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Leading Companies Advancing Innovation and Growth in the Artificial Intelligence (AI)-Powered Smart Grid Market
Artificial Intelligence (AI)-Powered Smart Grid Market
Projected Expansion of the Artificial Intelligence-Powered Smart Grid Market
The AI-powered smart grid market is projected to experience significant growth, reaching a value of $12.79 billion by 2030. This expansion corresponds to a compound annual growth rate (CAGR) of 14.1%, reflecting strong momentum in the sector. The market's upward trajectory can be linked to several factors, such as the integration challenges posed by renewable energy sources, a surge in electric vehicle charging demands, growing investments in AI-based grid automation, increasing cybersecurity needs, and the widening deployment of decentralized energy resources. Key trends expected to shape the market include AI-enhanced load forecasting, self-healing grid systems, predictive maintenance analytics, real-time grid monitoring tools, and sophisticated demand response management.
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Key Drivers Sustaining Growth in the Artificial Intelligence-Powered Smart Grid Market
One of the major drivers for this market is the rising complexity of integrating renewable energy into existing grids. As solar, wind, and other renewable sources become more prevalent, managing their variable output requires smarter, AI-assisted solutions to maintain grid stability and efficiency.
Additionally, the rapid adoption of electric vehicles is creating new challenges related to charging loads, which AI-powered systems help to optimize by predicting demand and balancing supply accordingly.
Leading Players Shaping the Artificial Intelligence-Powered Smart Grid Industry
The AI-driven smart grid market features several prominent companies that are leading innovation and deployment efforts. These major players include International Business Machines Corporation, Cisco Systems Inc., Oracle Corporation, Schneider Electric SE, Honeywell International Inc., Siemens Energy AG, GE Vernova Inc., ABB Ltd., Eaton Corporation plc, Octopus Energy Group Ltd., Itron Inc., Bentley Systems Incorporated, C3.ai Inc., Fluentgrid Limited, Innowatts Inc., Utilidata Inc., Percepto Robotics Ltd., Net2Grid B.V., Radix IoT LLC, and Esyasoft Holding Limited.
In a notable move in March 2025, Bidgely Inc., a US-based energy intelligence firm, acquired Grid4C Ltd., strengthening its position in AI-powered energy analytics. This acquisition enhances Bidgely's platform capabilities for grid management, distributed energy resource optimization, and delivering predictive insights that boost consumer engagement and operational effectiveness.
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Emerging Trends Highlighting the Future of AI in Smart Grids
A growing focus among market leaders is the integration of AI tools into grid management systems to improve operational efficiency and decision-making. One such innovation is the Embedded Grid AI Assistant, which supports grid operators with real-time troubleshooting, predictive analytics, and optimized operational decisions to enhance reliability.
For example, in November 2025, Schneider Electric SE introduced the One Digital Grid Platform. This AI-powered software solution helps utilities modernize their operations by combining planning, asset management, and real-time outage monitoring into a unified platform. By offering AI-driven diagnostics and cloud/on-premise flexibility, it enables faster outage restoration, lowers operational costs, and optimizes asset performance without requiring a complete overhaul of existing infrastructure. The platform's ability to integrate distributed energy resources and predictive analytics contributes to building a more resilient and sustainable energy grid.
Segmentation Overview of the Global AI-Powered Smart Grid Market
This market is segmented into several categories to cover various components, deployment models, solutions, applications, and end-use sectors.
1) Component segments include Hardware, Software, and Services.
2) Deployment Models are divided into On-Premise AI-Powered Grid Solutions, Cloud-Based AI-Powered Grid Solutions, and Hybrid Deployment Solutions.
3) Solution Types cover AI-Based Grid Analytics, Predictive Maintenance and Fault Detection, Demand Forecasting and Optimization, Real-Time Grid Monitoring and Control, Cloud Computing and Data Management, Cybersecurity and Risk Management, and Integration, Consulting, and Managed Services.
4) Application areas focus on Energy Distribution Optimization, Demand Response Management, Predictive Maintenance, and other uses.
5) End-Use categories include Utilities, Industrial, and Commercial & Residential sectors.
Further breakdowns include hardware subsegments like Smart Sensors, Edge Computing Devices, Communication Modules, Control and Protection Equipment, and Data Storage Devices. Software subcategories feature Grid Analytics Platforms, AI and Machine Learning Platforms, Energy Management Systems, Grid Monitoring and Visualization Software, and Optimization and Decision Support Software. Services are categorized into Integration, Consulting, and Managed Services.
This comprehensive segmentation reflects the diverse nature of the AI-powered smart grid market and the broad range of technologies and services involved in transforming energy infrastructures worldwide.
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