The AI in energy market is growing rapidly due to increasing adoption of smart grids, renewable energy integration, and demand for predictive maintenance, real-time analytics, and operational efficiency across the energy sector.
Austin, April 15, 2026 (GLOBE NEWSWIRE) — The AI in Energy Market was valued at USD 15.99 billion in 2025 and is expected to reach USD 297.36 billion by 2035, growing at a CAGR of 33.95% during the forecast period of 2026-2035.
The market for AI in energy is expanding quickly as a result of the growing use of digital energy management solutions, smart grids, and renewable energy integration. Utilities and energy industries are implementing AI technology due to the growing demand for predictive maintenance, demand forecasting, operational efficiency, and cost optimization.
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The U.S. AI in Energy Market was valued at USD 4.39 billion in 2025 and is expected to reach USD 79.47 billion by 2035, growing at a CAGR of 33.59% over 2026-2035.
Due to enhanced grid digitalization, early AI adoption, the growth of renewable energy, and robust government support, the U.S. AI in Energy Market is expanding, encouraging utilities to use AI for cost optimization, demand forecasting, predictive maintenance, and operational efficiency.
Market is Propelling Owing to Rising Operational Complexity and Cost Pressures Across Power Generation and Grids Globally
Energy firms must use advanced analytics to make quicker and more accurate decisions due to the increasing fluctuation of electricity consumption, intermittent renewable energy, fuel price volatility, and grid congestion. AI immediately lowers unplanned outages and operating costs by enabling real-time load forecasting, predictive maintenance, and asset performance optimization. In order to effectively manage dispersed energy resources, optimize dispatch, and balance supply and demand, utilities are depending more and more on artificial intelligence. Operators can react proactively rather than reactively thanks to the capacity to process enormous amounts of sensor, SCADA, and market data. Reliability, cost control, and profitability across generating, transmission, and distribution networks are greatly enhanced by these efficiency increases.
Segmentation Analysis:
By Component
Solutions dominated with 61% share in 2025 due to extensive adoption of integrated AI platforms for grid optimization, predictive maintenance, asset performance management, and real-time analytics across utilities. Services segment is expected to grow at the fastest CAGR from 2026–2035 as energy companies increasingly seek consulting, integration, customization, training, and lifecycle management support.
By End-user
Utilities dominated with 34% share in 2025 as utilities widely deploy AI for grid monitoring, outage management, load balancing, asset optimization, and regulatory compliance. Energy Generation segment is expected to grow at the fastest CAGR from 2026–2035 driven by rapid renewable capacity additions, hybrid power plants, and digitalized generation assets.
By Application
Renewables Management dominated with 23% share in 2025 due to rapid expansion of solar, wind, and energy storage projects globally. Demand Forecasting segment is expected to grow at the fastest CAGR from 2026–2035 as electrification, electric vehicle adoption, and decentralized energy resources increase consumption volatility.
By Deployment
Cloud dominated with 61% share in 2025 due to its ability to provide scalable, flexible, and cost-effective infrastructure for data storage, real-time analytics, and AI model deployment. The segment is expected to grow at the fastest CAGR from 2026–2035 as adoption of advanced AI solutions, IoT connectivity, and digital energy management accelerates, enabling faster innovation and operational efficiency across utilities and energy operators.
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Regional Insights:
North America dominated the AI in Energy Market with the highest revenue share of about 39% in 2025 due to the presence of well-established energy infrastructure, advanced digitalization, and early adoption of AI technologies.
Asia Pacific is predicted to develop at the fastest CAGR of almost 15.22% between 2026 and 2035 due to rising renewable energy installations, growing urbanization, and rising energy demand. Growing government spending on digitalization projects, AI-enabled energy management, and smart grids, as well as adoption by new utilities and industrial sectors, are driving market growth.
Key Players:
- General Electric
- Siemens Energy
- Schneider Electric
- ABB Ltd
- Honeywell International
- IBM
- C3.ai
- AutoGrid
- SparkCognition
- Uplight
- DataRobot
- Iberdrola
- Tibber
- Samotics
- Envision Digital
- Hitachi Energy
- SenseTime
- Fujitsu
- Origami Energy
- ATOS SE
Recent Developments:
At Innovation Summit North America 2025, Schneider Electric highlighted AI-powered EcoStruxure solutions to enhance grid resiliency, digital operations, and future-ready energy management.
IBM study revealed 74% of energy and utility companies are adopting AI, highlighting its watsonx platform to accelerate automation and AI workflows.
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Exclusive Sections of the Report (The USPs):
- AI Technology Deployment & Adoption Metrics – helps you understand AI usage across predictive maintenance, grid optimization, and load forecasting, along with sector-wise adoption and integration with renewable energy systems.
- Operational Efficiency & Cost Optimization Insights – helps you evaluate reduction in energy loss, improvements in grid stability, faster response times, and cost savings achieved through AI implementation.
- R&D, Innovation & Collaboration Trends – helps you identify patent activity, investment in smart grid and renewable AI projects, development timelines, and partnerships with AI technology providers.
- Regulatory Compliance & Cybersecurity Metrics – helps you assess adherence to energy regulations, impact of data privacy laws, approval requirements, and availability of incentives for AI deployment.
- Financial Performance & Market Penetration Analysis – helps you analyze ROI, deployment scale (pilot vs. full-scale), cost of implementation, and regional adoption trends across the energy sector.
- Supply Chain & Technology Integration Insights – helps you track connectivity with IoT and smart infrastructure, cloud vs. on-premise deployment trends, integration timelines, and supplier concentration.
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