AI in Nuclear Energy Market Investment and Growth Opportunities Analysis Report 2023-2031
Companies covered in this report are ABB Ltd, BWX Technologies, Inc., Framatome, GE Hitachi Nuclear Energy, General Electric Company, Honeywell International Inc., Kinectrics, Mitsubishi Heavy Industries Ltd, NuScale Power Corporation, TerraPower, Siemens Energy AG, and Toshiba Corporation
Jersey City, NJ, Nov. 22, 2023 (GLOBE NEWSWIRE) — InsightAce Analytic Pvt. Ltd. announces the release of a market assessment report on the “Global AI in Nuclear Energy Market- (By Application (Nuclear Power Plant Operations, Nuclear Waste Management, Radiological Protection, Nuclear Safety and Security, and Nuclear Medicine), By Technology (Deep Learning (DL), Machine Learning (ML), Natural Language Processing (NLP), Reinforcement Learning (RL), Robotics and Automation, and Others), By End User (Nuclear Power Plants, Nuclear Research Facilities, Nuclear Regulatory Authorities, Healthcare (for nuclear medicine applications), and Others)), Trends, Industry Competition Analysis, Revenue and Forecast To 2031.”
According to the latest research by InsightAce Analytic, the Global AI in Nuclear Energy Market is expected to witness a CAGR of 6.19% during the forecast period of 2023-2031.
AI in the nuclear energy market represents a dynamic and rapidly evolving sector that combines nuclear energy expertise with cutting-edge AI technologies. AI is used for predictive maintenance, real-time monitoring, and anomaly detection to prevent accidents and enhance safety protocols. Operational efficiency gains are achieved through AI optimization of nuclear power plant performance, reducing downtime, lowering operational costs, and extending the operational lifespan of ageing facilities.
The challenges of nuclear waste management are also being met with AI, streamlining waste disposal strategies, and ensuring safe storage and handling. Small Modular Reactors (SMRs) are being designed and operated more efficiently with AI, making them scalable and cost-effective. Government support, regulatory alignment, and the broader goal of energy security and sustainability propel AI adoption in the nuclear industry. Overall, the integration of AI is ushering in a new era of enhanced safety, operational efficiency, and sustainability in the nuclear energy market.
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- In November 2023, GE Vernova’s Digital business has unveiled Fleet Orchestration, a cutting-edge software system that assistsdesigned to assist power utilities in optimizing the utilization of renewable energy sources. The program facilitates accelerating carbon reduction goals by utilizing current resources while ensuring the capacity to consistently meet demand.
List Of Prominent Players In The AI In Nuclear Energy Market :
- ABB Ltd
- BWX Technologies, Inc.
- GE Hitachi Nuclear Energy
- General Electric Company
- Honeywell International Inc.
- Mitsubishi Heavy Industries Ltd
- NuScale Power Corporation
- Siemens Energy AG
- Toshiba Corporation
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AI in Nuclear Energy Market Report Scope:
|Growth Rate CAGR
|CAGR of 6.19% from 2023 to 2031
|Representation of revenue in US$ Million and CAGR from 2023 to 2031
|2019 to 2022
|The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends
|By Application, Technology, End-User
|North America; Europe; Asia Pacific; Latin America; Middle East & Africa
|U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; France; Italy; Spain; South East Asia; South Korea
AI enhances the reliability and efficiency of nuclear power, contributing to energy security and sustainable energy sources. AI analyzes vast amounts of data generated by nuclear facilities to provide actionable insights, improving decision-making and operational performance. AI optimizes nuclear plant operations, reducing downtime and improving efficiency. Predictive maintenance and data analytics lower operational costs and extend the lifespan of ageing facilities.
Safety is a primary driver of AI adoption in the nuclear energy sector. AI technologies enable predictive maintenance, real-time monitoring, and anomaly detection, reducing the risk of accidents and enhancing overall safety protocols. This has led to greater confidence in the industry. The adoption of AI in the nuclear energy market is experiencing significant expansion due to factors reshaping the industry and enhancing its competitiveness.
Integrating artificial intelligence (AI) in the nuclear energy market presents significant challenges that must be addressed to guarantee the flourishing adoption of AI technologies in this critical industry. Safety concerns are paramount, given the potential risks associated with AI systems. A primary challenge is ensuring that AI is implemented securely without introducing vulnerabilities or false alarms.
The nuclear industry operates under stringent regulatory frameworks to safeguard plant safety and environmental protection. Implementing AI in this environment necessitates navigating complex regulatory processes and potentially amending existing regulations to accommodate AI systems, requiring meticulous attention.
The acceptance of AI in the nuclear energy market varies across different parts of the world. North America strongly focuses on enhancing safety and extending the operational life of ageing nuclear facilities through AI-driven solutions. The region is home to established nuclear energy companies like General Electric and Westinghouse, which actively incorporate AI technologies for predictive maintenance and real-time monitoring to improve safety and operational efficiency. Meanwhile, in the Asia Pacific, increasing energy demands and a growing emphasis on sustainability drive interest in nuclear power.
AI is used to optimize plant operations and enhance safety measures in countries like China and Japan. Furthermore, Europe is fostering international collaborations and research initiatives to develop AI applications for the nuclear sector, aiming to improve nuclear energy’s competitiveness and environmental sustainability. These regional trends reflect the global recognition of AI’s potential in the nuclear energy market, with each region adapting AI solutions to meet its unique energy needs, safety standards, and environmental goals.
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Segmentation Of AI In Nuclear Energy Market –
- Plant operations
- Nuclear waste management
- Radiological protection
- Nuclear safety and security
- Nuclear medicine.
- Deep learning (DL)
- Machine learning (ML)
- Natural language processing (NLP)
- Reinforcement learning (RL)
- Robotics and automation
By End User-
- Nuclear power plants
- Nuclear research facilities
- Nuclear regulatory authorities
- Healthcare (for nuclear medicine applications)
- The US
- The UK
- Rest of Europe
- South Korea
- Southeast Asia
- Rest of Asia Pacific
- Rest of Latin America
Middle East & Africa-
- GCC Countries
- South Africa
- Rest of Middle East and Africa
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