AI-Based Energy Forecasting Services Market Size, Share and Trends 2026 to 2035

What is AI-Based Energy Forecasting Services Market Size?

The global AI-based energy forecasting services market is driven by rising demand for smart grid solutions, predictive analytics, and sustainable energy management worldwide. The market is proliferating due to the increasing energy demand from crucial sectors across the globe, the need to integrate renewable energy sources to meet the requirements, and the advancement of AI tools and platforms to conduct precise energy generation forecasting for effective energy distribution and management.

Market Highlights

• By region, North America held the largest market share in 2025.
• By region, Asia Pacific is expected to witness the fastest CAGR during the foreseeable period of 2026-2035.
• By service type, the forecasting-as-a-service segment held the largest market share in 2025.
• By service type, the managed forecasting & monitoring segment is expected to witness the fastest CAGR during the foreseeable period.
• By modeling technology, the machine learning/deep learning segment held the largest market share in 2025.
• By modeling technology, the probabilistic & ensemble forecasting segment is expected to witness the fastest CAGR during the foreseeable period.
• By deployment & delivery mode, the cloud/SaaS APIs & portals segment held the largest market share in 2025.
• By deployment & delivery mode, the hybrid (cloud training + edge inference) segment is expected to witness the fastest CAGR during the foreseeable period.
• By data inputs utilized, the smart meter/AMI time series segment held the largest market share in 2025.
• By data inputs utilized, the IoT/EV/building energy management data segment is expected to witness the fastest CAGR during the foreseeable period.
• By end user, the vertically integrated utilities & retail suppliers segment held the largest market share in 2025.
• By end user, the aggregators/VPP operators/DER providers segment is expected to witness the fastest CAGR during the foreseeable period of 2026-2035.

AI-Based Energy Forecasting Services Market Means

The Artificial Intelligence-based energy forecasting services market comprises third-party and vendor-provided services that use artificial intelligence (machine learning, deep learning, hybrid physics-informed models, probabilistic forecasting) to predict electricity demand, renewable generation, prices, and flexibility needs across multiple time horizons.
Services include Forecasting-as-a-Service (FaaS), managed model development & retraining, API/streaming forecast delivery, scenario & market simulations, and customized modelling for utilities, aggregators, IPPs, energy traders, and large consumers.
Value drivers include rapid renewable integration, growth of distributed energy resources (DERs), electrification (EVs, heat pumps), need for intraday balancing and market optimization, and outsourcing of complex model operations to specialized providers. Delivery models span cloud/SaaS, edge/embedded inference, hybrid managed offerings, and outcome-based contracts tied to forecast accuracy/KPI improvements.

AI-Based Energy Forecasting Services Market Outlook

• Industry growth overview: The AI-based energy forecasting market is rapidly expanding due to the increasing energy demand by leading sectors for higher operational efficiency, availability of renewable energy sources, and their integration to existing energy provider systems, along with the enhanced sharpness of AI algorithms and cloud computing infrastructure.
• Sustainability trends : Sustainability is a major and core part of the market's growth, which further extends to renewable energy management, efficient use of energy, and compliance with energy regulations to prevent misconduct. AI solutions offer inherent management of solar and wind energy, allowing grid operators to forecast energy generation more precisely. Thus, many leading companies leverage AI to cleverly optimize their energy consumption for cost efficiency.
• Major Investors : A substantial investment comes from governmental bodies, specialized venture capital firms, and leading companies like Siemens AG, ABB, Schneider Electric, and Amazon Web Services. Also, entities like the U.S DOE, IIT Bombay, and sustainable development technology in Canada offer continuous funding for research and start-ups.

Market Scope

Segmental Insights

Service TypeInsights

Why is Forecasting-as-a Service Leading in the AI-based Energy Forecasting Services Market?

Forecasting-as-a Service

The forecasting-as-a-service segment held the largest market share in 2025. The segment is dominating due to the increasing cost and expertise needed to develop and maintain AI solutions. FaaS solutions provide many compelling benefits, with high scalability, continuous learning, and model maintenance. They greatly shortened implementation cycles as well.

Managed Forecasting & Monitoring

The managed forecasting & monitoring segment is expected to witness the fastest CAGR during the foreseeable period. The segment is rapidly expanding due to many companies seeking to leverage AI advancements with cost efficiency and resource optimization, owing to the growing complexity of modern energy systems.

