Global AI in energy Market By industry (oil and gas{upstream,mid-stream and downstream} & power industry {generation, transmission and distribution}); By solution type (software, hardware and AI-as-a-solution); and Region –Analysis of Market Size, Share & Trends for 2016 – 2019 and Forecasts to 2029
Product overview
AI in the energy market uses slacks of data and advance algorithm from the source and provide the machine the ability to calculate, think and react to the provided information just like a human brain. By applying Artificial intelligence in the energy market it provides real-time insights into the industrial application, thereby meeting the demand for the energy market by increasing the efficiency of the system.
Electricity trade, smart grids, or the electricity, heat, and transport sector connection are typical application areas. Analyzing and assessing data volumes, AI helps the energy industry to be more efficient and secure.
Market Highlights
anticipates the AI in the energy market to surpass USD XX Billion by 2030, this is valued at XX billion in 2019 at a compound annual growth rate of XX%. The growth of global AI in the energy market is expected to be driven by the demand for improved operating efficiency, rising energy efficiency issues. Decentralized power producers are increasingly concerned about rising energy demand in the power distribution supply chain. An increase in the problem for the battery storage systems, leading to congestion and difficulty within the grid, may likely encourage the market’s growth. The digitalization of the energy market and a correspondingly wide variety of data that can be analyzed are the conditions for the expanded use of AI in the energy system.
Source: Fatpos Global
Recent Highlights in the AI in the energy market
In November 2019, Baker Hughes, C3.ai, and Microsoft announced their partnership to allow customers to implement Microsoft Azure-based, scalable AI solutions.
GE Power is working on incorporating AI to enhance its energy supply chain, which generates 30 percent of the world’s electricity. Through the aid of AI and machine learning (ML), GE aims to boost its business operations.
In January 2019, a cloud-based AI platform with real-time analytics for oil & gas industrial applications was launched by Kellton Tech Solutions Ltd.
AI in the energy market: Segments
The global AI in the energy market has been segmented on the basis of industry stream, product offering, and application. It has been further segmented on the basis of region into North America, Europe, Asia-Pacific, Mid East, and Africa.
On the basis of industry (in %), global AI in the energy market,2019
In 2019, the oil and gas industry dominated the market and accounted for XX% of the global market
The global AI in the energy market is segmented by solution type: Software, hardware, and AI- as-a-service.
Due to technological advances in the provision of customized application-specific cloud platforms and enhanced operating systems, the AI segment is expected to show its highest growth, which is expected to further contribute to strengthening end-user data storage architecture.
By industry (in %), global AI in energy market, 2019
Source: Fatpos Global
By solution type (in %), global AI in energy market, 2019
In 2019 the software, solution accounted for more than 60% of the total artificial intelligence in the energy market
The global AI in the energy market is segmented by solution type: Software, hardware, and AI- as-a-service.
Due to technological advances in the provision of customized application-specific cloud platforms and enhanced operating systems, the AI segment is expected to show its highest growth, which is expected to further contribute to strengthening end-user data storage architecture.
Global AI in energy market: Drivers and Restraints
Drivers
Collaborative Policies adopted by many companies
The competitive landscape in the energy market for AI shows a tendency towards companies that adopt strategies such as partnerships, cooperation, and joint ventures as well as launching and developing their products. With the growing global market growth, companies in this sector are being forced to develop collaborative policies to sustain themselves in the highly competitive market.
Efficient energy storage
AI in the industrial sector can prove to be beneficial to optimize energy storage efficiency. The production of energy is frequent and sometimes chaotic, and the storage of renewable energy is quite problematic. The combination of renewable energy with AI storage can make energy storage management much simpler, enhance business value and reduce the loss of electricity.
Restraints
Lack of Knowledge
One reason for the slow adoption of AI in the energy sector is a lack of necessary knowledge about AI technology among decision-makers. Many companies simply don’t have sufficient technical background to understand how their business can benefit from AI adoption. Conservative stakeholders prefer to stick with time-proven methods and tools rather than risk trying something new.
Fewer number trained professionals
AI is still a new technology, and skilled professionals are few. There are many experts with a thorough theoretical insight into the topic. Yet it is incredibly difficult to find professionals who are able to develop reliable, functional AI applications.
