AI in Energy Market By Component type, By Application, By End user, By Deployment Type: Global Opportunity Analysis and Industry Forecast, 2021-2031

Table of Contents

CHAPTER 1: INTRODUCTION
1.1. Report description
1.2. Key market segments
1.3. Key benefits to the stakeholders
1.4. Research Methodology
1.4.1. Secondary research
1.4.2. Primary research
1.4.3. Analyst tools and models

CHAPTER 2: EXECUTIVE SUMMARY
2.1. Key findings of the study
2.2. CXO Perspective

CHAPTER 3: MARKET OVERVIEW
3.1. Market definition and scope
3.2. Key findings
3.2.1. Top investment pockets
3.3. Porter’s five forces analysis
3.4. Top player positioning
3.5. Market dynamics
3.5.1. Drivers
3.5.2. Restraints
3.5.3. Opportunities
3.6. COVID-19 Impact Analysis on the market

CHAPTER 4: AI IN ENERGY MARKET, BY COMPONENT TYPE
4.1 Overview
4.1.1 Market size and forecast
4.2 Solutions
4.2.1 Key market trends, growth factors and opportunities
4.2.2 Market size and forecast, by region
4.2.3 Market analysis by country
4.3 Services
4.3.1 Key market trends, growth factors and opportunities
4.3.2 Market size and forecast, by region
4.3.3 Market analysis by country

CHAPTER 5: AI IN ENERGY MARKET, BY APPLICATION
5.1 Overview
5.1.1 Market size and forecast
5.2 Robotics
5.2.1 Key market trends, growth factors and opportunities
5.2.2 Market size and forecast, by region
5.2.3 Market analysis by country
5.3 Renewables Management
5.3.1 Key market trends, growth factors and opportunities
5.3.2 Market size and forecast, by region
5.3.3 Market analysis by country
5.4 Demand Forecasting
5.4.1 Key market trends, growth factors and opportunities
5.4.2 Market size and forecast, by region
5.4.3 Market analysis by country
5.5 Safety and Security
5.5.1 Key market trends, growth factors and opportunities
5.5.2 Market size and forecast, by region
5.5.3 Market analysis by country
5.6 Infrastructure
5.6.1 Key market trends, growth factors and opportunities
5.6.2 Market size and forecast, by region
5.6.3 Market analysis by country
5.7 Others
5.7.1 Key market trends, growth factors and opportunities
5.7.2 Market size and forecast, by region
5.7.3 Market analysis by country

CHAPTER 6: AI IN ENERGY MARKET, BY END USER
6.1 Overview
6.1.1 Market size and forecast
6.2 Energy Transmission
6.2.1 Key market trends, growth factors and opportunities
6.2.2 Market size and forecast, by region
6.2.3 Market analysis by country
6.3 Energy Generation
6.3.1 Key market trends, growth factors and opportunities
6.3.2 Market size and forecast, by region
6.3.3 Market analysis by country
6.4 Energy Distribution
6.4.1 Key market trends, growth factors and opportunities
6.4.2 Market size and forecast, by region
6.4.3 Market analysis by country
6.5 Utilities
6.5.1 Key market trends, growth factors and opportunities
6.5.2 Market size and forecast, by region
6.5.3 Market analysis by country

CHAPTER 7: AI IN ENERGY MARKET, BY DEPLOYMENT TYPE
7.1 Overview
7.1.1 Market size and forecast
7.2 On-premise
7.2.1 Key market trends, growth factors and opportunities
7.2.2 Market size and forecast, by region
7.2.3 Market analysis by country
7.3 Cloud
7.3.1 Key market trends, growth factors and opportunities
7.3.2 Market size and forecast, by region
7.3.3 Market analysis by country

