Through market attractiveness analysis, total addressable market evaluation, company benchmarking matrices, interactive Excel dashboards, expanded supply chain intelligence, emerging startup coverage, and detailed product insights, The Business Research Company’s 2026 market reports provide more actionable and strategically valuable research.
Edge Artificial Intelligence (AI) In Smart Grids Market Expected To Reach $48.91 Billion By 2030 At 25.9% CAGR
The edge artificial intelligence (AI) in smart grids market has experienced substantial expansion over recent years. This market is projected to grow from $15.49 billion in 2025 to $19.46 billion in 2026, achieving a compound annual growth rate (CAGR) of 25.7%. The increase observed in the historic period can be attributed to factors such as a rise in grid failures and outages, increasing demand for energy efficiency, enhanced integration of renewable energy, the expansion of smart meter deployments, and the adoption of industrial IoT in utilities.
The edge artificial intelligence (AI) in smart grids market size is set for significant expansion in the coming years. It is projected to increase to $48.91 billion by 2030, showing a compound annual growth rate (CAGR) of 25.9%. This growth throughout the forecast period stems from the implementation of edge AI for predictive analytics, the deployment of intelligent relays and processing units, the adoption of AI-driven grid management solutions, heightened investment in cybersecurity for smart grids, and the expansion of distributed energy resource management. Dominant trends during this period are expected to include edge AI-driven grid optimization, real-time energy load forecasting, predictive maintenance and asset monitoring, the integration of smart sensors and edge devices, and advancements in energy management and operational efficiency.
Download A Free Sample Report For Comprehensive Market Insights:
#Edge Artificial Intelligence (AI) In Smart Grids Market Growth Factors: Which Forces Are Supporting Market Expansion?
Increasing energy demand is projected to drive the future expansion of edge artificial intelligence (AI) within the smart grids market. This demand represents the overall energy volume required by consumers, industries, and services for operations, powering devices, and fulfilling daily needs over a specified period. The escalation in energy demand is attributed to population growth, as a larger populace boosts the necessity for electricity, transportation, heating, and other energy-intensive services. Edge artificial intelligence in smart grids improves energy management through real-time local data processing, facilitating quicker decision-making, minimizing energy losses, and optimizing the incorporation of renewable sources for a more efficient and reliable power delivery. For example, in September 2025, the International Energy Agency, a US-based intergovernmental organization, stated that total net electricity generation in the OECD reached 922.6 TWh in June, which was a 1.4% increase compared to June 2024. Therefore, the growing energy demand is propelling the advancement of edge artificial intelligence (AI) in the smart grids market.
Edge Artificial Intelligence (AI) In Smart Grids Market Segments: Where Are The Largest Growth Opportunities?
The edge artificial intelligence (AI) in smart grids market covered in this report is segmented –
1) By Component: Hardware, Software, Services
2) By Deployment Model: On-Premises, Cloud-Based
3) By Solution Type: Edge Intelligence Platforms, Real-Time Grid Analytics Solutions, Predictive Maintenance Solutions, Artificial Intelligence-Driven Control And Automation Services, Cybersecurity And Risk Management Services
4) By Application: Grid Management, Asset Management, Advanced Metering Infrastructure (AMI), Distributed Energy Resource Management, Other Applications
5) By End-User Industry: Electric Utilities, Industrial Facilities, Commercial Energy Operators, Smart City And Infrastructure Projects
Subsegments:
1) By Hardware: Edge Computing Devices, Sensors And Actuators, Networking Equipment, Processing Units, Control Modules
2) By Software: Edge Analytics Platforms, Machine Learning Software, Predictive Maintenance Software, Grid Optimization Software, Cybersecurity Software
3) By Services: Integration And Consulting Services, Managed Services, Training And Support Services, Maintenance Services, Cloud And Edge Computing Services
Edge Artificial Intelligence (AI) In Smart Grids Market Industry Trends: What Changes Are Reshaping Demand?
Leading companies in the edge artificial intelligence (AI) in smart grids market are concentrating on developing innovative solutions, such as AI-powered IoT edge compute cellular gateways, to facilitate real-time grid monitoring, automated decision-making, and optimized energy distribution. An AI-enabled IoT edge compute cellular gateway is a device designed to process data locally at the network’s edge using AI, connect various IoT devices, and transmit crucial insights over cellular networks for continuous monitoring and control. For instance, in October 2024, Lantronix Inc., a US-based technology company, introduced the SmartLV Gateway. This AI-enabled IoT Edge Compute Cellular Gateway is specifically engineered for low-voltage substations in smart grid and diverse industrial applications. The SmartLV Gateway offers immediate control, automation, and energy management capabilities. It incorporates edge AI functionalities, multi-protocol integration, and advanced cybersecurity measures. Equipped with both LTE and 5G connectivity, the SmartLV Gateway enables reliable remote operations while diminishing dependence on centralized cloud systems by processing data directly at the edge. Its seamless integration with existing infrastructure allows utilities and industrial operators to enhance energy distribution, improve operational efficiency, and strengthen overall grid resiliency.
Edge Artificial Intelligence (AI) In Smart Grids Market Major Participants And Competitive Dynamics
Major companies operating in the edge artificial intelligence (AI) in smart grids market are Siemens AG, Hitachi Energy Ltd., NVIDIA Corporation, Intel Corporation, Schneider Electric SE, Qualcomm Technologies Inc., GE Vernova, ABB Ltd., Hewlett Packard Enterprise Company, Beckwith Electric Co Inc., Itron Inc., Advantech Co. Ltd., Schweitzer Engineering Laboratories Inc., C3.ai Inc., SparkCognition Inc., Lantronix Inc., Uplight Inc., Utilidata Inc, Smarter Grid Solutions Ltd., ClearBlade Inc.
Access The Complete Edge Artificial Intelligence (AI) In Smart Grids Market Report:
Edge Artificial Intelligence (AI) In Smart Grids Market Regional Outlook: Where Are The Largest Opportunities Located?
North America was the largest region in the edge artificial intelligence (AI) in smart grids market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the edge artificial intelligence (AI) in smart grids market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
Get in touch with us:
The Business Research Company: https://www.thebusinessresearchcompany.com/
Americas: +1 310-496-7795
Asia: +44 7882 955267 & +91 8897263534
Europe: +44 7882 955267
Email us at: marketing@tbrc.info
Follow us on:
LinkedIn: https://in.linkedin.com/company/the-business-research-company
YouTube: https://www.youtube.com/channel/UC24_fI0rV8cR5DxlCpgmyFQ
Global Market Model: https://www.thebusinessresearchcompany.com/global-market-model
Wasay has over a decade of experience in market research, data modelling, and analytics, with prior experience at GlobalData and Decision Tree Consulting Services. At The Business Research Company , he leads research operations across syndicated studies, customized consulting engagements, and the Global Market Model platform. His professional experience includes supporting organizations such as Boston Consulting Group, KPMG, and Ernst & Young. Wasay holds a degree in Electronics and Communications Engineering, postgraduate management qualifications from International Management Institute Belgium and Indian School of Business and Entrepreneurship, and completed the Integrated Program in Business Analytics from Indian Institute of Management Indore.