Artificial Intelligence in Energy Market Size, Revenue, Trends, Competitive Landscape Study & Analysis, Forecast To

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Increasing need to obtain operational efficiency to meet energy requirements are key factors driving global Artificial Intelligence in energy market growth.

The Global Artificial Intelligence in Energy Market intelligence report further offers hard to find data derived from attractiveness analysis that narrates a lot about the products, regions and applications expected to generate more revenue. The research study sheds light on the key growth opportunities and market trends along with other vital market dynamics, including the drivers and restraints on the industry growth. With this report, the prospective buyers can be sure to become capable of adapting to the changes in the Artificial Intelligence in Energy industry.

Increasing need to obtain operational efficiency to meet energy requirements are key factors driving global Artificial Intelligence in energy market growth.   

Adoption of Artificial Intelligence solutions among oilfield services providers and operators has been increasing and is driving deployment of Artificial Intelligence solutions in oil gas industries. Rising need to identify improper threading in pipelines or defects in error-prone mechanisms is driving utilization of Artificial Intelligence-powered defect detection solutions in oil gas industries.                     

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  • 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.
  • Emergen Research has segmented the global Artificial Intelligence in energy market on the basis of product offering, industry stream, application, and region:
    • 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

Competitive Landscape:

The latest study provides an insightful analysis of the broad competitive landscape of the global Artificial Intelligence in Energy Market , emphasizing the key market rivals and their company profiles. A wide array of strategic initiatives, such as new business deals, mergers acquisitions, collaborations, joint ventures, technological upgradation, and recent product launches, undertaken by these companies has been discussed in the report. The report analyzes various elements of the market’s competitive scenario, such as the regulatory standards and policies implemented across the industry over recent years.

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Questions addressed in the report:

  • What is the estimated market growth rate throughout the forecast period?
  • Which end-use industry is expected to witness the highest demand for Artificial Intelligence in Energy market in the near future?
  • What is the regulatory framework governing the application of Artificial Intelligence in Energy Market in the food industry?
  • Which manufacturing processes are utilized for the production of Artificial Intelligence in Energy Market ?

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Table of Contents:

  • Chapter 1 includes an introduction of the global Artificial Intelligence in Energy market , along with a comprehensive market overview, market scope, product offerings, and an investigation of the market drivers, growth opportunities, risks, restraints, and other vital factors.
  • Chapter 2 offers an in-depth analysis of the key manufacturers engaged in this business vertical, along with their sales and revenue estimations.
  • Chapter 3 elaborates on the highly competitive terrain of the market, highlighting the key manufacturers and vendors.
  • In Chapter 4, our team has fragmented the market on the basis of regions, underscoring the sales, revenue, and market share of each region over the forecast timeline.
  • Chapters 5 and 6 have laid emphasis on the market segmentation based on product type and application

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.

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