AI in the energy market: Key Players
IBM Corporation
Company Overview
Business Strategy
Key Product Offerings
Financial Performance
Key Performance Indicators
Risk Analysis
Recent Development
Regional Presence
SWOT Analysis
SAP SE
Microsoft Corporation
Huawei Technologies
HCL Technologies
Accenture Plc
Schneider Electric
Honeywell International
Rockwell Automation
Schlumberger Limited
Other Prominent Players
Global AI in Energy Market: Regions
The largest share of the market in 2019 was held by America which accounting for over 49% share in the world.
Asia Pacific region despite having the lowest market share is anticipated to grow at the highest CAGR during the forecast period.
Source: Fatpos Global
The global AI in energy market is further segmented by region into:
North America Market Size, Share, Trends, Opportunities, Y-o-Y
Growth, CAGR – United States and Canada
Latin America Market Size, Share, Trends, Opportunities, Y-o-Y
Growth, CAGR – Mexico, Argentina, Brazil, and Rest of Latin America
Europe Market Size, Share, Trends, Opportunities, Y-o-Y Growth,
CAGR – United Kingdom, France, Germany, Italy, Spain, Belgium,
Hungary, Luxembourg, Netherlands, Poland, NORDIC, Russia,
Turkey and Rest of Europe
APAC Market Size, Share, Trends, Opportunities, Y-o-Y Growth,
CAGR – India, China, South Korea, Japan, Malaysia, Indonesia, New
Zealand, Australia, and Rest of APAC
MENA Market Size, Share, Trends, Opportunities, Y-o-Y Growth,
CAGR – North Africa, Israel, GCC, South Africa
Global Optical Coatings Market: Impact of COVID-19
The global pandemic COVID-19 has become global stress, not just for human lives, but also to industries across different industry verticals. The COVID-19 disease has infected several million people globally, with United States accounting for the highest share of infected cases. With increasing number of active cases on a daily basis, the duration of the pandemic is still difficult to predict. Yet the adverse effect of COVID-19 can be felt upon the Energy market leading to a fluctuation in demand for artificial intelligence in the energy market, the effect on manufacturing organizations due to the implementation of lockdown norms in many nations worldwide, and others. Difficulty in-migration of workers and the constant returns of workers to their homelands is becoming a constant obstacle in the growth path of the industry.
The global AI in energy market report also contains analysis on:
AI in energy market Segments:
By industry stream:
Oil and gas
Upstream
Mid-stream
Downstream
Power industry
Transmission
Generation
distribution
By solution type:
Software
Hardware
AI-as-a-solution
AI in energy market Dynamics
AI in energy market Size
Supply & Demand
Current Trends/Issues/Challenges
Competition & Companies Involved in the Market
Value Chain of the Market
Market Drivers and Restraints
FAQs on Global AI in energy market
Which segment is anticipated to hold the largest market share?
At what CAGR is the market anticipated to grow between 2020 and
Who are the key players in the global AI in the energy market?
What could be the challenging factors for the growth of AI in the energy market?
What are the growth drivers for AI in the energy market?
AI in the energy market uses slacks of data and advance algorithm from the source and provide the machine the ability to calculate, think and react to the provided information just like a human brain. By applying Artificial intelligence in the energy market it provides real-time insights into the industrial application, thereby meeting the demand for the energy market by increasing the efficiency of the system.
Electricity trade, smart grids, or the electricity, heat, and transport sector connection are typical application areas. Analyzing and assessing data volumes, AI helps the energy industry to be more efficient and secure.
Market Highlights
anticipates the AI in the energy market to surpass USD XX Billion by 2030, this is valued at XX billion in 2019 at a compound annual growth rate of XX%. The growth of global AI in the energy market is expected to be driven by the demand for improved operating efficiency, rising energy efficiency issues. Decentralized power producers are increasingly concerned about rising energy demand in the power distribution supply chain. An increase in the problem for the battery storage systems, leading to congestion and difficulty within the grid, may likely encourage the market’s growth. The digitalization of the energy market and a correspondingly wide variety of data that can be analyzed are the conditions for the expanded use of AI in the energy system.
