AI in Energy market was valued at $14.8 billion in 2024 and is projected to reach $76.3 Billion by 2035, growing at a CAGR of 16.1% from 2025 to 2035.
Artificial Intelligence (AI) has the potential to significantly enhance grid management, which is one of the most complex yet highly reliable technologies. AI can aid in planning, permitting, operations, reliability, and resilience in grid systems (a network of power plants, transmission lines, and distribution centers). It can also support a range of applications to help achieve climate goals by 2050. This market is driven by increasing demand for energy optimization, growing adoption of renewable energy sources and smart grids, government regulations, and incentives for sustainable energy use, integration of IoT and AI technologies for real-time energy monitoring, and expansion of smart cities and urbanization fuels AI-driven energy solutions. According to the International Energy Agency (IEA), in November 2023, a recent estimate suggests that AI already serves more than 50 different uses in the energy system.
Market Dynamics
Smart Grid Infrastructure Development
The development of smart grid infrastructure is a significant driver for the integration of AI in the energy market. AI technologies are playing an increasingly critical role in transforming traditional grids into more intelligent, efficient, and resilient systems. Several major economies have announced significant investments to modernize and digitize their electricity grids. For instance, in 2022, the European Commission launched the EU action plan ‘Digitalization of the Energy System’. It hopes to invest $633.0 billion in the European electricity grid by 2030, with $184.0 billion going towards digitalization, such as smart meters, automated grid management, digital technologies for metering, and improvements to field operations. Similarly, in North America, the US announced its Grid Resilience Innovative Partnership (GRIP) Program in 2022, providing $10.5 billion in funding to support the upgrade and expansion of the country’s electric grids.
AI and Global Energy Innovation
Presently, the modernizing and decarbonizing of the grid are critical paths to meeting energy goals. A modernized grid allows efficient decision-making based on multi-directional flows of energy and information, rapid integration of new carbon-free generation sources such as wind and solar, actively balances both electricity supply and demand (including increasing electrification and integration of grid-connected distributed energy resources), and proactively mitigate risks associated with climate change and extreme events. AI could support a range of applications to help advance an equitable clean energy economy. Reaching net-zero Greenhouse Gas (GHG) emissions across the economy requires addressing unique challenges across many end-use sectors including transportation, buildings, industry, and agriculture and there are promising opportunities for AI to accelerate decarbonization in each. Examples include optimizing planning for electric vehicle (EV) charging networks, enabling virtual power plants, generating the design of structural materials for manufacturing, and discovering alternatives for critical materials. Employing a portfolio of these AI-enabled solutions, while mitigating any potential risks, can support transformations needed across the economy to tackle the climate crisis, reduce costs, and improve lives.
According to the International Association for Energy Economics, AI is transforming China’s energy sector by improving operational efficiency, driving innovation, and aiding in the transition to cleaner energy sources. The technology helps optimize energy consumption, enhance grid management, and integrate renewable energy. Real-world examples include AI-powered smart grids in Guangzhou, predictive maintenance in power generation, and AI-driven wind energy forecasting in Inner Mongolia. However, the adoption of AI faces challenges such as regulatory hurdles, data quality issues, and a lack of skilled talent. Despite these challenges, AI presents significant opportunities for improving energy efficiency, reducing environmental impact, and supporting China’s goals for sustainable energy development.
Market Segmentation and Growth Areas
Software Segment to Lead the Market with the Largest Share
AI software in the energy management market comprises distinct platforms or applications that utilize AI and ML capabilities to enhance the operation, management, and integration of energy systems. These solutions are based on the basic ideology of analyzing real-time data from diverse sources across the energy infrastructure, which is further processed for identifying consumption behaviors, usage disparities, and energy flow disruptions, among others. Furthermore, this software is offered in two distinct forms, including platforms/suites or individual software, to energy producers, asset management companies, and investing companies, which includes energy storage optimization software, energy demand forecasting software, energy trading software, and asset management software, among others. Moreover, the dynamics for integration of AI-powered tools, particularly software, have experienced a positive shift in recent years. This shift is promoted by factors such as advancements in product offerings for energy workflows, regulatory pressure for automating the energy sector, increasing complexities of activities across the energy sector, and growing investments in digital energy tools and systems. Additionally, this changing need and demand of the energy sector has readily been fulfilled by energy software development companies by incorporating several advancements and developments in their product offerings, which include cloud-based energy management systems, AI-driven predictive grid optimization software, autonomous energy trading, and portfolio management platforms, among others. For instance, in September 2024, SLB launched the Lumi data and AI platform, integrating advanced AI, including generative AI, into workflows across the energy value chain. The platform is open, secure, and modular, providing access to high-quality data spanning subsurface, surface, planning, and operations. This enhanced connectivity fosters cross-domain collaboration, delivering new insights and intelligence to improve decision-making speed and quality at an enterprise level.
Cloud Service Providers: A Key Segment in Market Growth
Cloud technology has been instrumental in helping energy companies manage their data and use it effectively. AI-driven cloud deployment is transforming the energy market by improving operational efficiency and enabling more sustainable practices. Predictive maintenance is one of the significant applications in cloud deployment, where companies such as GE Digital utilize AI to monitor thermal power plants and turbines. AI can predict potential equipment failures, allowing for proactive maintenance and reducing costly downtime. This application ensures that critical infrastructure operates efficiently and without unexpected disruptions. Another major area where AI and cloud technology are being deployed is energy demand forecasting. For instance, Google’s DeepMind, working with Google Cloud, applied AI to optimize the cooling of data centers. Predicting cooling requirements based on factors such as weather patterns and server activity, the system can reduce energy consumption, making operations more sustainable. Similarly, Siemens uses cloud-based AI platforms such as MindSphere, Spectrum Power, SIESTOR, and others to manage smart grids, balancing supply and demand, optimizing power distribution, and improving grid reliability.
