AI in Nuclear Energy Market Report 2026

The artificial intelligence in nuclear energy market size has grown exponentially in recent years. It will grow from $3.86 billion in 2025 to $4.64 billion in 2026 at a compound annual growth rate (CAGR) of 20.4%. The growth in the historic period can be attributed to increasing focus on improving nuclear safety through real-time monitoring, rising demand for automation to reduce operational risks in nuclear plants, growing adoption of predictive maintenance to prevent equipment failures, increasing deployment of digital systems for optimizing plant performance, and rising need for efficient radiation detection and analysis.

The artificial intelligence in nuclear energy market size is expected to see exponential growth in the next few years. It will grow to $9.66 billion in 2030 at a compound annual growth rate (CAGR) of 20.1%. The growth in the forecast period can be attributed to growing investment in modernizing nuclear infrastructure with digital technologies, increasing need for high-accuracy monitoring solutions in next-generation reactors, rising adoption of ai-enabled simulation tools for fuel cycle optimization, growing reliance on autonomous inspection systems to enhance operational efficiency, and increasing government support for safe and advanced nuclear power development. Major trends in the forecast period include advancement in ai-based digital twins for reactor modeling, innovation in autonomous robotic inspection tools for hazardous environments, integration of machine learning algorithms to enhance radiation forecasting, advancement in intelligent control systems for small modular reactors, and integration of ai-enabled cybersecurity frameworks to protect nuclear assets.

The growing focus on safety and anomaly detection is expected to drive the growth of the artificial intelligence (AI) in nuclear energy market in the coming years. Safety and anomaly detection involves using advanced technologies to identify irregular patterns, equipment malfunctions, or operational deviations that could signal potential safety risks in nuclear facilities. This focus is increasing due to the need for real-time monitoring and proactive risk prevention to avoid equipment failures, radiation leaks, or unplanned shutdowns. AI in nuclear energy supports safety and anomaly detection by analyzing vast amounts of operational data in real time to predict potential issues before they occur, ensuring higher reliability and compliance with safety standards. For example, in July 2024, Microsoft, a US-based technology and cybersecurity company, reported processing 78 trillion security signals per day from the cloud, endpoints, software tools, and partner ecosystem in 2024, up from 65 trillion signals per day in 2023, to protect against digital threats and cybercriminal activity. Hence, the rising focus on safety and anomaly detection is fueling growth in the AI in nuclear energy market.

Major companies in the artificial intelligence (AI) in nuclear energy market are focusing on advanced technologies, such as nuclear-focused large language models, to streamline technical workflows, enhance knowledge discovery, and improve operational decision-making in highly regulated environments. Nuclear-focused large language models are AI systems capable of understanding, processing, and generating content specific to nuclear power operations, including regulatory, technical, design, and operational documentation. For example, in May 2024, NuclearN.ai, a US-based nuclear AI company, launched SPARK-mini, the first publicly available large language model trained specifically for the nuclear power domain. The model can be deployed on-premise, providing secure access for researchers, practitioners, and nuclear service providers with strict data security requirements. SPARK-mini powers NuclearN’s AtomAssist platform, enabling information discovery, Q&A, chat, and document preparation. Trained on millions of regulatory and technical records from the Nuclear Regulatory Commission’s Automated Dynamic Analysis of Mechanical Systems (ADAMS) Public Library, SPARK-mini can accurately interpret complex nuclear terminology and deliver actionable insights for nuclear operators and service providers.

In July 2025, Mirion Technologies Inc., a US-based provider of radiation detection and safety solutions, acquired Certrec Inc. for $81 million. Through this acquisition, Mirion Technologies aims to strengthen its presence across nuclear power facilities and expand its digital ecosystem by integrating Certrec’s licensing and compliance software to better serve the energy sector. Certrec Inc. is a US-based company offering regulatory compliance and reporting software that leverages AI-driven solutions for the nuclear energy industry.

Major companies operating in the artificial intelligence (AI) in nuclear energy market are 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., NuScale Power Corporation.

North America was the largest region in the artificial intelligence in nuclear energy market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the artificial intelligence (AI) in nuclear energy market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the artificial intelligence (AI) in nuclear energy market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Note that the outlook for this market is being affected by rapid changes in trade relations and tariffs globally. The report will be updated prior to delivery to reflect the latest status, including revised forecasts and quantified impact analysis. The report’s Recommendations and Conclusions sections will be updated to give strategies for entities dealing with the fast-moving international environment.

Tariffs have affected the artificial intelligence in nuclear energy market by increasing costs for imported sensors, industrial servers, radiation monitoring devices, and advanced computing hardware. The impact is most pronounced in nuclear utilities and research institutions in regions relying on cross border technology supply chains. To mitigate risks, operators are increasing local sourcing and forming long term supplier partnerships. In some cases, tariffs have accelerated domestic development of nuclear grade AI hardware and software solutions.

Artificial intelligence in nuclear energy refers to the use of advanced machine learning algorithms and data-driven models to improve the operation, safety, and efficiency of nuclear power systems. It enables predictive maintenance, real-time monitoring, and optimization of nuclear reactors by analyzing complex datasets generated during energy production. This technology helps enhance decision-making, reduce operational risks, and boost the overall performance of nuclear energy facilities.

The main components of AI in nuclear energy include software, hardware, services, data, and application programming interfaces (APIs) and middleware. Software consists of AI-driven platforms and algorithms designed to optimize nuclear energy operations, supporting tasks such as predictive maintenance, reactor control, fuel management, safety monitoring, and operational efficiency. Deployment modes include cloud-based and on-premises solutions. Technology types encompass machine learning, deep learning, computer vision, natural language processing, robotics and automation, among others. Applications include 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 more. Major end-users include nuclear power utilities and operators, engineering, procurement, and construction (EPC) firms, plant OEMs and vendors, regulatory bodies and safety agencies, research institutions and national labs, and service providers and third-party inspectors.

The artificial intelligence in nuclear energy market consists of revenues earned by entities by providing services such as operational efficiency consulting, simulation and modeling, cybersecurity solutions, data analytics services, and regulatory compliance support. The market value includes the value of related goods sold by the service provider or included within the service offering. The artificial intelligence in nuclear energy market includes sales of monitoring instruments, smart meters, data acquisition hardware, radiation detectors, automated testing equipment, and computing servers. Values in this market are ‘factory gate’ values, that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

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