전력망 관리용 AI 시장 규모, 점유율, 동향 및 성장 분석 보고서(2026-2034년)

The global AI in power grid management market size is expected to reach USD 39.37 Billion in 2034 from USD 8.95 Billion in 2025, growing at a CAGR of 17.89% during 2026-2034.This market is expanding as electricity networks become more complex due to renewable energy integration, distributed generation, electric vehicles, and growing electricity demand. Artificial intelligence is increasingly being used to analyze large volumes of grid data, improve forecasting, detect anomalies, and optimize network operations. Utilities are adopting AI-based tools to enhance reliability, manage demand, and respond more effectively to changing grid conditions. The expansion of smart meters, sensors, connected substations, and digital control systems is generating the data required for advanced AI applications across transmission and distribution networks.

Renewable energy integration is a major growth driver because solar and wind generation can fluctuate according to weather conditions. AI can help utilities forecast generation, predict demand, optimize energy flows, and coordinate distributed energy resources. Machine learning is also being applied to predictive maintenance, helping operators identify potential equipment failures before they cause outages. Increasing grid modernization investments and the need to improve resilience against extreme weather and infrastructure failures are supporting adoption. AI-enabled cybersecurity and anomaly detection are becoming increasingly important as power networks become more connected and digitally managed.

The future outlook is highly promising as utilities move toward intelligent, automated, and increasingly decentralized electricity systems. AI is expected to support real-time grid balancing, autonomous fault detection, demand response, energy storage optimization, and improved renewable integration. Digital twins and advanced simulation technologies may further improve planning and operational decision-making. Cybersecurity, data quality, interoperability, and regulatory requirements will remain important considerations. Utilities and technology providers that successfully combine AI with sensors, smart-grid infrastructure, cloud platforms, and advanced analytics are likely to gain significant opportunities as global power systems undergo continued digital transformation.

Our reports are carefully developed to deliver comprehensive and actionable insights across a wide range of industries and markets. Each report includes several essential components designed to provide a complete understanding of the market environment:

Market Overview: This section provides a clear introduction to the market, including key definitions, classifications, and an overview of the current industry landscape.

Market Dynamics: A detailed evaluation of the primary drivers, restraints, opportunities, and challenges shaping market growth. It covers factors such as technological developments, regulatory frameworks, and evolving industry trends.

Segmentation Analysis: A structured breakdown of the market into key segments based on product type, application, end-user, and geographic region. This section highlights the performance, growth potential, and contribution of each segment.

Competitive Landscape: An in-depth assessment of leading market participants, including their market positioning, product portfolios, strategic initiatives, and financial performance. It provides valuable insights into competitive dynamics and the strategies adopted by key players.

Market Forecast: Data-driven projections of market size and growth patterns over a defined forecast period. This section incorporates historical trends, current market conditions, and quantitative analysis to illustrate expected future developments.

Regional Analysis: A comprehensive review of market performance across major geographic regions, identifying high-growth areas and regional trends to better understand localized market opportunities.

Emerging Trends and Opportunities: Identification of significant market trends, technological advancements, and new investment opportunities. This section highlights potential growth areas and future industry developments.

Customization Options: We offer flexible customization services to tailor reports according to specific client requirements. This may include additional segmentation, country-level analysis, competitor profiling, customized data points, or focused insights on particular market segments to better support strategic decision-making.

MARKET SEGMENTATION

By Component

• Software & Platforms (Grid Analytics & Situational Awareness Platforms, AI-Integrated SCADA & Energy Management Systems, Demand Forecasting & Load Optimization Software, Others)
• Services (Consulting & Advisory Services, System Integration & Implementation Services, Others)

By AI Technology

• Machine Learning & Predictive Analytics
• Deep Learning & Neural Networks
• Computer Vision & Image Processing
• Others

By Application

• Demand Forecasting & Load Management
• Fault Detection & Predictive Maintenance
• Grid Optimization & Energy Balancing
• Renewable Energy Integration
• Others

By End User

• Investor-Owned Utilities (IOUs)
• Public Power Utilities & Cooperatives
• Industrial & Commercial Microgrids
• Others

COMPANIES PROFILED

• ABB, AspenTech, AVEVA, Baker Hughes, BluWave-ai, Buzz Solutions, C3.ai, Cognite, Enel Group, Envision Digital, GE Vernova, GridBeyond, Hitachi Energy, Honeywell, IBM, Oracle Utilities, Schneider Electric, Siemens, Toshiba Energy Systems, Uplight, Utilidata

TABLE OF CONTENTS

Chapter 1. PREFACE

• 1.1. Market Segmentation & Scope
• 1.2. Market Definition
• 1.3. Information Procurement
  • 1.3.1 Information Analysis
  • 1.3.2 Market Formulation & Data Visualization
  • 1.3.3 Data Validation & Publishing
• 1.4. Research Scope and Assumptions
  • 1.4.1 List of Data Sources

Chapter 2. EXECUTIVE SUMMARY

• 2.1. Market Snapshot
• 2.2. Segmental Outlook
• 2.3. Competitive Outlook

Chapter 3. MARKET VARIABLES, TRENDS, FRAMEWORK

• 3.1. Market Lineage Outlook
• 3.2. Penetration & Growth Prospect Mapping
• 3.3. Value Chain Analysis
• 3.4. Regulatory Framework
  • 3.4.1 Standards & Compliance
  • 3.4.2 Regulatory Impact Analysis
• 3.5. Market Dynamics
  • 3.5.1 Market Drivers
  • 3.5.2 Market Restraints
  • 3.5.3 Market Opportunities
  • 3.5.4 Market Challenges
• 3.6. Porter's Five Forces Analysis
• 3.7. PESTLE Analysis

