Global AI in Renewable Energy Market Size, Share & Trends Analysis Report, Forecast Period, 2024-2031

The AI in Renewable Energy market is experiencing robust expansion, with market size projected to increase from XX billion in 2024 to xx billion by 2031, demonstrating a consistent year-over-year growth rate of 27.89%. AI in Renewable Energy Market Size, Share, Competitive Landscape and Trend Analysis Report, , by applications (Robotics, Renewables Management, Demand Forecasting, Safety and Security, Infrastructure) And regions (North America(United States.Canada.Mexico), South America(Brazil.Argentina.Chile.Rest of South America), Europe(Germany.France.Italy.United Kingdom.Benelux.Nordics.Rest of Europe), Asia Pacific(China.Japan.India.South Korea.Australia.Southeast Asia.Rest of Asia-Pacific), MEA(Middle East.Africa)) : Industry Forecast and Opportunity Analysis for 2024 - 2031

The market for AI in renewable energy on a global scale includes the implementation of artificial intelligence solutions into the improvement of the operating capabilities of renewable energy systems. AI-assisted decision-making can utilize process data from a variety of sources, including but not limited to weather reports, sensors, and patterns of energy use. There are numerous driving forces concerning the global AI renewable energy market. These include increasing trends in the use of renewable energy sources, the demand for more effective energy management systems, and the need to reduce carbon emissions. Again, it is possible to make AI-based approaches to renewable energy systems better and even turn out cost-efficient.

AI in Renewable Energy Report Highlights

Report Metrics	Details
Forecast period	2019-2031
Base Year Of Estimation	2023
Growth Rate	CAGR of 27.89%
Forecast Value (2031)	USD 44.34 Billion
Key Market Players	ATOS SE SmartCloud Inc. Zen Robotics Ltd. Origami Energy Ltd. Alpiq General Electric Siemens AG Hazama Ando Corporation AppOrchid Inc. Flex Ltd
By Region	North America(United States.Canada.Mexico) South America(Brazil.Argentina.Chile.Rest of South America) Europe(Germany.France.Italy.United Kingdom.Benelux.Nordics.Rest of Europe) Asia Pacific(China.Japan.India.South Korea.Australia.Southeast Asia.Rest of Asia-Pacific) MEA(Middle East.Africa)

AI in Renewable Energy Market Trends

The worldwide AI-renewables market is rapidly increasing owing to the need for better energy management and efficiency techniques. Advanced technologies such as predictive analytics and deep learning have been applied in facilitating the operational efficiencies of renewable energy systems, including solar, wind, and hydel. These applications of AI also contribute to energy generation forecasting, grid management enhancement, and energy storage optimization. The incorporation of real-time data by the AI reduces waste through better management of energy mixes in the grid, thus promoting a continuous and efficient flow of low-carbon energy. There is also the promotion of carbon reduction and carbon-free energy systems, which Favors the introduction of approaches employing artificial intelligence in the enhancement of renewable energy systems. Another important trend is the rising investment into AI applications for predictive maintenance and automation of processes related to commercial renewable energy operations. More companies are resorting to artificial intelligence systems to enable them to prevent or foresee equipment failures, such as those that come with wind turbines or solar panels or any other renewable asset, so that regular maintenance does not occur in a drop in productivity. In addition to this, AI also facilitates the distribution of energy within microgrid systems and smart grids, thereby allowing for energy utilization that is demand responsive.

AI in Renewable Energy Market Leading Players

The key players profiled in the report are ATOS SE, SmartCloud Inc., Zen Robotics Ltd., Origami Energy Ltd., Alpiq, General Electric, Siemens AG, Hazama Ando Corporation, AppOrchid Inc., Flex Ltd

Growth Accelerators

The major factor responsible for the growth of the global AI in renewable energy market is the growing need for energy-efficient and ecologically clean energy sources. AI is a key enabling technology in the generation, storage, and distribution of renewable energy as states and institutions everywhere seek to achieve carbon neutrality and use cleaner energy sources. AI solutions facilitate predictive maintenance, support grid management, and optimize energy usage, thus improving renewable systems like solar, wind, and hydropower. This helps to minimize the operational expenditures and boost the reliability of the renewable sources of energy, making them on par with the traditional types of energy. The other key market factors are technological expansion, particularly regarding the application of AI techniques, and the interconnection with renewable energy systems. All this is due to the AI implemented in improved energy production forecasting, including the use of weather prediction and information to improve on solar and wind farm energy outtakes. It is further changing the dynamics of electric grid operations, as effectively applied forecasting techniques through the use of machine learning and big data analytics enhance energy demand prediction for better deployment of renewables into national and regional grids.

AI in Renewable Energy Market Segmentation analysis

The Global AI in Renewable Energy is segmented by Application, and Region.
. The Application segment categorizes the market based on its usage such as Robotics, Renewables Management, Demand Forecasting, Safety and Security, Infrastructure. Geographically, the market is assessed across key Regions like North America(United States.Canada.Mexico), South America(Brazil.Argentina.Chile.Rest of South America), Europe(Germany.France.Italy.United Kingdom.Benelux.Nordics.Rest of Europe), Asia Pacific(China.Japan.India.South Korea.Australia.Southeast Asia.Rest of Asia-Pacific), MEA(Middle East.Africa) and others, each presenting distinct growth opportunities and challenges influenced by the regions.

