Global Artificial Intelligence in Energy Management Market 2025-2035

Global Artificial Intelligence in Energy Management Market Size, Share & Trends Analysis Report by Component Type (Solutions and Services), by Deployment Type (On-premise and Cloud), by Application (Energy Transmission, Energy Generation, Energy Distribution and Others), and by End Users (Robotics, Renewables Management, Demand Forecasting, Safety and Security and Others), Forecast Period (2025-2035)

Industry Outlook

Artificial intelligence in the energy management market is anticipated to grow at a CAGR of 15.5% during the forecast period (2025-2035). Artificial intelligence increases efficiency, optimizes resource allocation, and makes sustainable energy solutions possible. AI is revolutionizing the energy business. AI integration in the energy sector enables businesses to improve decision-making, forecast demand variations, and analyze massive information. Predictive analytics minimize waste and operational expenses by optimizing supply and demand. The real-time monitoring and automation made possible by AI-driven smart grid technology, energy transmission efficiency, and dependability are increased. In a region where even, minor inefficiencies can have a huge economic and environmental impact, these improvements are important.

Segmental Outlook

The global artificial intelligence in the energy management market is segmented by component type, deployment type, application, and end-users. Based on the component type, the market is sub-segmented into solutions and services. Based on the deployment type, the market is sub-segmented into on-premise and cloud. Based on the application, the market is sub-segmented into energy transmission, energy generation, energy distribution, and others (utilities). Further, based on end users, the market is sub-segmented into robotics, renewables management, demand forecasting, safety and security, and others (infrastructure). Among the applications, the energy generation sub-segment is anticipated to hold a considerable share of the market owing to the rise in the development of AI for the real-time monitoring of power grids, more accurate predictions of power fluctuations, and the development of new strategies to generate geothermal energy sources.

Renewables Management is Predicted to Grow Significantly in Global Artificial Intelligence in the Energy Management Market

Renewable energy management holds a significant market share in the global artificial intelligence market. The production and consumption of energy are being resolved by AI. The automation operations for solar panels, wind turbines, and others are being improved by artificial intelligence. By using historical data and weather trends to forecast energy generation, these technologies use powerful predictive analytics to improve supply and demand alignment.

As the adoption of renewable energy sources increases, robotics power rentals in substations and switchgear types are evolving as it is being used more frequently. The market for robotics AI in the energy sector is expanding owing to the trend toward modular and compact electrical applications, that allow for the incorporation of sophisticated features and functionalities into applications with limited space.

Regional Outlook

The global artificial intelligence in energy management market is further segmented based on geography including North America (the US, and Canada), Europe (UK, Italy, Spain, Germany, France, and the Rest of Europe), Asia-Pacific (India, China, Japan, South Korea, Australia & New Zealand, ASEAN Countries and Rest of Asia), and the Rest of the World (the Middle East & Africa, and Latin America. Among these, North America is anticipated to hold a prominent share of the market across the globe, owing to increased applications of artificial intelligence in the energy sector, along with real-time maintenance and identification of ideal maintenance schedules.

The European Region is Expected to Grow at a Significant CAGR in the Global Artificial Intelligence in Energy Management Market

Europe's energy market's use of AI is significantly impacted by strict regulations meant to cut carbon emissions and a strong commitment to sustainability. AI technologies are being aggressively adopted by European nations to improve energy efficiency and make it easier for their grids to include renewable energy sources. Clean energy-related government programs and policies are powerful inducers for investment in AI-powered solutions that help utilities increase grid flexibility, optimize operations, and better control demand. In the UK, the market is derived from the urgent need for sustainability and the transition to renewable energy sources. An increasing number of AI technologies are being used to optimize energy generation, improve demand forecasting, and improve grid management as the UK works to cut carbon emissions and reach net-zero targets.

Market Players Outlook

The major companies serving artificial intelligence in the energy management market include Schneider Electric SE, GE Vernova, Siemens AG, ABB Ltd., and Honeywell International Inc., among others. The market players are considerably contributing to the market growth by the adoption of various strategies including mergers and acquisitions, partnerships, collaborations, funding, and new product launches, to stay competitive in the market. For instance, in April 2023, to improve energy access forecasting and model energy equity, IBM and the United Nations Development Programme (UNDP) announced the creation of new tools. As a component of the IBM Sustainability Accelerator program, this partnership makes use of innovative technologies such as IBM Watson, IBM Cloud, and IBM Environmental Intelligence. These resources are intended to aid in the pursuit of fair energy distribution and the resolution of the obstacles that vulnerable groups encounter in obtaining energy.

