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Prominent AI in Energy Market Trend for 2025: AI-Powered Energy Infrastructure Operations For Optimal Energy Management In The Telecom Sector
AI in Energy Market
The upswing in microgrid usage is anticipated to fuel the expansion of AI within the energy sector. A microgrid is a localized energy system that can function independently or in tandem with the primary power grid. Microgrids' pivotal role in integrating and optimizing AI technology in the energy domain enables smart energy management, grid enhancement, and the assimilation of renewable energy sources. These aid in AI energy applications such as demand response, load balancing, and incorporation of renewable energy. The usage of microgrids leading to a substantial growth of AI in the energy market becomes prominent. For example, in September 2024, the Energy Trends published by the Department for Energy Security and Net Zero, a UK-based ministerial department, noted that the installed capacity surged 3.9 percent (2.1 GW) in the second quarter of 2024 compared to the same quarter in 2023, culminating in a total of 57.5 GW. As such, the escalating usage of microgrids will likely continue to spur the growth of AI in the energy sector.
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What growth opportunities are expected to drive the ai in energy market's CAGR through 2034?
The market size of AI in the energy sector has seen an impressive escalation in the previous years. It is projected to surge from $19.03 billion in 2024 to $22.94 billion in 2025, with a compound annual growth rate (CAGR) of 20.6%. The factors contributing to the growth during the historic period include efficiency through data analytics, managing demand responses, predictive maintenance, grid optimization, and the incorporation of renewable energy.
In the coming years, the market size of AI in energy is predicted to experience substantial expansion. The growth will ascend to $50.91 billion by 2029, with a compound annual growth rate (CAGR) of 22.0%. This growth during the forecast period can be credited to factors such as decentralized energy systems, management of energy storage, smart cities and infrastructure, transportation electrification, and the incorporation of edge computing. Key trends in the forecast period encompass energy efficiency analytics, autonomous energy infrastructure, solutions for cybersecurity, virtual power plants, and edge ai for energy administration.
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What are the emerging trends shaping the future of the ai in energy market?
Advancements in technology are becoming an increasingly popular trend within the AI in the energy industry. Major players in this domain are harnessing new technologies to maintain market dominance. For instance, in February 2022, the Sweden-based IT services and consulting firm, Telefonaktiebolaget LM Ericsson, launched their AI-powered Energy Infrastructure Operations. This is an energy management system that aids communication service providers in minimizing their energy consumption across their network infrastructure by leveraging artificial intelligence and advanced data analytics. With the help of AI, energy infrastructure operations can reduce energy-related OPEX by 15%, passive infrastructure-related site visits by 15%, and energy-related outages by 30%. This contributes to lowering OPEX and CO2 emissions for communication service providers by utilizing AI and data analytics to optimize energy efficiency and site availability.
Which growth-oriented segments of the ai in energy market are leading the industry's development?
The AI in energy market covered in this report is segmented -
1) By Offering: Support Services, Hardware, AI-As-A-Service, Software
2) By Deployment: On-Premise, Cloud
3) By Application: Demand Response Management, Fleet And Asset Management, Renewable Energy Management, Precision Drilling, Demand Forecasting, Infrastructure Management, Other Applications
4) By End User: Energy Transmission, Energy Generation, Energy Distribution, Utilities, Other End Users
Subsegments:
1) By Support Services: Consulting Services, Implementation Services, Maintenance And Support Services
2) By Hardware: AI-Powered Sensors, Smart Meters, Edge Computing Devices
3) By AI-As-A-Service: Machine Learning Platforms, Data Analytics Services, Model Training And Development Services
4) By Software: Energy Management Software, Predictive Maintenance Software, Demand Response Software, Grid Management Software
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What regions are leading the charge in the ai in energy market?
North America was the largest region in AI in the energy market in 2024. Asia-pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the AI in energy market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
What companies are at the forefront of innovation in the ai in energy market?
Major companies operating in the AI in energy market include Google, Microsoft Corporation, Engie SA, Huawei Technologies Co Ltd., Siemens AG, General Electric Company, Intel Corporation, International Business Machines Corporation, Iberdrola, Cisco Systems Inc., Schneider Electric SE, Honeywell International Inc., Flex Ltd., ABB Ltd, Duke Energy Corporation, Nvidia Corporation, Alpiq Holding AG, ATOS SE, Enel Green Power S.p.A., Databricks Inc., C3 AI, Uptake Technologies, Sentient Energy Inc., AutoGrid Systems Inc., Arundo Analytics Inc., Bidgely Inc., Verdigris Technologies, Greenbird Integration Technology AS, AppOrchid Inc., Ecube Labs Co. Ltd
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What Is Covered In The AI in Energy Global Market Report?
• Market Size Forecast: Examine the ai in energy market size across key regions, countries, product categories, and applications.
• Segmentation Insights: Identify and classify subsegments within the ai in energy market for a structured understanding.
• Key Players Overview: Analyze major players in the ai in energy market, including their market value, share, and competitive positioning.
• Growth Trends Exploration: Assess individual growth patterns and future opportunities in the ai in energy market.
• Segment Contributions: Evaluate how different segments drive overall growth in the ai in energy market.
• Growth Factors: Highlight key drivers and opportunities influencing the expansion of the ai in energy market.
• Industry Challenges: Identify potential risks and obstacles affecting the ai in energy market.
• Competitive Landscape: Review strategic developments in the ai in energy market, including expansions, agreements, and new product launches.
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