New Nuclear & AI

Posted: 26th August 2026

Generative AI systems such as ChatGPT have become famous for their ability to learn the patterns behind data to create realistic new variations of existing data. Well known applications range from auto-generated translations to entire books co-authored by machine. What is less well known, however, is that recent advances in generative AI could also unlock the immense data resources across the energy industry to transform everything from regulatory compliance and maintenance to innovation and workforce skills. Today, workers in industries such as the nuclear power generation sector have to manually search millions of documents for records of everything from maintenance checks to design changes and stay abreast of rapidly evolving protocols and regulations. The data is often fragmented and employees typically lack a holistic overview of all the valuable information outside their specialist silos. The ability of generative AI systems to rapidly translate complex data into human-like text has the power to democratise knowledge and skills, drastically improving everything from learning and development to plant design and operational efficiency and safety. Nuclear power is expected be a key pillar of the energy transition and the industry is growing in response. Globally some 170 new plants are planned or under construction while old plants are being restarted or kept operating for longer. Yet, the industry’s growth could be jeopardised by a skills shortage exacerbated by an aging workforce and increasing early retirements. This, combined with a safety-conscious, conservative culture is stifling innovation, with the nuclear industry taking over a decade just to move from paper to digital records. The industry has also been slow to adopt new innovations such as AI, with nuclear workers the least likely of any energy sector to use AI in their current job role. This is leaving substantial technology resources significantly untapped. New advances in Large Language Models (LLMs) for example, which are trained on vast amounts of text to generate their own text, have the potential to help overcome many of these challenges and in turn, help speed the energy transition.

NS Energy 24th Aug 2026

https://www.nsenergybusiness.com/analysis/llms-and-the-nuclear-challenge/