Chapter 4. GLOBAL AI IN POWER GRID MANAGEMENT MARKET: BY COMPONENT 2022-2034 (USD MN)

• 4.1. Market Analysis, Insights and Forecast Component
• 4.2. Software & Platforms (Grid Analytics & Situational Awareness Platforms, AI-Integrated SCADA & Energy Management Systems, Demand Forecasting & Load Optimization Software, Others) Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 4.3. Services (Consulting & Advisory Services, System Integration & Implementation Services, Others) Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 5. GLOBAL AI IN POWER GRID MANAGEMENT MARKET: BY AI TECHNOLOGY 2022-2034 (USD MN)

• 5.1. Market Analysis, Insights and Forecast Ai Technology
• 5.2. Machine Learning & Predictive Analytics Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 5.3. Deep Learning & Neural Networks Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 5.4. Computer Vision & Image Processing Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 5.5. Others Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 6. GLOBAL AI IN POWER GRID MANAGEMENT MARKET: BY APPLICATION 2022-2034 (USD MN)

• 6.1. Market Analysis, Insights and Forecast Application
• 6.2. Demand Forecasting & Load Management Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 6.3. Fault Detection & Predictive Maintenance Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 6.4. Grid Optimization & Energy Balancing Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 6.5. Renewable Energy Integration Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 6.6. Others Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 7. GLOBAL AI IN POWER GRID MANAGEMENT MARKET: BY END USER 2022-2034 (USD MN)

• 7.1. Market Analysis, Insights and Forecast End User
• 7.2. Investor-Owned Utilities (IOUs) Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 7.3. Public Power Utilities & Cooperatives Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 7.4. Industrial & Commercial Microgrids Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 7.5. Others Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 8. GLOBAL AI IN POWER GRID MANAGEMENT MARKET: BY REGION 2022-2034 (USD MN)

• 8.1. Regional Outlook
• 8.2. North America Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 8.2.1 By Component
  • 8.2.2 By Ai Technology
  • 8.2.3 By Application
  • 8.2.4 By End User
  • 8.2.5 United States
  • 8.2.6 Canada
  • 8.2.7 Mexico
• 8.3. Europe Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 8.3.1 By Component
  • 8.3.2 By Ai Technology
  • 8.3.3 By Application
  • 8.3.4 By End User
  • 8.3.5 United Kingdom
  • 8.3.6 France
  • 8.3.7 Germany
  • 8.3.8 Italy
  • 8.3.9 Russia
  • 8.3.10 Rest Of Europe
• 8.4. Asia-Pacific Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 8.4.1 By Component
  • 8.4.2 By Ai Technology
  • 8.4.3 By Application
  • 8.4.4 By End User
  • 8.4.5 India
  • 8.4.6 Japan
  • 8.4.7 South Korea
  • 8.4.8 Australia
  • 8.4.9 South East Asia
  • 8.4.10 Rest Of Asia Pacific
• 8.5. Latin America Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 8.5.1 By Component
  • 8.5.2 By Ai Technology
  • 8.5.3 By Application
  • 8.5.4 By End User
  • 8.5.5 Brazil
  • 8.5.6 Argentina
  • 8.5.7 Peru
  • 8.5.8 Chile
  • 8.5.9 Rest of Latin America
• 8.6. Middle East & Africa Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 8.6.1 By Component
  • 8.6.2 By Ai Technology
  • 8.6.3 By Application
  • 8.6.4 By End User
  • 8.6.5 Saudi Arabia
  • 8.6.6 UAE
  • 8.6.7 Israel
  • 8.6.8 South Africa
  • 8.6.9 Rest of the Middle East And Africa

Chapter 9. COMPETITIVE LANDSCAPE

• 9.1. Recent Developments
• 9.2. Company Categorization
• 9.3. Supply Chain & Channel Partners (based on availability)
• 9.4. Market Share & Positioning Analysis (based on availability)
• 9.5. Vendor Landscape (based on availability)
• 9.6. Strategy Mapping

Chapter 10. COMPANY PROFILES OF GLOBAL AI IN POWER GRID MANAGEMENT INDUSTRY

• 10.1. Top Companies Market Share Analysis
• 10.2. Company Profiles
  • 10.2.1 ABB
  • 10.2.2 AspenTech
  • 10.2.3 AVEVA
  • 10.2.4 Baker Hughes
  • 10.2.5 BluWave-ai
  • 10.2.6 Buzz Solutions
  • 10.2.7 C3.ai
  • 10.2.8 Cognite
  • 10.2.9 Enel Group
  • 10.2.10 Envision Digital
  • 10.2.11 GE Vernova
  • 10.2.12 GridBeyond
  • 10.2.13 Hitachi Energy
  • 10.2.14 Honeywell
  • 10.2.15 IBM
  • 10.2.16 Oracle Utilities
  • 10.2.17 Schneider Electric
  • 10.2.18 Siemens
  • 10.2.19 Toshiba Energy Systems
  • 10.2.20 Uplight
  • 10.2.21 Utilidata