Modeling TechnologyInsights

How are ML/DL Technologies Facilitating the AI-based Energy Forecasting Services Market?

Machine Learning/Deep Learning

The machine learning/deep learning segment held the largest market share in 2025. The segment is dominating due to its ability to analyze vast, complex, and non-linear datasets to predict hidden patterns and give precise results. These technologies outperform conventional ways for energy management by adding crucial variables, which further lead to cost savings.

Probabilistic & Ensemble Forecasting

The probabilistic & ensemble forecasting segment is expected to witness the fastest CAGR during the foreseeable period. The segment is growing due to the rapid integration of highly variable renewable energy sources like solar and wind into the grid and the requirement for highly accurate uncertainty quantification that leads to effective grid operation while managing risks.

Deployment & Delivery Mode Insights

What is offered by cloud/SaaS Deployment in the AI-based Energy Forecasting Services Market?

Cloud/SaaS APIs & Portals

The cloud/SaaS APIs & portals segment held the largest market share in 2025. The segment is dominating due to its prominent advantages like high scalability and flexibility, along with simplified management as compared to conventional on-premises infrastructure. The SaaS model helps eliminate the mandate of substantial investment at an initial level for hardware, software, and other components with maintenance teams.

Hybrid (Cloud Training + Edge Inference)

The hybrid (cloud training + edge inference) segment is expected to witness the fastest CAGR during the foreseeable period. The segment is expanding due to its capability to provide low-latency, real-time processing of edge computing, along with huge computational power and higher scalability for the cloud. It thus offers real-time decision-making for energy management.

Data Inputs UtilizedInsights

Why Does Smart Meter/AMI Time Series Preference Exist in the AI-based Energy Forecasting Services Market?

Smart Meter/AMI Time Series

The smart meter/AMI time series segment held the largest market share in 2025. The segments dominate due to their capability to offer high-volume real-time data with high granularity, which is crucial for the precision and effectiveness of modern AI algorithms. It fills the gap created by conventional forecasting methods that struggle with the complex nature of modern grids.

IoT/EV/Building Energy Management Data

The IoT/EV/building energy management data segment is expected to witness the fastest CAGR during the foreseeable period. The segment is growing primarily owing to the rising integration of distributed energy resources and the shift towards sustainability goals with regulatory compliance. Smart meter/AMI offers high resolution and real-time data for precise forecasting.

End UserInsights

Which End-user Dominates the AI-based Energy Forecasting Services Market?

Vertically Integrated Utilities & Retail Suppliers

The vertically integrated utilities & retail suppliers segment held the largest market share in 2025. The segment is dominating due to the crucial roles of utilities & grid operators to maintain grid stability and reliability even in increasingly complex energy systems. The unique challenges they face can be resolved by AI-based forecasting that leverages predictive capabilities offered by the AI system.

Aggregators/VPP Operators/DER Providers

The aggregators/VPP operators/DER providers segment is expected to witness the fastest CAGR during the foreseeable period of 2025-2034. The segment is proliferating due to the growing penetration of variable renewable energy sources and increasing demand for improved grid stability. Also, AI-based forecasting provides the ability to develop optimal trading and bidding for aggregators, helping avoid blackouts.

Regional Analysis

What Made North America a Dominant Force in the AI-based Energy Forecasting Services Market?

North America held the largest market share in 2025. The region is dominating due to the combination of major reasons like well-established and mature infrastructure, substantial private and public investment, supportive government regulations aiming to establish sustainable energy practices in North America, along with a highly skilled workforce.

Federal and state-level policies and incentives in the leading countries like the U.S. and Canada are actively promoting grid modernization, aiming to provide clean energy throughout the region. Private giants like Microsoft, AWS, and Google, along with energy companies, are heavily investing in R&D of AI-based energy forecasting services.

The U.S. AI-based Energy Forecasting Services Market

The region is expanding due to the prioritization of integration of intermittent renewables like solar and wind into existing energy provider infrastructure in the U.S. AI is facilitating precise energy generation forecasting, which translates into efficient energy use. Programs like “VoltAlc Initiative” are majorly supported by the U.S. DOE and actively get funds for R&D further.

Why is the Asia Pacific AI-based Energy Forecasting Services Market Growing Rapidly?

