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AI in Energy Management Market By Deployment Type (Cloud, On-premise), By Solution (Renewable Management, Demand Management, Infrastructure Management), By Technology (Machine Learning, Natural Language Processing, Computer Vision), By Application (Energy Generation, Energy Transmission, Energy Distribution, Energy Output Forecasting), By End-user (Manufacturing, Utility, Residential, Government, Retail, Healthcare, Education) - Growth, Share, Opportunities & Competitive Analysis, 2019 – 2027

Rising energy production and consumption worldwide will boost the market growth.

The global AI in the energy management market is growing tremendously, projected to expand at a CAGR of 21.2% throughout the projected period from 2019 to 2027, starting from US$ 5.10 Bn in 2018. 

The global AI in the energy management market is majorly driven by the growing energy production & consumption worldwide, along with leveraging artificial intelligence (AI) to improve grid stability and the growing need for smart energy management solutions. In 2018, the global primary energy consumption was 1 57,063.77 TWh raised 2.4% from 1, 53,347.15 TWh in 2017. Moreover, India, China, and the U.S. together accounted for over 2/3rd of the worldwide increase in energy demand. In addition, the surge in the use of renewable energy sources is another factor driving the growth of the market. In addition, the introduction of cloud-based software to improve service operations, deliver real-time insights, and easy product development are other major factors expected to enhance the market demand over the forecast period. 

The integration of IoT (internet of things) to monitor utility & energy data in energy management systems is another major factor expected to drive market growth over the forecast period. The global energy management systems market was valued at around US$ 39.0 Bn in 2018 and is anticipated to expand with a CAGR of nearly 19% over the forecast period. Market players focus on strategic collaborations to launch advanced AI-based energy management systems. For instance, in November 2019, ABB Ltd. partnered with Verdigris Technologies to revolutionize energy management through artificial intelligence (AI) solutions. As a result, they launched two AI-powered applications in the ABB Ability EDCS (Electrical Distribution Control System), Energy Forecasting and Intelligent Alerts. The intelligent Alerts app will help consumers to identify underlying issues and better manage their assets. The Energy Forecasting app will help in reducing electricity bills through tumbling peak demand charges. 

Market Synopsis

Application Analysis

Growing need for effective energy management services to spur the segment growth

The energy output forecasting segment dominated the global market in 2018. The segment had the highest share due to a surge in the need for effective energy management services coupled with growing energy consumption worldwide. Artificial intelligence (AI) solutions help utilize data through machine learning techniques and statistical algorithms, which help provide better services to consumers.  

Surge in demand to manage energy output globally to spur the segment growth.

The energy generation segment is anticipated to expand with the highest CAGR over the forecast period owing to the growing demand to manage the total energy output from different sources such as wind power stations, solar power plants, thermal plants, and others. In addition, the need to match temporal and spatial variations in real time is another factor for segment growth.

Regional Analysis

The rise in the integration of AI in the energy industry to enhance North America growth

In 2018, North America was dominant in the global AI in the energy management market. The region accounted for around 33% of the world market share in the same year. North America was dominant in 2018 due to the rise in the integration of artificial intelligence in the energy industry, along with early technological adoption and the presence of major market players in the region, such as IBM Corporation, Honeywell International, Inc., General Electric Company, and others. The U.S. had the highest share in the North America AI in energy management market in 2018, contributing to more than 82% market share in the same year. The U.S. had a major share due to a surge in government investment coupled with the growing demand for energy. According to a report, U.S. consumption has been expanding at its fastest rate for the last 30 years.  

Key Industry Developments: 

  • In July 2019, Microsoft Corporation and Schneider Electric SE collaborated to launch an artificial intelligence (AI) accelerator program for green energy in the Microsoft Corporation AI factory in Europe. The program will help start-ups transform the region's energy sector by increasing energy efficiency and decreasing consumption.
  • In May 2019, Schneider Electric SE acquired a stake in AutoGrid. With the stake acquisition in AutoGrid, Schneider Electric SE establishes a co-innovation partnership. The co-innovation partnership will focus on driving machine learning and artificial intelligence (AI) solutions for the energy industry.
  • In February 2020, Eaton Corporation PLC acquired Power Distribution, Inc. With the acquisition of Power Distribution, Inc., Eaton Corporation PLC is anticipated to expand its data center power monitoring and distribution solutions.
  • In October 2019, Siemens AG announced the separation of its energy business into a new company called Siemens Energy. Siemens Energy is expected to become a separate entity in April 2020. The new company will work on the reduction of CO2 emissions and will introduce new trends in the energy industry with the help of artificial intelligence (AI). 

List of Companies Covered:

  • IBM Corporation
  • Eaton Corporation PLC
  • General Electric Company
  • ABB Ltd.
  • Siemens AG
  • Honeywell International Inc.
  • Schneider Electric SE
  • Xcel Energy Inc.
  • Rockwell Automation
  • Wipro Limited
  • Microsoft Corporation 

Historical & Forecast Period

This study report represents an analysis of each segment from 2017 to 2027, considering 2018 to be the base year. Compounded Annual Growth Rate (CAGR) for each of the respective segments estimated for the forecast period from 2019 to 2027.Segmentation

 Deployment Type (2017–2027; US$ Bn)

  • Cloud
  • On-premise

 Solution (2017–2027; US$ Bn)

  • Renewable Management
  • Demand Management
  • Infrastructure Management

 Technology (2017–2027; US$ Bn)

  • Machine Learning
  • Natural Language Processing
  • Computer Vision

 Application (2017–2027; US$ Bn)

  • Energy Generation
  • Energy Transmission
  • Energy Distribution
  • Energy Output Forecasting

 End-user (2017–2027; US$ Bn)

  • Manufacturing
  • Utility
  • Residential
  • Government
  • Retail
  • Healthcare
  • Education

 Geography Segment (2017–2027; US$ Mn)

  • North America (U.S. and Canada)
  • Europe (U.K., Germany, France, Spain, Italy, and the Rest of Europe)
  • Asia Pacific (Japan, China, India, and the Rest of Asia Pacific)
  • Rest of the World (Middle East & Africa (MEA), Latin America)

The current report also comprehends qualitative and qualitative market valuation factors such as key market drivers, market trends, restraints, and opportunities to better understand the overall AI in the energy management market. In addition, the global report also represents the competitive landscape based on market initiatives and strategies, product portfolio, and business strengths.

Frequently Asked Question:

The market for AI in Energy Management Market is expected to reach USD$ XX Mn in 2027.

The AI in Energy Management Market is expected to see significant CAGR growth over the coming years, at 21.2%.

The report is forecasted from 2019 -2027.

The base year of this report is 2018.

IBM Corporation,Eaton Corporation PLC,General Electric Company,ABB Ltd.,Siemens AG,Honeywell International Inc.,Schneider Electric SE,Xcel Energy Inc.. are some of the major players in the global market.

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Published Date:  Mar 2020
Category:  IT & Telecom
Report ID:   60223
Report Format:   PDF
Pages:   120
Rating:    4.4 (58)
Delivery Time: 24 Hours to 48 Hours   
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