Source: Fatpos Global
Recent Highlights in the AI in the energy market
In November 2019, Baker Hughes, C3.ai, and Microsoft announced their partnership to allow customers to implement Microsoft Azure-based, scalable AI solutions.
GE Power is working on incorporating AI to enhance its energy supply chain, which generates 30 percent of the world’s electricity. Through the aid of AI and machine learning (ML), GE aims to boost its business operations.
In January 2019, a cloud-based AI platform with real-time analytics for oil & gas industrial applications was launched by Kellton Tech Solutions Ltd.
AI in the energy market: Segments
The global AI in the energy market has been segmented on the basis of industry stream, product offering, and application. It has been further segmented on the basis of region into North America, Europe, Asia-Pacific, Mid East, and Africa.
On the basis of industry (in %), global AI in the energy market,2019
In 2019, the oil and gas industry dominated the market and accounted for XX% of the global market
The global AI in the energy market is segmented by solution type: Software, hardware, and AI- as-a-service.
Due to technological advances in the provision of customized application-specific cloud platforms and enhanced operating systems, the AI segment is expected to show its highest growth, which is expected to further contribute to strengthening end-user data storage architecture.
By industry (in %), global AI in energy market, 2019
Source: Fatpos Global
By solution type (in %), global AI in energy market, 2019
In 2019 the software, solution accounted for more than 60% of the total artificial intelligence in the energy market
The global AI in the energy market is segmented by solution type: Software, hardware, and AI- as-a-service.
Due to technological advances in the provision of customized application-specific cloud platforms and enhanced operating systems, the AI segment is expected to show its highest growth, which is expected to further contribute to strengthening end-user data storage architecture.
Global AI in energy market: Drivers and Restraints
Drivers
Collaborative Policies adopted by many companies
The competitive landscape in the energy market for AI shows a tendency towards companies that adopt strategies such as partnerships, cooperation, and joint ventures as well as launching and developing their products. With the growing global market growth, companies in this sector are being forced to develop collaborative policies to sustain themselves in the highly competitive market.
Efficient energy storage
AI in the industrial sector can prove to be beneficial to optimize energy storage efficiency. The production of energy is frequent and sometimes chaotic, and the storage of renewable energy is quite problematic. The combination of renewable energy with AI storage can make energy storage management much simpler, enhance business value and reduce the loss of electricity.
Restraints
Lack of Knowledge
One reason for the slow adoption of AI in the energy sector is a lack of necessary knowledge about AI technology among decision-makers. Many companies simply don’t have sufficient technical background to understand how their business can benefit from AI adoption. Conservative stakeholders prefer to stick with time-proven methods and tools rather than risk trying something new.
Fewer number trained professionals
AI is still a new technology, and skilled professionals are few. There are many experts with a thorough theoretical insight into the topic. Yet it is incredibly difficult to find professionals who are able to develop reliable, functional AI applications.
AI in the energy market: Key Players
IBM Corporation
Company Overview
Business Strategy
Key Product Offerings
Financial Performance
Key Performance Indicators
Risk Analysis
Recent Development
Regional Presence
SWOT Analysis
SAP SE
Microsoft Corporation
Huawei Technologies
HCL Technologies
Accenture Plc
Schneider Electric
Honeywell International
Rockwell Automation
Schlumberger Limited
Other Prominent Players
Global AI in Energy Market: Regions
The largest share of the market in 2019 was held by America which accounting for over 49% share in the world.
Asia Pacific region despite having the lowest market share is anticipated to grow at the highest CAGR during the forecast period.