Asia Pacific is expected to witness the fastest CAGR of nearly 22% during the foreseeable period of 2025-2034. The region is expanding due to the increasing population and energy demand from various industries, aggressive renewable energy targets, rapid urbanization, and government-backed policies for smart grids development across the region. Leading countries like China, Japan, and India are introducing various policies like PM Surya Ghar by India, Society 5.0 by Japan, further accelerating the market's growth.

China AI-Based Energy Forecasting Services Market Trends

The region is growing due to the strategic push towards energy security, large-scale integration of renewable energy sources, strong governmental support, and huge funding for the energy sector and strategic plans to lead AI services globally. China is seen as a global leader in the manufacturing and deployment of solar and wind energy.

What are the Growth Factors in Promoting Europe's Market?

The Europe AI-based energy forecasting services market is rapidly expanding due to the proactive approach to AI regulations, with initiatives like the AI Act that mandate stringent compliance for high-energy applications in the energy sector. Also, the ambitious plan of Europe, named ‘Green Deal Industrial Plan', is expanding the markets to reach a maximum level.

Germany AI-Based Energy Forecasting Services Market Trends

Germany is hugely contributing to the AI-based energy forecasting services market growth due to an aggressive target of 80% renewable electricity by 2030 and the climate neutrality aim by 2045. Germany is a leader in research centers like the German Research Center for AI, which conducts various projects to develop reliable AI models.

Middle East & Africa

The Middle East & Africa region is notably growing in the market due to the national vision about AI and its applications are core strategies of their national interests, along with massive renewable energy projects such as Mohammad bin Rashid AI Maktoum Solar Park in the UAE and projects like NEOM megacity in Saudi Arabia, highlighting their prominent efforts to achieve 100% AI-powered renewable energy sector.

Saudi Arabia AI-based Energy Forecasting Services Market Trends

The country is a major contributor in the Middle East & Africa AI-based energy forecasting services market due to the nation's aim to diversify the economy from conventional oil export businesses only and transform it into technology-based trading. Hence, the government has largely invested in AI development through SDAIA and Public investment funds.

Who are the Major Players in the AI-Based Energy Forecasting Services Market?

The major players in the ai based energy forecasting services market include Siemens AG, General Electric Company, Schneider Electric SE, IBM Corporation, ABB Ltd, Honeywell International Inc., Hitachi Energy, Microsoft Corporation, Amazon Web Services (AWS), and C3.ai.

Recent Developments in the Market

• In November 2025, ELRDC, GRID-INDIA, and IIT Delhi collaborated on AI-powered smart home energy management systems. The collaboration aims to optimize electricity use, improve grid stability, and drive digital growth in India. (Source:https://indianmasterminds.com)
• In November 2025, Hitachi Energy introduced ‘Nostradamus', which is an AI energy forecasting software solution built by leveraging modern ML for unmatched precision of energy forecasting from anywhere. (Source:https://www.hitachienergy.com)

Segments Covered in the Report

By Service Type

• Forecasting-as-a-Service (FaaS) / API delivery
• Custom Model Development & Integration
• Managed Forecasting & Monitoring Services (SLAs)
• Scenario & Market Simulation Services
• Model Validation & Audit Services

By Modeling Technology

• Machine Learning/Deep Learning (LSTM, Transformer, XGBoost)
• Hybrid Physics-Informed + ML Models
• Probabilistic & Ensemble Forecasting
• Time-Series/Statistical Models (ARIMA family)
• Transfer Learning & Federated Learning Approaches

By Deployment & Delivery Mode

• Cloud/SaaS APIs & Portals
• Managed Cloud + Expert Support (outsourced ops)
• On-Premises / Edge Inference (substation/plant)
• Hybrid (cloud training + edge inference)

By Data Inputs Utilized

• Smart Meter/AMI Time Series
• Weather & Satellite Data (solar irradiance, wind speed)
• SCADA / Telemetry & SCADA Streams
• Market & Transactional Data (prices, bids)
• IoT/ EV/Building Energy Management Data

By End-User

• Transmission & Distribution System Operators (TSOs/DSOs)
• Vertically Integrated Utilities & Retail Suppliers
• Renewable IPPs & Asset Managers (wind/solar/battery fleets)
• Energy Traders & Retail Energy Suppliers
• Aggregators/VPP Operators/DER Providers
• Large C&I Energy Buyers & Data-Center Operators

By Region

• North America
• Europe
• Asia-Pacific
• Latin America
• Middle East & Africa