Artificial Intelligence in Energy Market Size, Share, Industry, Forecast and outlook (2024-2031)

Global Artificial Intelligence in Energy Market is segmented By Solution (Software Solutions, Hardware Solutions, Services), By Application (Load Research and forecasting, Optimization, Transmission & distribution), and By Region (North America, Latin America, Europe, Asia Pacific, Middle East, and Africa) – Share, Size, Outlook, and Opportunity Analysis, 2024-2031.

Artificial Intelligence in Energy Market Outlook

A report by DataM Intelligence estimates the Global Artificial Intelligence in Energy market to grow at a high CAGR during the forecast period 2024-2031. The Global AI in Energy Market is thriving as energy companies seek data integration and visual analytics to gain valuable business insights from their vast data reserves.. The competitive rivalry intensifies with ABB, IBM., Siemens, and others operating in the market.

Artificial Intelligence is being used in the energy sector for stabilizing power grids by creating an ‘autonomous grid’ that is programmed with past fluctuations and weak points on the grid. Such an autonomous grid would be able to respond to power fluctuations on its own seamlessly.

Artificial Intelligence in Energy Market Summary

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Artificial Intelligence in Energy Market Growth Trends

The Global Artificial Intelligence in Energy Market is predominantly driven by the increasing demand of data integration and visual analytics by energy companies for getting relevant and useful business insights from their huge repository of data. Another factor driving the growth of AI in the energy sector is the growing need to decrease uncertainty mainly in the renewable energy sector, which is touted to be the future of energy supply management.

Industries have resorted to automation of repetitive and risky tasks to cut costs and decrease human errors in the production process. However, this has led end-users to search for solutions to address the limitations of industrial automation and robotics technologies. These limitations arise due to factors such as cost, computational capacity, storage, size, power supply, motion mode, and working environment. Therefore, the need to enhance existing systems using AI has also resulted in an increase in the demand for cloud-based Artificial Intelligence solutions.

Energy companies require Artificial Intelligence platforms to link multiple enterprise systems with the internet and other cloud-based applications to facilitate real-time information exchange, given that globalization has led to customers, suppliers, and companies being scattered across the world. There has been an increased demand for bringing in AI in the energy sector primarily as it needs low and substantial seed investment and a low level of risk of failure.

Artificial Intelligence allows real-time synthesizing of data to facilitate stat analysis which leads to an efficient decision-making system. The increased levels of complexity have also made deployment of the data processing interface difficult, leading to an increase in demand for data integration solutions. The exponential rate of increase in the volume of data that needs to be processed played a major role in increasing the demand for Artificial Intelligence in data processing as meaningful insights are the need for energy companies.

Lack of availability of skilled staff ready to cope with the change in software/hardware services is hindering the penetrability of AI in the energy sector until the clients have employees who can deal with the disruption in the status quo caused due to incorporating AI.

Artificial Intelligence in Energy Market Segmentation Analysis

By solution, the Global Artificial Intelligence in Energy Market solution is segmented into software, hardware, and services. Services sector is further sub-segmented to support & maintenance, and consulting services. Software solutions for artificial intelligence processing interfaces are the leading sector in the Energy AI market and are mainly used by power companies to predict and manage fluctuations based on past data. Demand is expected to surge in this segment as there is a substantial need from power supply companies to predict fluctuations such as surges and dips in power requirements of consumers so as to give them a viable estimate to producers beforehand.

By application, the Global Artificial Intelligence in Energy Market is segmented into Load Research & Forecasting, Optimization, and Transmission & Distribution. Load research & forecasting sector is anticipated to have strong growth in the coming years, due to increasing need for analyzing energy demand and load requirements. Forecasting also refers to clients using AI to predict when their systems might fail, so that they can opt for necessary precautionary measures. 

Artificial Intelligence in Energy Market Geographical Share

A major portion of the Global Artificial Intelligence in Energy Market Share is predicted to be concentrated in North America, despite the fact that the Global Artificial Intelligence Market as a whole is forecasted to be centered in the APAC region. One of the major reasons is the increased spending by big tech companies on developing Artificial Intelligence for applications in distinct fields. For example, Enlighted (a company based in USA), which works in this sector has already received over USD 80 Million in funding from investors.

Artificial Intelligence in Energy Market Key players

The Global Artificial Intelligence in Energy Market is a concentrated market, with the key players holding most of the market share, and the others having a minute market share globally. 

Key players in the industry are focusing on security issues that arise in AI. For instance, IBM has dedicated resources to develop a secure, autonomous grid to defend it from malicious cyber-attacks, a problem with serious consequences in today’s world. 

Major players are ABB, Alphabet, General Electric, IBM, Siemens, Schneider Electric, BuildingIQ, Enlighted, Grid4C, Watty, and among others.

Alphabet has made huge strides in this field, by developing a revolutionary technology that has the ability to predict power supply output 36 hours before the actual generation, ensuring that its clients can give a confident estimate of power supply to consumers. This reduces the inherent uncertainty in the wind power industry.

General Electric has started catering to AI market consisting of energy companies that requires market insights to analyze predictive patterns to augment energy savings through Big Data analytics. 

Building IQ on the other hand is focusing on large building complexes to provide predictive solutions for energy optimization using Artificial Intelligence. It takes into account factors such as thermodynamic information of a building, weather forecast in the region, and so on.

Key Takeaways

• Given that the market as a whole is still in its nascent stages, companies providing AI solutions to clients in the energy industry have a huge opportunity to capitalize on this boom in demand.
• The energy sector as a whole is undergoing a rapid transformation in making each component in the supply chain smart.
• Over the next several years, AI is expected to boost efficiencies across the renewable energy sector by automating operations in the solar and wind industries.
• The AI in energy sector is also bound to benefit from the fact that there is a shift of preferences of consumers from machines that decrease production time to machines that learn while doing the same.
• North America has emerged as the leading region with the highest market share. This might be due to the presence of major tech companies, which form the Silicon Valley in the US. 
• Companies that invest in AI ventures are bound to witness an upsurge in revenue generated.