CHAPTER 8: AI IN ENERGY MARKET, BY REGION
8.1 Overview
8.1.1 Market size and forecast
8.2 North America
8.2.1 Key trends and opportunities
8.2.2 North America Market size and forecast, by Component type
8.2.3 North America Market size and forecast, by Application
8.2.4 North America Market size and forecast, by End user
8.2.5 North America Market size and forecast, by Deployment Type
8.2.6 North America Market size and forecast, by country
8.2.6.1 U. S.
8.2.6.1.1 Market size and forecast, by Component type
8.2.6.1.2 Market size and forecast, by Application
8.2.6.1.3 Market size and forecast, by End user
8.2.6.1.4 Market size and forecast, by Deployment Type
8.2.6.2 Canada
8.2.6.2.1 Market size and forecast, by Component type
8.2.6.2.2 Market size and forecast, by Application
8.2.6.2.3 Market size and forecast, by End user
8.2.6.2.4 Market size and forecast, by Deployment Type
8.2.6.3 Mexico
8.2.6.3.1 Market size and forecast, by Component type
8.2.6.3.2 Market size and forecast, by Application
8.2.6.3.3 Market size and forecast, by End user
8.2.6.3.4 Market size and forecast, by Deployment Type
8.3 Europe
8.3.1 Key trends and opportunities
8.3.2 Europe Market size and forecast, by Component type
8.3.3 Europe Market size and forecast, by Application
8.3.4 Europe Market size and forecast, by End user
8.3.5 Europe Market size and forecast, by Deployment Type
8.3.6 Europe Market size and forecast, by country
8.3.6.1 Germany
8.3.6.1.1 Market size and forecast, by Component type
8.3.6.1.2 Market size and forecast, by Application
8.3.6.1.3 Market size and forecast, by End user
8.3.6.1.4 Market size and forecast, by Deployment Type
8.3.6.2 Italy
8.3.6.2.1 Market size and forecast, by Component type
8.3.6.2.2 Market size and forecast, by Application
8.3.6.2.3 Market size and forecast, by End user
8.3.6.2.4 Market size and forecast, by Deployment Type
8.3.6.3 UK
8.3.6.3.1 Market size and forecast, by Component type
8.3.6.3.2 Market size and forecast, by Application
8.3.6.3.3 Market size and forecast, by End user
8.3.6.3.4 Market size and forecast, by Deployment Type
8.3.6.4 Spain
8.3.6.4.1 Market size and forecast, by Component type
8.3.6.4.2 Market size and forecast, by Application
8.3.6.4.3 Market size and forecast, by End user
8.3.6.4.4 Market size and forecast, by Deployment Type
8.3.6.5 France
8.3.6.5.1 Market size and forecast, by Component type
8.3.6.5.2 Market size and forecast, by Application
8.3.6.5.3 Market size and forecast, by End user
8.3.6.5.4 Market size and forecast, by Deployment Type
8.3.6.6 Rest of Europe
8.3.6.6.1 Market size and forecast, by Component type
8.3.6.6.2 Market size and forecast, by Application
8.3.6.6.3 Market size and forecast, by End user
8.3.6.6.4 Market size and forecast, by Deployment Type
8.4 Asia-Pacific
8.4.1 Key trends and opportunities
8.4.2 Asia-Pacific Market size and forecast, by Component type
8.4.3 Asia-Pacific Market size and forecast, by Application
8.4.4 Asia-Pacific Market size and forecast, by End user
8.4.5 Asia-Pacific Market size and forecast, by Deployment Type
8.4.6 Asia-Pacific Market size and forecast, by country
8.4.6.1 China
8.4.6.1.1 Market size and forecast, by Component type
8.4.6.1.2 Market size and forecast, by Application
8.4.6.1.3 Market size and forecast, by End user
8.4.6.1.4 Market size and forecast, by Deployment Type
8.4.6.2 Japan
8.4.6.2.1 Market size and forecast, by Component type
8.4.6.2.2 Market size and forecast, by Application
8.4.6.2.3 Market size and forecast, by End user
8.4.6.2.4 Market size and forecast, by Deployment Type
8.4.6.3 India
8.4.6.3.1 Market size and forecast, by Component type
8.4.6.3.2 Market size and forecast, by Application
8.4.6.3.3 Market size and forecast, by End user
8.4.6.3.4 Market size and forecast, by Deployment Type
8.4.6.4 South Korea
8.4.6.4.1 Market size and forecast, by Component type
8.4.6.4.2 Market size and forecast, by Application
8.4.6.4.3 Market size and forecast, by End user
8.4.6.4.4 Market size and forecast, by Deployment Type
8.4.6.5 Australia
8.4.6.5.1 Market size and forecast, by Component type
8.4.6.5.2 Market size and forecast, by Application
8.4.6.5.3 Market size and forecast, by End user
8.4.6.5.4 Market size and forecast, by Deployment Type
8.4.6.6 Rest of Asia-Pacific
8.4.6.6.1 Market size and forecast, by Component type
8.4.6.6.2 Market size and forecast, by Application
8.4.6.6.3 Market size and forecast, by End user
8.4.6.6.4 Market size and forecast, by Deployment Type
8.5 LAMEA
8.5.1 Key trends and opportunities
8.5.2 LAMEA Market size and forecast, by Component type
8.5.3 LAMEA Market size and forecast, by Application
8.5.4 LAMEA Market size and forecast, by End user
8.5.5 LAMEA Market size and forecast, by Deployment Type
8.5.6 LAMEA Market size and forecast, by country
8.5.6.1 Brazil
8.5.6.1.1 Market size and forecast, by Component type
8.5.6.1.2 Market size and forecast, by Application
8.5.6.1.3 Market size and forecast, by End user
8.5.6.1.4 Market size and forecast, by Deployment Type
8.5.6.2 Saudi Arabia
8.5.6.2.1 Market size and forecast, by Component type
8.5.6.2.2 Market size and forecast, by Application
8.5.6.2.3 Market size and forecast, by End user
8.5.6.2.4 Market size and forecast, by Deployment Type
8.5.6.3 South Africa
8.5.6.3.1 Market size and forecast, by Component type
8.5.6.3.2 Market size and forecast, by Application
8.5.6.3.3 Market size and forecast, by End user
8.5.6.3.4 Market size and forecast, by Deployment Type
8.5.6.4 Rest of LAMEA
8.5.6.4.1 Market size and forecast, by Component type
8.5.6.4.2 Market size and forecast, by Application
8.5.6.4.3 Market size and forecast, by End user
8.5.6.4.4 Market size and forecast, by Deployment Type

