Vancouver, BC -- (SBWIRE) -- 02/24/2021 -- The global Artificial Intelligence in energy market is expected to reach a market size of USD 20.83 Billion at a steady CAGR of 23.6% in 2028, according to latest analysis by Emergen Research. This steady revenue growth can be attributed to increasing need to obtain operational efficiency to meet energy requirements. Digitalization of the energy sector is contributing to increasing demand for Artificial Intelligence in energy systems.

The study draws a forecast of the growth of the Artificial Intelligence in Energy market by evaluating the market size, share, demand, trends, and gross revenue of the industry. It also focuses on the positions of the major companies against the competitive landscape and their individual share in the global market. The report segments the industry based on product type, application and end-use. It highlights the recent trends and technological developments in the sector that will potentially influence the industry. The research offers a detailed outlook of the trends observed in the market, the contributing factors, major stakeholders, key companies and prime areas that exhibit a potential for growth.

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Key Highlights of Report
In July 2020, Petro.ai, which is an expert in machine learning and Artificial Intelligence for geotechnical data science and providers of the industry-leading integrated analytics platform, announced the launch of a new offering enabling modern analytics from legacy data lakes using integrated data ingestion pipelines on Amazon Web Services (AWS). Petro.ai on AWS leverages the scalability and flexibility of AWS infrastructure to accelerate discovery of oil and gas insights through the fusion of subsurface and operational data.
The software segment accounted for largest revenue share of 2020. Artificial Intelligence-driven software is expected to improve customer savings by controlling energy costs without interrupting operations, which is expected to drive revenue growth of the software segment.
Power industry segment revenue is expected to expand at a rapid CAGR of 23.8% during the forecast period. Rising need to make the power industry more secure and efficient by analyzing and evaluating data volumes is a key factor driving demand for Artificial Intelligence solutions in the power industry.
The renewable energy management segment accounted for a significantly high revenue share in the Artificial Intelligence in energy market in 2020. Increasing need for low carbon emissions is expected to drive rising utilization of AI for renewable energy management during the forecast period.
North America accounted for largest revenue share contribution to the global Artificial Intelligence in energy market in 2020. Increasing adoption of Artificial Intelligence-based smart meters and smart home solutions is contributing to growing demand for AI in the energy sector in countries in the region.
Key players in the market include Accenture PLC, Amazon Web Services, Inc., AutoGrid Systems, Inc, Cisco Systems Inc., C3 IoT, Inc., General Electric, HCL Technologies Ltd., Huawei Technologies Co., Ltd., IBM Corporation, and Intel Corporation.

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Product offering Outlook (Revenue, USD Billion; 2021–2028)
Support Services
Hardware
AI-as-a-Service
Software

Industry stream Outlook (Revenue, USD Billion; 2021–2028)
Power Industry (Generation, Transmission, Distribution)
Oil & Gas Industry (Upstream, Midstream, Downstream)

Application Outlook (Revenue, USD Billion; 2021–2028)
Demand Response Management
Fleet & asset Management
Renewable Energy Management
Precision Drilling
Demand forecasting
Infrastructure Management
Others

Key questions answered in the report
What will be the market size in terms of value and volume in the next five years?
Which segment is currently leading the market?
In which region will the market find its highest growth?
Which players will take the lead in the market?
What are the key drivers and restraints of the market's growth?

The report segments the Artificial Intelligence in Energy market on the basis of geography, end-user, end-use, product application, type, share, growth rate and size to reveal where the industry will be in the coming years. The researchers assessing the industry have included the details about the recent decisions and events such acquisition and mergers, collaborations, product launch and investments. Important decisions connected with such events come handy for business owners when positioning their brands in the global market and finalizing the marketing strategies.

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Table of Content
Chapter 1. Methodology & Sources
1.1. Market Definition
1.2. Research Scope
1.3. Methodology
1.4. Research Sources
1.4.1. Primary
1.4.2. Secondary
1.4.3. Paid Sources
1.5. Market Estimation Technique
Chapter 2. Executive Summary
2.1. Summary Snapshot, 2019-2027
Chapter 3. Key Insights
Chapter 4. Artificial Intelligence in Energy Market Segmentation & Impact Analysis
4.1. Artificial Intelligence in Energy Market Material Segmentation Analysis
4.2. Industrial Outlook
4.2.1. Market indicators analysis
4.2.2. Market drivers analysis
4.2.2.1. Stringent environmental regulations
4.2.2.2. Rising need to reduce bacterial or algal contamination in water systems
4.2.2.3. Increasing demand for biocides for municipal water treatment
4.2.3. Market restraints analysis
4.2.3.1. Fluctuating prices of raw material
4.2.3.2. Present challenging economic conditions due to the pandemic
4.3. Technological Insights
4.4. Regulatory Framework
4.5. Porter's Five Forces Analysis
4.6. Competitive Metric Space Analysis
4.7. Price trend Analysis
4.8. Covid-19 Impact Analysis
Chapter 5. Artificial Intelligence in Energy Market By Application Insights & Trends, Revenue (USD Million), Volume (Kilo Tons)
Chapter 6. Artificial Intelligence in Energy Market By Product type Insights & Trends Revenue (USD Million), Volume (Kilo Tons)
Chapter 7. Artificial Intelligence in Energy Market Regional Outlook
Chapter 8. Competitive Landscape
Continued…