilitating low-voltage substation management in smart grids with capabilities including real-time automation and multi-protocol connectivity. In 2025, Bidgely acquired Grid4C, enhancing its UtilityAI platform with enhanced grid-side intelligence, customer engagement and load forecasting.

Prominent companies in the industry include Siemens, Hitachi Energy, Nvidia, Intel, Schneider Electric and Qualcomm.

The imposition of tariffs has impacted the market by escalating costs of imported edge computing devices and sensors, affecting hardware components and software-integrated options especially in North America and Europe. This has propelled a shift towards local suppliers, driving innovation in cost-effective edge AI.

Edge AI in smart grids involves integrated hardware, software and services. Hardware comprises sensors and communication modules for real-time data collection and AI processing. Products are deployed via on-premises and cloud models across applications such as grid management and distributed energy resource management.

Primary users include electric utilities, industrial facilities and smart city projects. The market encapsulates revenues from providing services such as edge AI model development and energy load forecasting. Market value includes the factory gate value of goods sold directly or via distribution channels.

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