Source: Fatpos Global
The global AI in energy market is further segmented by region into:
North America Market Size, Share, Trends, Opportunities, Y-o-Y
Growth, CAGR – United States and Canada
Latin America Market Size, Share, Trends, Opportunities, Y-o-Y
Growth, CAGR – Mexico, Argentina, Brazil, and Rest of Latin America
Europe Market Size, Share, Trends, Opportunities, Y-o-Y Growth,
CAGR – United Kingdom, France, Germany, Italy, Spain, Belgium,
Hungary, Luxembourg, Netherlands, Poland, NORDIC, Russia,
Turkey and Rest of Europe
APAC Market Size, Share, Trends, Opportunities, Y-o-Y Growth,
CAGR – India, China, South Korea, Japan, Malaysia, Indonesia, New
Zealand, Australia, and Rest of APAC
MENA Market Size, Share, Trends, Opportunities, Y-o-Y Growth,
CAGR – North Africa, Israel, GCC, South Africa
Global Optical Coatings Market: Impact of COVID-19
The global pandemic COVID-19 has become global stress, not just for human lives, but also to industries across different industry verticals. The COVID-19 disease has infected several million people globally, with United States accounting for the highest share of infected cases. With increasing number of active cases on a daily basis, the duration of the pandemic is still difficult to predict. Yet the adverse effect of COVID-19 can be felt upon the Energy market leading to a fluctuation in demand for artificial intelligence in the energy market, the effect on manufacturing organizations due to the implementation of lockdown norms in many nations worldwide, and others. Difficulty in-migration of workers and the constant returns of workers to their homelands is becoming a constant obstacle in the growth path of the industry.
The global AI in energy market report also contains analysis on:
AI in energy market Segments:
By industry stream:
Oil and gas
Upstream
Mid-stream
Downstream
Power industry
Transmission
Generation
distribution
By solution type:
Software
Hardware
AI-as-a-solution
AI in energy market Dynamics
AI in energy market Size
Supply & Demand
Current Trends/Issues/Challenges
Competition & Companies Involved in the Market
Value Chain of the Market
Market Drivers and Restraints
FAQs on Global AI in energy market
Which segment is anticipated to hold the largest market share?
At what CAGR is the market anticipated to grow between 2020 and
Who are the key players in the global AI in the energy market?
What could be the challenging factors for the growth of AI in the energy market?
What are the growth drivers for AI in the energy market?
1. EXECUTIVE SUMMARY
2. AI IN ENERGY
2.1. Product Overview
2.2. Market Definition
2.3. Segmentation
2.4. Assumptions and Acronyms
3. RESEARCH METHODOLOGY
3.1. Research Objectives
3.2. Primary Research
3.3. Secondary Research
3.4. Forecast Model
3.5. Market Size Estimation
4. AVERAGE PRICING ANALYSIS
5. MARKET DYNAMICS
5.1. Growth Drivers
5.2. Restraints
5.3. Opportunity
5.4. Trends
6. CORRELATION & REGRESSION ANALYSIS
6.1. Correlation Matrix
6.2. Regression Matrix
7. RECENT DEVELOPMENT, POLICIES®ULATORY LANDSCAPE
8. RISK ANALYSIS
8.1. Demand Risk Analysis
8.2. Supply Risk Analysis
9. AI IN ENERGY INDUSTRY ANALYSIS
9.1. Porters Five Forces
9.1.1. Threat of New Entrants
9.1.2. Bargaining Power of Suppliers
9.1.3. Threat of Substitutes
9.1.4. Rivalry
9.2. PEST Analysis
9.2.1. Political
9.2.2. Economic
9.2.3. Social
9.2.4. Technological
10. GLOBAL AI IN ENERGY MARKET
10.1. Market Size & forecast, 2019A-2030F
10.1.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11. GLOBAL AI IN ENERGY MARKET: MARKET SEGMENTATION
11.1. By Regions
11.1.1. North America:(U.S. and Canada)
11.1.1.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.1.2. Latin America: (Brazil, Mexico, Argentina, Rest of Latin America)
11.1.2.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.1.3. Europe: (Germany, UK, France, Italy, Spain, BENELUX, NORDIC, Hungary, Poland, Turkey, Russia, Rest of Europe)
11.1.3.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.1.4. Asia-Pacific: (China, India, Japan, South Korea, Indonesia, Malaysia, Australia, New Zealand, Rest of Asia Pacific)
11.1.4.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.1.5. Middle East and Africa: (Israel, GCC, North Africa, South Africa, Rest of Middle East and Africa)
11.1.5.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.2. By Industry: Market Share (2020-2030F)
11.2.1. Oil and gas, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.2.2. Power, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.3. By Solution Type: Market Share (2020-2030F)
11.3.1. Software, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.3.2. Hardware, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.3.3. AI-as-a-Service, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.4. By industry Stream: Market Share (2020-2030F)
11.4.1. Upstream, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.4.2. Midstream, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.4.3. Downstream, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12. COMPANY PROFILE
12.1. IBM Corporation
12.1.1. Company Overview
12.1.2. Company Total Revenue (Financials)
12.1.3. Market Potential
12.1.4. Global Presence
12.1.5. Key Performance Indicators
12.1.6. SWOT Analysis
12.1.7. Product Launch
12.2. SAP SE
12.3. Microsoft Corporation
12.4. Huawei technologies
12.5. Accenture PLC
12.6. HCL technologies
12.7. Schneider Electric
12.8. Honeywell international
12.9. Rockwell Automation
12.10. Schlumberger Limited
12.11. Other prominent players
Consultant Recommendation
**The above-given segmentations and companies could be subjected to further modification based on in-depth feasibility studies conducted for the final deliverable.