Recent Developments

  • In December 2024, AI-powered energy grid management systems had advanced significantly for Energy Infrastructure Predictive Maintenance. These systems use machine learning technologies to maximize energy distribution across grids in real time and forecast energy demand. In regions with variable renewable power, including wind and solar, AI integration helps with demand forecasting, energy outage prevention, and the integration of renewable energy sources.
  • In September 2024, the grid's integration of renewable energy sources like wind and solar will be aided by artificial intelligence. Forecasting weather patterns, measuring solar radiation, and optimizing wind farm efficiency are all being done with artificial intelligence (AI). To reduce dependency on fossil fuels and improve the reliability and efficiency of sustainable energy sources, several projects were launched to integrate AI with renewable energy infrastructure.
The Report Covers
  • Market value data analysis of 2025 and forecast to 2035.
  • Annualized market revenues ($ million) for each market segment.
  • Country-wise analysis of major geographical regions.
  • Key companies operating in the global AI in energy management market. Based on the availability of data, information related to new product launches, and relevant news is also available in the report.
  • Analysis of business strategies by identifying the key market segments positioned for strong growth in the future.
  • Analysis of market-entry and market expansion strategies.
  • Competitive strategies by identifying ‘who-stands-where’ in the market.


1. Report Summary
Current Industry Analysis and Growth Potential Outlook
Global AI in Energy Management Market Sales Analysis – Component Type | Deployment Mode| Application| End-User ($ Million)
1.1. Research Methodology
Primary Research Approach
Secondary Research Approach
2. Market Overview and Insights
2.1. Scope of the Study
2.2. Analyst Insight & Current Market Trends
2.2.1. Key Global AI in Energy Management Market Trends
2.2.2. Market Recommendations
2.2.3. Conclusion
3. Market Determinants
3.1. Market Drivers
3.1.1. Drivers For Global AI in Energy Management Market: Impact Analysis
3.2. Market Pain Points and Challenges
3.2.1. Restraints For Global AI in Energy Management Market: Impact Analysis
3.3. Market Opportunities
4. Competitive Landscape
4.1. Competitive Dashboard – Global AI in Energy Management Market Revenue by Manufacturers
4.2. Key Company Analysis
4.2.1. Overview
4.2.2. Product Portfolio
4.2.3. Financial Analysis (Subject to Data Availability)
4.2.4. SWOT Analysis
4.2.5. Business Strategy
4.3. Top Winning Strategies by Market Players
4.3.1. Merger and Acquisition
4.3.2. Product Launch
4.3.3. Partnership And Collaboration
5. Global AI in Energy Management Market by Component ($ Million)
5.1. Solutions
5.2. Services
6. Global AI in Energy Management Market by Deployment Type ($ Million)
6.1. On-premise
6.2. Cloud
7. Global AI in Energy Management Market by Application ($ Million)
7.1. Energy Transmission
7.2. Energy Generation
7.3. Energy Distribution
7.4. Others
8. Global AI in Energy Management Market by End-User ($ Million)
8.1. Robotics
8.2. Renewables Management
8.3. Demand Forecasting
8.4. Safety and Security
8.5. Others
9. Regional Analysis
9.1. North American AI in Energy Management Market Sales Analysis Component Type | Deployment Mode| Application| End-User | Country ($ Million)
9.1.1. United States
9.1.2. Canada
9.2. European AI in Energy Management Market Sales Analysis Component Type | Deployment Mode| Application| End- User | Country ($ Million)
9.2.1. UK
9.2.2. Germany
9.2.3. Italy
9.2.4. Spain
9.2.5. France
9.2.6. Russia
9.2.7. Rest of Europe
9.3. Asia-Pacific Global AI in Energy Management Market Sales Analysis Component Type | Deployment Mode| Application| End-User | Country ($ Million)
9.3.1. China
9.3.2. Japan
9.3.3. South Korea
9.3.4. India
9.3.5. Australia & New Zealand
9.3.6. ASEAN Countries (Thailand, Indonesia, Vietnam, Singapore, And Other)
9.3.7. Rest of Asia-Pacific
9.4. Rest of the World AI in Energy Management Market Sales Analysis Component Type | Deployment Mode| Application| End-User | Country ($ Million)
9.4.1. Latin America
9.4.2. Middle East and Africa
10. Company Profiles
10.1. AutoGrid Systems, Inc.
10.2. Aveva Group Ltd.
10.3. BIDGELY Inc.
10.4. BrAInBox AI
10.5. C3.AI Inc.
10.6. Dubai Electricity and Water Authority (PJSC)
10.7. Duke Energy Corp.
10.8. Enel Italia S.p.a.
10.9. Fluence Energy, LLC
10.10. GE Vernova Group
10.11. Iberdrola, S.A.
10.12. Intel Corp.
10.13. N-iX LTD.
10.14. Omdena Inc.
10.15. SAP SE
10.16. Schneider Electric
10.17. Southern Company
10.18. SparkCognition, Inc.
10.19. Stem, Inc.
10.20. Uplight, Inc.

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