Google and Westinghouse Electric assert that their collaboration on AI technologies promises to revolutionize nuclear reactor construction in the US, addressing energy demands accelerated by growing AI applications.

This innovative approach, announced in July, targets improvements in construction timelines and budgeting, using digital twins and AI optimization tools.

Westinghouse is on track to deploy ten more large reactors, backed by an $80 billion US government initiative to meet AI’s energy demands.

Construction costs are often unpredictable, fueled by lengthy timelines and a diminishing pool of expertise due to a pause in new builds over recent decades.

To mitigate these risks, the partnership is leveraging AI-driven platforms to streamline construction tasks, accompanied by WNEXUS digital twin technology—improving predictability and efficiency.

Media presentations by Westinghouse demonstrated how AI models optimize schedules, react to supply chain hiccups, and predict potential setbacks.

Initial trials revealed substantial cost savings and time efficiency—vastly improving traditional manual planning.

While the functionality is noted, skeptics question if AI is necessary for such optimizations.

Despite this, Westinghouse confirms the platform’s transition from prototype to application, forecasting operational deployment of reactors within five to seven years.

In parallel, Schneider Electric has disclosed a similar AI-driven system aiming to enhance efficiency by unifying building and energy management into a cohesive ecosystem.

Their ‘EcoStruxure Foresight Operation’ promises cost and time savings, available for early adopters by late 2026, offering further opportunities for AI to impact infrastructure.