AI in Energy Market Expected to Reach $14.0 Billion by 2029

According to a new report published by Allied Market Research, titled, “AI in energy market" was valued at $5.4 billion in 2023, and is projected to reach $14.0 billion by 2029, growing at a CAGR of 17.2% from 2024 to 2029.

Artificial Intelligence (AI) in energy refers to the application of advanced computational algorithms and data analytics to optimize various aspects of energy production, distribution, and consumption. By leveraging vast amounts of data generated from smart grids, renewable energy sources, and consumer behavior, AI can enhance decision-making processes, predict energy demand, and improve efficiency across the energy sector. This technology plays a crucial role in the integration of renewable energy systems, enabling real-time monitoring and management of energy resources. 

Market Dynamics

The increase in demand for renewable energy is significantly driving the adoption of artificial intelligence (AI) in the energy sector. As the world shifts towards sustainable energy sources such as solar, wind, and hydroelectric power, the complexity of managing these resources escalates. According to the International Energy Agency (IEA), solar PV and wind account for 95% of the expansion, with renewables overtaking coal to become the largest source of global electricity generation by early 2025. Renewable energy generation is inherently variable, with fluctuations based on weather conditions and time of day. AI plays a pivotal role in optimizing the integration of these renewable sources into the energy grid by enabling advanced predictive analytics. By analyzing weather patterns, historical data, and real-time energy consumption, AI forecasts energy production and demand more accurately, facilitating a smoother transition between energy supply and demand. 

Furthermore, AI enhances the operational efficiency of renewable energy systems. For instance, in solar energy, AI algorithms optimize the positioning of solar panels, enhancing their energy capture efficiency. In wind energy, predictive maintenance powered by AI identifies potential issues before they lead to system failures, thus reducing downtime and maintenance costs. As energy storage solutions, such as batteries, become more critical in balancing supply and demand, AI can optimize the charging and discharging cycles, ensuring that energy is stored when it's abundant and released when needed. This capability is essential for enhancing the reliability of renewable energy sources, making them more appealing to consumers and investors alike. All these factors are expected to drive the demand for AI in the energy market during the forecast period. 

However, high implementation costs pose a significant barrier to the widespread adoption of artificial intelligence (AI) in the energy sector. The initial investment required to develop, integrate, and maintain AI systems are substantial, often encompassing hardware, software, and specialized talent. Energy companies may need to upgrade their existing infrastructure to accommodate AI technologies, which further escalates costs. All these factors hamper AI in energy market growth. 

Carbon emission monitoring and reduction present significant opportunities for the application of artificial intelligence (AI) in the energy sector. As governments and organizations increasingly commit to reducing greenhouse gas emissions and transitioning to more sustainable practices, AI plays a pivotal role in monitoring emissions in real-time. Advanced AI algorithms analyze vast amounts of data from various sources, including energy production facilities, transportation networks, and industrial operations, to track carbon emissions accurately. This capability allows organizations to identify high-emission processes and areas for improvement, facilitating targeted interventions that can lead to substantial reductions in their carbon footprint. All these factors are anticipated to offer new growth opportunities for AI in energy market. 

Segment Highlights 

The artificial intelligence (AI) in energy market is segmented into component type, deployment type, application, end-use, and region. On the basis of component type, it is classified into solutions and services. By deployment type, the market is categorized into on-premise and cloud. On the basis of application, the market is fragmented into robotics, renewables management, demand forecasting, safety & security, infrastructure, and others. On the basis of end-use, it is divided into energy transmission, energy generation, energy distribution, and utilities. Region-wise, the market is studied across North America, Europe, Asia-Pacific, and LAMEA. 

Key market players in the AI in energy market include Atos SE, Siemens Energy, Schneider Electric, GE Vernova, Terex Corporation, Vestas, Iberdrola, S.A., JinkoSolar Holding Co., Ltd., AutoGrid Systems, Inc., and Constellation.