Key Questions Answered in this Report:
- What are the key trends and opportunities in the market pertaining to AI in energy?
- What is the estimated global AI in energy market size in terms of revenue for the time period 2018-2024, and what is the expected compound annual growth rate (CAGR) during the forecast period 2019-2024?
- What is the expected future outlook and revenue to be generated by the different types of product offerings including software, hardware, AI-as-a-Service, and support services?
- What is the estimated revenue generated by AI solutions in both power and oil & gas industries for the time period 2018-2024?
- What is the estimated revenue generated by AI solutions in different power industry streams such as generation, transmission, and distribution for the time period 2018-2014?
- What is the estimated revenue generated by AI solutions in different oil & gas industry streams such as upstream, midstream, and downstream for the time period 2018-2024?
- What is the estimated revenue generated by AI solutions in different applications of power and oil & gas industry for the time period 2018-2024?
- What is the current market size and opportunities of AI solutions in energy industry across different regions including North America, Europe, Asia-Pacific, and Rest-of-the-World?
- What are the major driving forces that are expected to increase the demand for the global AI in energy market during the forecast period?
- What are the major restraints inhibiting the growth of the global AI in energy market?
- What kind of new strategies are being adopted by the existing market players to expand their market position in the industry?
- What is the competitive strength of the key players in the AI in energy market on the basis of analysis of their recent developments, product offerings, and regional presence?
- How is the competitive benchmarking of the key AI focused IT companies in the energy market on the basis of analysis of their market coverage and market potential?
- What is the funding and investment landscape in the global AI in energy market?
- Which type of players and stakeholders operate in the market ecosystem of AI in energy, and what are their significance in the global market?
- Which are the leading consortiums and associations in the global AI in energy market, and what is their role in the market?
- How does the regulatory landscape differ in different regions for AI in energy?
Global Artificial Intelligence (AI) in Energy Market Forecast, 2019-2024
The Global Artificial Intelligence (AI) in Energy Industry Analysis by the report projects the market to grow at a significant CAGR of 22.49% during the forecast period from 2019 to 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.
"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.”
Scope of the Global Artificial Intelligence (AI) in Energy Market
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.
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 in the Artificial Intelligence (AI) in Energy Market
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.