CHAPTER 9: COMPANY LANDSCAPE
9.1. Introduction
9.2. Top winning strategies
9.3. Product Mapping of Top 10 Player
9.4. Competitive Dashboard
9.5. Competitive Heatmap
9.6. Key developments

CHAPTER 10: COMPANY PROFILES
10.1 Alpiq AG
10.1.1 Company overview
10.1.2 Company snapshot
10.1.3 Operating business segments
10.1.4 Product portfolio
10.1.5 Business performance
10.1.6 Key strategic moves and developments
10.2 SmartCloud Inc.
10.2.1 Company overview
10.2.2 Company snapshot
10.2.3 Operating business segments
10.2.4 Product portfolio
10.2.5 Business performance
10.2.6 Key strategic moves and developments
10.3 General Electric
10.3.1 Company overview
10.3.2 Company snapshot
10.3.3 Operating business segments
10.3.4 Product portfolio
10.3.5 Business performance
10.3.6 Key strategic moves and developments
10.4 Siemens AG
10.4.1 Company overview
10.4.2 Company snapshot
10.4.3 Operating business segments
10.4.4 Product portfolio
10.4.5 Business performance
10.4.6 Key strategic moves and developments
10.5 Hazama Ando Corporation
10.5.1 Company overview
10.5.2 Company snapshot
10.5.3 Operating business segments
10.5.4 Product portfolio
10.5.5 Business performance
10.5.6 Key strategic moves and developments
10.6 ATOS SE
10.6.1 Company overview
10.6.2 Company snapshot
10.6.3 Operating business segments
10.6.4 Product portfolio
10.6.5 Business performance
10.6.6 Key strategic moves and developments
10.7 AppOrchid Inc
10.7.1 Company overview
10.7.2 Company snapshot
10.7.3 Operating business segments
10.7.4 Product portfolio
10.7.5 Business performance
10.7.6 Key strategic moves and developments
10.8 Zen Robotics Ltd
10.8.1 Company overview
10.8.2 Company snapshot
10.8.3 Operating business segments
10.8.4 Product portfolio
10.8.5 Business performance
10.8.6 Key strategic moves and developments
10.9 Schneider Electric
10.9.1 Company overview
10.9.2 Company snapshot
10.9.3 Operating business segments
10.9.4 Product portfolio
10.9.5 Business performance
10.9.6 Key strategic moves and developments
10.10 ABB
10.10.1 Company overview
10.10.2 Company snapshot
10.10.3 Operating business segments
10.10.4 Product portfolio
10.10.5 Business performance
10.10.6 Key strategic moves and developments

Executive Summary

According to this report, titled, 'AI in Energy Market,' the AI in energy market size was valued at $4 billion in 2021, and is estimated to reach $19.8 billion by 2031, growing at a CAGR of 17.4% from 2022 to 2031.

Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, and speech recognition and machine vision. Every industrial environment needs artificial intelligence . The adoption of AI offers particularly good potential for AI in energy market growth. Artificial intelligence gives a machine the capability to learn and make choices in order to solve issues or improve outcomes in order to achieve a goal. In the energy business, there are several decisions that must be made quickly and with a large amount of data. Artificial intelligence industry is capable of carrying out these crucial judgments in the most effective way possible, which calls for the immediate collection and analysis of these massive volumes of data.

In addition, electric vehicles are the way of the future, but they also come with new difficulties. AI is now being installed in the electric vehicle sector within cars themselves in order to manage it and transmit information that contributes to solving these challenges, but also outside the car to facilitate the effective management of reports, intelligent mobility solutions, etc. Artificial intelligence is attempting to be used in the energy sector and is already proving essential by providing the market and households with new information services in the control over energy infrastructure, optimizing generation, reducing consumption, or fighting climate change, which are only some of the promises it holds in the coming years. This factor is predicted to create AI in energy market opportunities for expansion of the market in the future.

Furthermore, energy companies are integrating data with AI-powered video analytics systems to explore and analyze various types of data, such as sales data, for informed decision-making. For the dynamic depiction of data, firms are incorporating business analytics software into their operations. As a result, the need for AI in energy sector is anticipated to grow considerably throughout the projection period.

The AI in energy market forecast is segmented based on component type, deployment type, application, end-user, and region. Based on component type, it is classified into solutions and services. By deployment type, the market is categorized into on-premise and cloud. Based on application, the market is fragmented into robotics, renewables management, demand forecasting, safety & security, infrastructure, and others. Based on end-user, it is divided into energy transmission, energy generation, energy distribution, and utilities. Region-wise, the market is studied across North America, Europe, Asia-Pacific, and LAMEA.

Key players operating in the global AI in energy market analysis include ABB ltd., Accenture plc, Amazon Web Services Inc., Autogrid Systems, Inc., C3.ai, Centrica plc, Cisco Systems Inc., General Electric, HCL Technologies, Huawei Technologies Co., Ltd., IBM Corporation, Intel Corporation, Mitsubishi Electric, and Schneider Electric and Senseye.

Key findings of the study

By component type, the solutions segment is estimated to display the highest growth rate in revenue, registering a CAGR of 17.2% from 2022 to 2031.

By deployment type, the cloud segment is estimated to display the highest growth rate in revenue, registering a CAGR of 17.6% from 2022 to 2031.

By applications, the safety and security segment is anticipated to register the highest CAGR of 18.0% during the forecast period.

By end user, the utility segment is anticipated to register the highest CAGR of 17.9% during the forecast period.

Asia-Pacific garnered the highest AI in energy market share of 40% in 2021, in terms of revenue, growing at a CAGR of 17.7%.

Companies Mentioned

• Alpiq AG
• Smartcloud Inc.
• General Electric
• Siemens AG
• Hazama Ando Corporation
• Atos SE
• Apporchid Inc.
• Zen Robotics Ltd.
• Schneider Electric
• ABB

Methodology

The analyst offers exhaustive research and analysis based on a wide variety of factual inputs, which largely include interviews with industry participants, reliable statistics, and regional intelligence. The in-house industry experts play an instrumental role in designing analytic tools and models, tailored to the requirements of a particular industry segment. The primary research efforts include reaching out participants through mail, tele-conversations, referrals, professional networks, and face-to-face interactions.

They are also in professional corporate relations with various companies that allow them greater flexibility for reaching out to industry participants and commentators for interviews and discussions.

They also refer to a broad array of industry sources for their secondary research, which typically include; however, not limited to:

• Company SEC filings, annual reports, company websites, broker & financial reports, and investor presentations for competitive scenario and shape of the industry
• Scientific and technical writings for product information and related preemptions
• Regional government and statistical databases for macro analysis
• Authentic news articles and other related releases for market evaluation
• Internal and external proprietary databases, key market indicators, and relevant press releases for market estimates and forecast

Furthermore, the accuracy of the data will be analyzed and validated by conducting additional primaries with various industry experts and KOLs. They also provide robust post-sales support to clients.