2. AI IN ENERGY
2.1. Product Overview
2.2. Market Definition
2.3. Segmentation
2.4. Assumptions and Acronyms
3. RESEARCH METHODOLOGY
3.1. Research Objectives
3.2. Primary Research
3.3. Secondary Research
3.4. Forecast Model
3.5. Market Size Estimation
4. AVERAGE PRICING ANALYSIS
5. MARKET DYNAMICS
5.1. Growth Drivers
5.2. Restraints
5.3. Opportunity
5.4. Trends
6. CORRELATION & REGRESSION ANALYSIS
6.1. Correlation Matrix
6.2. Regression Matrix
7. RECENT DEVELOPMENT, POLICIES®ULATORY LANDSCAPE
8. RISK ANALYSIS
8.1. Demand Risk Analysis
8.2. Supply Risk Analysis
9. AI IN ENERGY INDUSTRY ANALYSIS
9.1. Porters Five Forces
9.1.1. Threat of New Entrants
9.1.2. Bargaining Power of Suppliers
9.1.3. Threat of Substitutes
9.1.4. Rivalry
9.2. PEST Analysis
9.2.1. Political
9.2.2. Economic
9.2.3. Social
9.2.4. Technological
10. GLOBAL AI IN ENERGY MARKET
10.1. Market Size & forecast, 2019A-2030F
10.1.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11. GLOBAL AI IN ENERGY MARKET: MARKET SEGMENTATION
11.1. By Regions
11.1.1. North America:(U.S. and Canada)
11.1.1.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.1.2. Latin America: (Brazil, Mexico, Argentina, Rest of Latin America)
11.1.2.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.1.3. Europe: (Germany, UK, France, Italy, Spain, BENELUX, NORDIC, Hungary, Poland, Turkey, Russia, Rest of Europe)
11.1.3.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.1.4. Asia-Pacific: (China, India, Japan, South Korea, Indonesia, Malaysia, Australia, New Zealand, Rest of Asia Pacific)
11.1.4.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.1.5. Middle East and Africa: (Israel, GCC, North Africa, South Africa, Rest of Middle East and Africa)
11.1.5.1. By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.2. By Industry: Market Share (2020-2030F)
11.2.1. Oil and gas, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.2.2. Power, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.3. By Solution Type: Market Share (2020-2030F)
11.3.1. Software, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.3.2. Hardware, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.3.3. AI-as-a-Service, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.4. By industry Stream: Market Share (2020-2030F)
11.4.1. Upstream, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.4.2. Midstream, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
11.4.3. Downstream, By Value (USD Million) 2019-2030F; Y-o-Y Growth (%) 2020-2030F
12. COMPANY PROFILE
12.1. IBM Corporation
12.1.1. Company Overview
12.1.2. Company Total Revenue (Financials)
12.1.3. Market Potential
12.1.4. Global Presence
12.1.5. Key Performance Indicators
12.1.6. SWOT Analysis
12.1.7. Product Launch
12.2. SAP SE
12.3. Microsoft Corporation
12.4. Huawei technologies
12.5. Accenture PLC
12.6. HCL technologies
12.7. Schneider Electric
12.8. Honeywell international
12.9. Rockwell Automation
12.10. Schlumberger Limited
12.11. Other prominent players
Consultant Recommendation
**The above-given segmentations and companies could be subjected to further modification based on in-depth feasibility studies conducted for the final deliverable.
