Artificial Intelligence
Global AI in Energy Market 2019-2024 – Fruitful Opportunities in Fleet & Asset Management Applications
Dublin, Jan. 14, 2020 (GLOBE NEWSWIRE) — The “Global Artificial Intelligence in Energy Market: Focus on Product Type, Industry, Applications, Funding – Analysis and Forecast, 2019-2024” report has been added to ResearchAndMarkets.com’s offering.
The Global Artificial Intelligence (AI) in Energy Industry Analysis projects the market to grow at a significant CAGR of 22.49% during the forecast period from 2019 to 2024, enabling the market to reach $7.78 billion by 2024
The increasing demand for energy efficiency across the globe has propelled the need for artificial intelligence in energy. Moreover, there is an increased concern for decentralized power generators in the electricity distribution supply chain to reduce the electricity demand. The growth of the market is likely to be encouraged by the rise of battery storage system, leading to congestion and complexity within the grid.
Expert Quote
Fleet and asset management is one of the prominent applications of the AI in energy market. The fleet assets at remote locations are difficult to monitor and control. Any failure of assets without prior intimation leads to an increase in operational downtime. Thus, the energy industry is adopting AI technology to monitor and control the fleet assets across the supply chain. The AI-powered hardware components integrated with the AI software ensures efficient operation of oil & gas assets using vibration analytics, thereby ensuring a safe working atmosphere. An AI-enabled fleet and asset monitoring solution using computer vision provides visibility across the functioning of the equipment, which further helps in investigating the asset performance.
Report Scope
The global artificial intelligence in energy market research provides a detailed perspective regarding the product offerings, applications, value, and estimation, among others. The purpose of this market analysis is to examine the artificial intelligence in energy in terms of factors driving the market, trends, technological developments, and funding scenario, among others.
The report further takes into consideration the market dynamics and the competitive landscape along with the detailed financial and product contribution of the key players operating in the market. The artificial intelligence in energy market report is a compilation of different segments including market breakdown by product offerings, industry stream, and region.
Segment Highlights The global artificial intelligence in energy market comprises oil & gas and power industries. The oil & gas industry has been further segmented into upstream, midstream, and downstream. Similarly, for power industry, generation, transmission, and distribution are the three sectors across the supply chain.
Upstream segment in the oil & gas industry and distribution segment in the power industry accounted for the largest share in the market as a result of the increasing necessity for efficient oil & gas exploration and growing demand for continuous supply of electricity. However, during the forecast period, the generation segment in the power industry is expected to display the highest growth, owing to the increasing focus toward decentralized power generation.
The emerging trends of the AI in energy market vary across different regions. In 2018, North America was at the forefront of the market, with huge market concentration in the U.S. During the forecast period, the Asia-Pacific region is expected to flourish as one of the most lucrative markets for AI in energy. Rising demand for decentralized power generation drive the growth of global AI in energy market.
Key Companies
The prominent players in the artificial intelligence in energy market include IBM Corporation, Microsoft Corporation, Accenture Plc, Amazon Web Services, Inc., Intel Corporation, Oracle Corporation, SAP SE, Huawei Technology, Cisco Systems, General Electric Company, Rockwell Automation, C3.ai, AutoGrid Systems, HCL Technologies, and Wipro Limited. Major Questions Answered Key Topics Covered
Executive Summary
1 Market Dynamics 2 Competitive Landscape 3 Industry Analysis 4 Global Artificial Intelligence (AI) in Energy Market (by Industry Stream) 5 Global Artificial Intelligence (AI) in Energy Market (by Product Offering) 6 Global Artificial Intelligence (AI) in Energy Market (by Application) 7 Global Artificial Intelligence (AI) in Energy Market (by Region) 8 Company Profiles AI Solution Providers
Other Key Companies
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1.1 Market Drivers
1.1.1 Demand for Increasing Operational Efficiency to Fulfil Energy Requirement
1.1.2 Significant Increase in Demand for Decentralized Power Generation
1.1.3 Growing Need for Battery Storage Systems
1.2 Market Restraints
1.2.1 High Cost of Deployment
1.2.2 Privacy and Security Risk
1.3 Market Opportunities
1.3.1 Rising Deployment of Smart Grids
1.3.2 Growth of Establishment of Smart Buildings
2.1 Key Market Developments and Strategies
2.1.1 Partnerships, Collaborations, and Joint Ventures
2.1.2 New Product Launches and Developments
2.1.3 Business Expansions and Contracts
2.1.4 Mergers and Acquisitions
2.1.5 Others (Awards and Recognitions)
2.2 Competitive Benchmarking of IT Solution Providers in AI in Energy Market
3.1 Artificial Intelligence in Energy: Market Ecosystem
3.2 Artificial Intelligence in Energy: Technology Ecosystem
3.2.1 AI Technology Stack
3.2.1.1 AI-Powered Technologies
3.2.1.1.1 Machine Learning
3.2.1.1.2 Computer Vision
3.2.1.1.3 Deep Learning
3.2.1.1.4 Speech Recognition
3.2.1.1.5 Other Technologies
3.2.1.2 Hardware
3.2.1.2.1 Memory
3.2.1.2.2 Storage
3.2.1.2.3 Logic
3.2.1.2.4 Networking
3.2.1.3 Others
3.2.2 AI Technology Classifications
3.2.2.1 AI Technology (by Functionality)
3.2.2.1.1 Reactive Machines
3.2.2.1.2 Limited Memory
3.2.2.1.3 Theory of Mind
3.2.2.1.4 Self-Awareness
3.2.2.2 AI Technology (by Capability)
3.2.2.2.1 Weak AI
3.2.2.2.2 General AI
3.2.2.2.3 Strong AI
3.2.3 Key AI Use Cases in Energy
3.2.3.1 Predictive Analytics
3.2.3.2 Drones/UAVs
3.2.3.3 Intelligent Energy Storage
3.2.3.4 Variable Renewable Energy Integration
3.3 Investment and Funding Landscape
3.4 Key Consortiums and Associations
4.1 Market Overview
4.2 Oil & Gas Industry
4.2.1 Upstream
4.2.2 Midstream
4.2.3 Downstream
4.3 Power Industry
4.3.1 Generation
4.3.2 Transmission
4.3.3 Distribution
5.1 Market Overview
5.2 Software
5.3 Hardware
5.4 AI-as-a-Service
5.5 Support Services
6.1 Market Overview
6.2 Oil & Gas Applications
6.2.1 Fleet and Asset Management
6.2.2 Precision Drilling
6.2.3 Demand Forecasting
6.2.4 Others
6.3 Power Applications
6.3.1 Renewable Energy Management
6.3.2 Infrastructure Management
6.3.3 Demand Response Management
6.3.4 Others
7.1 North America
7.2 Europe
7.3 Asia-Pacific
7.4 Rest-of-the-World (RoW)
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