INTELLIGENT TECHNOLOGY: ENERGY TECHNOLOGY

In 2025, Westinghouse shared with the White House that it was building a plan to have 10 of its state-of-theart AP1000 nuclear reactors under construction by 2030, helping to address growing demands on the US energy grid from AI and other sources. meet nuclear’ s stringent regulatory and exportcontrol frameworks. They also developed Bertha, a generative AI assistant that instantly accesses 75 years of meticulous nuclear knowledge and documentation at Westinghouse.

Combined, these 10 reactors are powerful enough to electrify 7.5 million households or roughly the five largest US cities plus a few data centers.

To reach its ambitious goal, Westinghouse has partnered with Google Cloud to develop a custom AI-powered platform using specialised models from both Google and Westinghouse, itself a leader in AI for energy production, that helps optimise and accelerate reactor construction.

So far, early pilots of the platform have shown significant time and cost savings and the companies are also exploring ways for AI to help enhance nuclear operations and safety.

Dr Lou Martinez Sancho, Westinghouse’ s CTO and Executive Vice President of R & D and Innovation, framed the core idea as“ energy for AI and AI for energy.”

Nuclear is notable for offering clean, reliable power at an immense scale from a small footprint. With the United States projected to need 400 gigawatts of new power by 2040, a 32 % increase from current usage, conventional construction timelines are insufficient.

Google engineers were impressed that a 140-year-old company had quietly assembled the exact foundation needed to deploy AI securely in a heavily regulated environment.

The core AI innovation targets the construction process – historically 60 % of reactor costs. Until recently, construction management relied on spreadsheets and paper documents, leading to delays that cascaded across thousands of interdependent tasks. But with AI, Westinghouse turned decades of documentation to its advantage.

The new AI system combines the companies’ AI models and prediction tools with Westinghouse’ s WNEXUS, a 3D digital twin of its reactors. When combined with current and historic data, the system can predict bottlenecks, optimise construction task sequences, adjust staffing levels and account for external factors like supply chain constraints.

The optimisation technology for new reactor construction is built using a‘ technology brick approach’ Martinez Sancho said, meaning it has applications far beyond the initial project.

Westinghouse CEO Dan Sumner has stressed that AI-driven decision-making optimisation is essential to making nuclear power a viable investment for utilities and addressing energy urgency. A major factor in the partnership’ s success has been Westinghouse’ s AI readiness.

The company already established its own proprietary AI infrastructure, Hive, designed specifically to

The same AI tools are already being applied to reduce licensing processes and operations timing. By finding the fastest path through maintenance and refuelling tasks, the AI helps minimise reactor downtime.

Westinghouse views AI not as a tool for simple cost optimisation but instead as a catalyst for a revolution that transforms the energy sector and turns decades of documentation into an asset that accelerates progress. p

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