Competitive Landscape

The global market for AI and renewable energy has a significant presence of established firms in various sectors, energy suppliers, and even start-up companies. Companies like Google, IBM, and Microsoft, which are tech behemoths in their own right, have made it possible to use artificial intelligence in managing energy control, stabilizing the grid, and projecting the weather for wind farms. Such companies have merged AI with renewable energy sources, including wind, solar, and hydroelectric power, in order to enhance efficiency, cut costs, and boost (up)clean energy solutions. In addition to that, firms in the renewable energy sector, such as NextEra Energy and Ørsted, are equally implementing AI systems to enhance operational efficiencies and increase the sharing of renewable energy with the grid over which they operate, mastering business in urban centers.

Challenges In AI in Renewable Energy Market

The integration of AI into renewable energy stands, however, to several challenges, especially the prohibitive cost of the initial setup. Most renewable energy companies, particularly in underdeveloped countries, do not have enough budgets to implement AI solutions mainly due to the high cost of infrastructure, data procurement, and system integration. Moreover, this geography of the challenges encompasses the one relating to data quality and availability. For instance, in renewable energy, AI systems require large amounts of data collected from different information sources, such as weather data, energy consumption, and grid data. The success of AI algorithms may be hampered by imprecise, partial, or contradictory data, which can result in failures. The concerns for data safety, cybersecurity, and energy laws and regulations also create barriers for the adoption of AI systems in the energy industry in a major way. A major challenge still is creating amenable systems allowing for adherence to best practices without compromising the safety and integrity of data systems.

Risks & Prospects in AI in Renewable Energy Market

The global AI in renewable energy market opens up great promise in the sectors of energy production, distribution, and consumption. With the help of massive amounts of information, data-driven solutions can improve the effectiveness of renewable energy such as wind, solar, and hydropower by managing the systems in real time. Among other things, this includes system process control optimizations for wind farms and photovoltaic systems, forecasting the energy generations, and operating the electric grids. AI technologies will also allow carrying out predictive maintenance, which will minimize the outage time and operating expenses of the renewable energy facilities, thus making better business sense for the adoption of renewable energy resources over time. In addition, the use of AI has enabled energy management systems, including storage and demand response, thus creating mechanisms for the impact of uneven renewable energy supply on demand. Algorithms based on AI can help to predict the level of energy consumption, operation of energy storage systems, and the redistribution of energies so that power supply is assured all the time. Given the sustainability issues and carbon emission concerns that many countries and corporates are striving to adhere to, the function of AI in enhancing the expandability and dependability of green energy systems will persist in its upward growth and hence, catalyze more funding and new ventures in the renewable energy industry.

Key Target Audience

One of the core target groups within the global AI in renewable energy business includes energy providers and utilities who use AI technologies to enhance the generation, transmission, and use of renewable energy. These players, including solar and wind energy businesses, implement AI to forecast energy output, optimize grid networks, and improve energy systems. These and other organizations use smart technologies to cushion against the variability of renewable energy sources as well as interconnect multiple sources of energy for efficient and environmentally friendly operations, which in turn reduces costs as well as enhances the uptake of renewable energy.,, Another key audience consists of governments, policy makers, and environmental stakeholders who seek to promote the use of clean energy technologies. The trend shows that economic powers are now turning to AI in a bid to achieve their renewable energy goals and reduce their carbon emissions as well as assist in the energy transformation process. AI is also of great interest to corporate and industrial end users interested in the power management and energy savings for the operations of smart systems.

Merger and acquisition

The global AI in renewable energy market is experiencing a remarkable activity of mergers and acquisitions, which aims at increasing the use of artificial intelligence in optimizing energy generation processes while still maintaining sustainable economics. One of the recently concluded deals was IBM’s acquisition of Prescinto, a company focused on providing asset performance management (APM) software services for the renewable energy market. This acquisition, announced in December 2023, is set to integrate Prescinto’s AI-enhanced offerings into IBM’s Maximo Application Suite to improve the monitoring and control of the performance of solar and wind assets. With the technology from Prescinto, real-time analytics and predictive maintenance will be incorporated, which are key in achieving operational efficiency for renewables in most of the markets across the world. Besides, along with IBM’s acquisition, other protective behaviors displayed by other big companies also include renewable energy sector investments aimed at achieving their sustainability agenda. For example, Microsoft’s notable new obligations in renewable energy include already executing an agreement with Brookfield Asset Management for the delivery of 10.5 gigawatts of renewable energy, which will be used to power the company’s data centers around the world over time. Well, this also reinforces the trend of corporate mergers where energy technologies involving AI and renewable energy are being used to counter the increasing energy consumption without breaching environmental parameters.