Challenges: Power Sourcing and Infrastructure Hurdles
Data center companies face challenges in sourcing sufficient volumes of power, particularly from carbon-free generation sources. New, large-scale data centers often have significant power requirements, which, depending on the target build jurisdiction, may require costly, time-consuming new infrastructure solutions. Integrating renewable energy is also challenging due to variability and storage issues, which hinder consistent power delivery. Transmission additionally brings complexity as high-voltage lines are near capacity in some regions. In the US, some utility companies have even halted new service requests or begun rationing power.
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Regional Outlook
The global AI in Energy market is further divided by geography, including North America (the US and Canada), Asia-Pacific (India, China, Japan, South Korea, Australia and New Zealand, ASEAN Countries, and the Rest of Asia-Pacific), Europe (the UK, Germany, France, Italy, Spain, Russia, and the Rest of Europe), and the Rest of the World (the Middle East & Africa, and Latin America).
North America Region Dominates the Market with Major Share
The US AI in energy management market is anticipated to experience significant growth during the forecast period, driven by government initiatives, an increase in renewables generation, expansion of AI in energy management, and others. According to the US Department of Energy (DOE), ML models have been used by researchers and the energy industry to gather value from vast pools of data available through the power grid’s existing distributed network of sensors, meters, and plants. DOE has been a supportive partner working with the industry to build a vision for the smart grid through National Labs, supporting continued R&D of AI models for scientific and energy applications. In April 2024, DOE invested $13 million in the initiative to build AI-powered tools to improve the siting and permitting of clean energy infrastructure and partnered with Pacific Northwest National Laboratory (PNNL) to develop PolicyAI, a policy-specific Large Language Model test bed that will be used to develop software to augment National Environmental Policy Act and related reviews.
AI Integration Enhances Sustainability in Japan’s Energy Sector
Japan’s proactive approach to integrating AI in energy applications, such as predictive maintenance, demand forecasting, and grid management, is set to propel the growth of the AI in energy management market. The country is pushing itself to partner with international companies to expand its AI ecosystem, Japan aims to enhance productivity and energy efficiency. For instance, in December 2022, Japan’s Ministry of the Environment partnered with Oracle Opower to reduce carbon dioxide emissions through behavioral science and AI. The collaboration, involving Oracle Japan, Jyukankyo Research Institute, and five major utilities, provided 300,000 households with personalized energy-saving reports. These reports helped reduce emissions by up to 2.8%, leading to a 47,000-ton reduction in CO2 between 2017 and 2021. The success of the program, with high engagement rates, demonstrated the effectiveness of AI and behavioral science in driving energy efficiency, prompting some utilities to continue the initiative. Thus, AI integration enhances efficiency and sustainability, directly contributing to the growth of the AI in energy management market during the forecast period.
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Market Players Outlook
The major companies operating in the global AI in Energy market include Microsoft Corp., IBM, Siemens Energy, Nvidia Corp., and Alphabet Inc (Google LLC), among others. Market players are leveraging partnerships, collaborations, mergers, and acquisition strategies for business expansion and innovative product development to maintain their market positioning.
Recent Developments
- In October 2024, Google signed the first corporate deal to purchase nuclear power from multiple small modular reactors, aiming to support AI-driven energy demands. Partnering with Kairos Power, Google plans to bring its first reactor online by 2030, with further deployments through 2035, securing 500 megawatts from six to seven reactors.
- In July 2024, the International Olympic Committee (IOC) deployed Alibaba Cloud’s Energy Expert sustainability platform to monitor and optimize electricity consumption at Paris 2024 Olympic venues, aiming to reduce the event’s carbon footprint. The data collected will include electricity consumption, power demand, venue capacity, and weather conditions, supporting both the Olympics and Paralympics in their sustainability efforts and informing future event planning.
- In September 2023, Ontario Power Generation (OPG) teamed with Microsoft to develop an AI-powered chatbot for employees called ChatOPG. The chatbot is designed to provide information, answer questions, and act as a personal assistant at work. Adopting AI technology helped OPG drive operational efficiencies by improving productivity, safety, and performance among employees.
- In May 2023, BHP accelerated time to value with Microsoft AI and machine learning, using real-time plant data from the copper concentrators and Microsoft Azure Machine Learning to make hourly predictions.
Some of the key companies in the global AI in Energy market include:
- Brainbox AI Inc.
- AI, Inc.
- Edgecom Energy
- Fluence Energy, Llc
- Grid Edge Ltd.
- Grid4c
- Gridx, Inc.
- Mprest Systems Ltd.
- Nnergix Energy Management, Sl
- Power Factors, Llc
- Tibo Energy
- Vroc Australia Pty Ltd.
- Uplight Inc.
AI in Energy Market Segmentation Analysis
Global AI in Energy Market by Type
- Solutions
- Â Services Memory
Global AI in Energy Market by Deployment
- On-premises
- Cloud
Global AI in Energy Market by Application
- Energy Transmission
- Energy Generation
- Energy Distribution
- Others
Global AI in Energy Market by End-User
- Robotics
- Renewables Management
- Demand Forecasting
- Safety and Security
- Others
Regional Analysis
- North America
- United States
- Canada
- Europe
- UK
- Germany
- Italy
- Spain
- France
- Rest of Europe
- Asia-Pacific
- China
- India
- Japan
- South Korea
- Rest of Asia-Pacific
- Rest of the World
- Latin America
- Middle East and Africa
Anurag Tiwari
Director Sales Division
+91 780-304-0404
info@omrglobal.com
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