Global AI in Energy Market by Component, Function, Application and Region, Global Industry Analysis and Forecast 2022 – 2030 offers assembled trends and predictions to clients. The report delivers a comprehensive overview of the crucial elements of the market and elements such as drivers, current trends of the past and present times, supervisory scenario & technological growth. The report is an intensive investigation portraying the details and the new opportunity appraisal of the market.
Artificial intelligence (AI) is an extent of computer technology that highlights the formation of intelligent machines that works and reacts like humans. In addition, considering advanced technologies, it creates extreme changes and effects of AI technology in the energy and utility market which can be seen in their applications such as smart automated grid and energy distribution system. High investment is one of the biggest challenges that impede the growth of this technology in the energy and utilities sector. This sector involves in production and distribution of energy constitutes such as oil & gas, and power generation.
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Top Impacting Factors: Market Scenario Analysis, Trends, Drivers, and Impact Analysis
Artificial intelligence software in energy market came up with growth in software market due to increase in implementation of cloud based solution and growth in adoption of micro grids technology, and it is likely to see the fastest growth during pandemic and increase in the number of renewable energy producers in emerging economies such as China and India. In addition, North America was the largest AI in energy market in 2019, and offered several growth opportunities to market vendors during the forecast period. However, AI in energy market disintegrated. Some of the major market vendors such as ABB Ltd, Alphabet Inc., Flex Ltd, General Electric Co, Intel Corp, International Business Machines Corp, Microsoft Corp, Origami Energy Ltd, Siemens AG and Verdigris Technologies Inc. which are used to help many clients improve their market condition and provides a detailed analysis of the market.
Increase in Adoption of Cloud Based Solutions
Increase in adoption of cloud based solutions in AI is one of the major trends in the energy sector to enhance the capabilities of existing systems. In addition, with the rise applications of robotics management in tedious and risky tasks, end users are increasingly seeking opportunities to ensure the rejection of margins of industrial automation and robotics technologies.
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Rise of Micro-grid Adoption
AI provides a certain amount of capability to balance micro-grids, demands, negotiate actions, self-healing and facilitating ability for new software and services. Micro-grid adoption in AI, particularly evolving and growing rapidly due to implementation of smart cities is expected to drive the energy market. In addition, many government sectors and organizations have started investigating the viability of micro-grids to enable persistence of service during an emergency or power outage. Furthermore, with the evolution of different technologies such as distributed energy resources and block-chain, AI has prospective to deliver the active management which is the requirement of the future.
Key players operating in the market:
ABB Ltd., Alphabet Inc., Flex Ltd., General Electric Co., Intel Corp., International Business Machines Corp., Microsoft Corp., Origami Energy Ltd., Siemens AG, Verdigris Technologies Inc
Questions Answered in the Global AI in Energy Market Research Report
- Which are the leading players active in the AI in energy market?
- What would be the detailed impact of COVID-19 on the market?
- What current trends would influence the market in the next few years?
- What are the driving factors, restraints, and opportunities in the AI in energy market?
- What are the projections for the future that would help in taking further strategic steps?
By Component
- Solutions
- Services
By Function
- Predictive maintenance and machinery inspection
- Material movement
- Production planning
- Field services
- Quality control
- Reclamation
By Application
- Upstream
- Downstream
- Midstream
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