Global Trends Overview: The Fast-Paced Development of the Artificial Intelligence (AI) Market in Nuclear Energy

The integration of artificial intelligence (AI) into the nuclear energy sector is ushering in a transformative era of innovation and efficiency. As the industry evolves, AI technologies are being harnessed to optimize operations, enhance safety, and support sustainable development. Let's explore the current market outlook, key players, emerging trends, and segmentation within the AI in nuclear energy landscape.

Forecasted Market Size and Growth Potential of the AI in Nuclear Energy Market
The market for artificial intelligence in nuclear energy is poised for significant expansion, with projections estimating a value of $9.66 billion by 2030. This growth reflects a robust compound annual growth rate (CAGR) of 20.1%. Several factors contribute to this upward trend, including substantial investments aimed at modernizing nuclear infrastructure with advanced digital technologies. Additionally, the increasing demand for highly accurate monitoring solutions in next-generation reactors and the adoption of AI-powered simulation tools for optimizing fuel cycles also drive market growth. Growing reliance on autonomous inspection systems to boost operational efficiency, coupled with rising governmental support to promote safe and advanced nuclear power, further fuels the market's expansion. Key developments to watch include the advancement of AI-based digital twins for reactor modeling, autonomous robotic inspection innovations suited for hazardous environments, the use of machine learning to improve radiation forecasting, intelligent control systems designed for small modular reactors, and the deployment of AI-enabled cybersecurity frameworks to safeguard nuclear assets.

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Main Firms Leading the AI in Nuclear Energy Market
Several prominent companies are shaping the AI in nuclear energy market globally. These include Rosatom State Atomic Energy Corporation, Palantir Technologies Inc., Cameco Corporation, Hitachi Ltd., Veolia Nuclear Solutions, Honeywell International Inc., Siemens Energy AG, GE Vernova Inc., Asea Brown Boveri Ltd., Mitsubishi Heavy Industries Ltd., Toshiba Corporation, Jacobs Solutions Inc., Framatome SAS, BWX Technologies Inc., Mirion Technologies Inc., Assystem S.A., Kinectrics Inc., TerraPower LLC., X-energy LLC., and NuScale Power Corporation.
A notable recent development occurred in July 2025, when Mirion Technologies Inc., an American radiation detection and safety firm, acquired Certrec Inc. for $81 million. This acquisition aims to strengthen Mirion's presence across nuclear power facilities by expanding its digital ecosystem. Certrec, a US-based company specializing in regulatory compliance and reporting software powered by AI, enhances Mirion's ability to serve the nuclear energy sector more effectively through integrated licensing and compliance solutions.

Innovations and Emerging Trends Shaping AI in Nuclear Energy
The AI in nuclear energy industry is increasingly embracing cutting-edge technologies tailored specifically to the sector's unique needs. Among these, nuclear-focused large language models are gaining traction for their ability to streamline complex technical workflows, enhance knowledge discovery, and support decision-making in highly regulated environments. These AI systems can understand, process, and generate content closely tied to nuclear power operations, encompassing regulatory, technical, design, and operational documentation.
For instance, in May 2024, NuclearN.ai, a US-based AI company specializing in nuclear technology, launched SPARK-mini, the first openly accessible large language model specifically trained for the nuclear power domain. Designed to operate on-premise for secure access, SPARK-mini caters to researchers, practitioners, and nuclear service providers requiring strict data security. This model powers NuclearN's AtomAssist platform, offering tools for information discovery, Q&A, chat, and document preparation. It has been trained on millions of regulatory and technical records sourced from the Nuclear Regulatory Commission's Automated Dynamic Analysis of Mechanical Systems (ADAMS) Public Library, enabling it to accurately interpret complex nuclear terminology and provide valuable insights for operators and service providers.

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Detailed Segmentation of the AI in Nuclear Energy Market
This market is divided into multiple segments that capture the breadth of AI applications within nuclear energy. The report categorizes the market by:
1) Component - including Software, Hardware, Services, Data, Application Programming Interfaces (APIs), and Middleware.
2) Deployment Mode - Cloud-Based and On-Premises solutions.
3) Technology - encompassing Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Robotics and Automation, along with other emerging technologies.
4) Application - covering Asset Management and Predictive Maintenance, Reactor Operation and Control, Fuel Management and Waste Reduction, Safety and Security Monitoring, Radiation Monitoring and Dose Management, Supply Chain and Project Management, and other relevant uses.
5) End User - comprising Nuclear Power Utilities or Operators, Engineering, Procurement and Construction (EPC) firms, Plant Original Equipment Manufacturers and Vendors, Regulatory Bodies and Safety Agencies, Research Institutions and National Laboratories, as well as Service Providers and Third-Party Inspectors.

Subcategories include:
- Software types such as AI Modeling Software, Predictive Maintenance Software, Reactor Simulation Software, Data Analytics and Visualization Tools, Safety Monitoring Software, Workflow Automation Platforms, and Cybersecurity Software specifically for nuclear systems.
- Hardware components like Sensors (temperature, pressure, radiation, vibration), Edge Devices and Controllers, AI Chips and Processors, Robotics Hardware, Monitoring and Inspection Devices, plus Industrial Servers and Storage Units.
- Services encompassing Consulting, System Integration, Predictive Maintenance, Training and Support, Managed AI Services, and Installation and Commissioning.
- Data categories include Operational Data, Environmental and Radiation Data, Safety and Compliance Data, Predictive Maintenance Datasets, Historical Reactor Performance Data, and Real-Time Monitoring Data Streams.
- APIs and Middleware involve Integration APIs, Data Exchange APIs, Machine Learning Model APIs, Security and Authentication Middleware, Cloud Connectivity Middleware, and Workflow Orchestration Middleware.

This thorough segmentation reflects the complex and multifaceted nature of AI technology deployment in nuclear energy, addressing the varied needs of the industry from technology providers to end users.

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