AI in Energy Market to Reach $14.0 Billion, Globally, by 2029 at 17.2% CAGR: AMR

The AI in energy market is growing as AI enables real-time supply-demand balance, improving the reliability of renewable sources like wind and solar.

WILMINGTON, DE, UNITED STATES, January 30, 2025 /EINPresswire.com/ -- Allied Market Research published a report, titled, "AI in Energy Market by Component Type (Solutions, and Services), Deployment Type (On-Premise, and Cloud), Application (Robotics, Renewables Management, Demand Forecasting, Safety & Security, Infrastructure, and Others), and End-Use (Energy Transmission, Energy Generation, Energy Distribution, and Utilities): Global Opportunity Analysis and Industry Forecast, 2024-2029". According to the report, the 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.

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Prime determinants of growth
The global AI in energy market has experienced growth due to several factors such as increase in demand for modern grid and clean energy is expected to growth of AI in energy market. However, the high initial cost of implementing AI technologies is expected to hamper market expansion. Surge in energy storage optimization is expected to provide lucrative opportunities in the AI in energy market during the forecast period.

The solution segment is expected to remain the largest type throughout the forecast period.
By component type, the solution segment is expected to dominate the market during the forecast period as AI algorithms optimize the operation of smart grids by analyzing vast amounts of data from sensors, meters, and other grid components. AI-driven energy storage systems optimize charging and discharging schedules based on factors such as energy prices, demand patterns, and grid constraints. Reinforcement learning algorithms adopt storage strategies over time, maximizing economic benefits while ensuring system reliability. AI models analyze market data, including energy prices, supply-demand dynamics, regulatory policies, and geopolitical factors, to optimize trading strategies.

The cloud segment is expected to lead throughout the forecast period.
By deployment type, the cloud segment is expected to lead the market during the forecast period as cloud providers invest in green data center technologies, such as energy-efficient hardware, cooling systems, and renewable energy sources. AI optimizes the utilization of these resources by dynamically adjusting their usage based on workload demands and environmental conditions. AI-powered auto-scaling systems automatically adjust the number of running instances or containers based on workload fluctuations. By scaling up or down in response to demand changes, cloud deployments optimize energy usage by aligning resource provisioning with actual requirements.

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Safety & Security segment dominated the AI in energy market throughout the forecast period.
By application, the safety & security segment is anticipated to dominate the market throughout the forecast period as AI systems identify anomalies in energy consumption patterns that may indicate security breaches or equipment malfunctions. For example, unusual spikes or drops in energy usage signal potential security threats or operational issues. AI algorithms assist in developing emergency response plans by simulating various scenarios and identifying the most effective strategies for mitigating risks and minimizing damage during emergencies such as fires, explosions, or chemical leaks.
The utilities segment dominated the AI in energy market throughout the forecast period.

By end-use, the utilities segment is projected to dominate the market during the forecast period. AI-powered Energy Management Systems (EMS) continuously monitor and control energy-consuming devices in buildings and industrial facilities. They adjust settings based on occupancy, weather conditions, and energy prices to minimize consumption without sacrificing comfort or productivity. AI optimizes the operation of smart grids by balancing supply and demand, managing energy storage systems, and integrating renewable energy sources. This improves grid stability, reduces losses, and facilitates the integration of distributed energy resources.

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Asia-Pacific to maintain its dominance by 2033.
By region, the Asia-Pacific region is expected to dominate the market by 2033. AI algorithms analyze data from sensors and smart meters to identify patterns and anomalies in energy consumption, enabling businesses and households to optimize their energy usage. This is particularly important in densely populated areas such as Singapore and Hong Kong. AI algorithms are employed in energy trading platforms to optimize energy trading strategies, forecast market trends, and manage risk. This is especially relevant in countries with deregulated energy markets like Australia and parts of Southeast Asia.

Players: -
• Atos SE
• Siemens Energy
• Schneider Electric
• GE Vernova
• Terex Corporation
• Vestas
• Iberdrola, S.A.
• JinkoSolar Holding Co., Ltd.
• AutoGrid Systems, Inc
• Constellation.

The report provides a detailed analysis of these key players in the global AI in energy market. These players have adopted different strategies such as new product launches, collaborations, expansion, joint ventures, agreements, and others to increase their market share and maintain dominant shares in different regions. The report is valuable in highlighting business performance, operating segments, product portfolio, and strategic moves of market players to showcase the competitive scenario.

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