The Department of Energy (DOE) has unveiled specifications for 26 artificial intelligence (AI) challenges under its Genesis Mission, aimed at transforming how power plants are designed, licensed, built, and operated. These initiatives focus on nuclear plant deployment timelines, grid interconnection bottlenecks, data center load integration, fusion commercialization, and subsurface energy recovery. Launched through an executive order on November 24, 2025, the Genesis Mission aspires to double the productivity and impact of American science and engineering within a decade by integrating AI across the DOE’s 17 national laboratories and decades of operational data.
The Genesis Mission is described by the DOE as a national discovery platform designed to build the world’s most powerful scientific infrastructure. This ambitious initiative will connect supercomputing, AI systems, emerging quantum technologies, and large-scale scientific instruments, fostering collaboration between scientists and intelligent systems capable of reasoning, simulating, and experimenting. The primary objective is to generate high-fidelity data, train physics-informed AI models, and expedite the transition from scientific hypotheses to engineering applications across energy, materials, and security domains.
To jumpstart this effort, the DOE has signed non-binding memorandums of understanding with 24 organizations—including Amazon Web Services, Google, Microsoft, NVIDIA, and OpenAI—on December 18, 2025. This collaboration aims to explore AI applications across various sectors, including nuclear energy and grid modeling. Furthermore, the DOE has established the Genesis Mission Consortium, a partnership that facilitates coordinated access to national lab supercomputers, datasets, and experimental facilities.
The 26 challenges, detailed in a 28-page technical document released on February 12, outline the DOE’s vision for AI-driven breakthroughs. Specific targets include reducing nuclear deployment schedules by half, cutting operational costs by over 50%, expediting grid interconnection decisions by up to 100 times, and developing fusion energy digital twins that integrate plasma physics and materials science in real time. “These 26 challenges are a direct call to action to America’s researchers and innovators to join the Genesis Mission and deliver science and technology breakthroughs that will benefit the American people,” said Michael Kratsios, assistant to the president and director of the White House Office of Science and Technology Policy. He also expressed hope for expanding the list of challenges across federal agencies to enhance the mission’s impact.
A significant focus of the Genesis Mission is on nuclear systems, with ten of the 26 initiatives targeting this sector. The challenges encompass commercial reactor deployment, nuclear facility digitization, site remediation, and the modernization of the National Nuclear Security Administration (NNSA) enterprise. The DOE aims to accelerate nuclear deployment timelines, incorporate digital models into operations, expand experimental throughput, and enhance data infrastructures across civilian and defense facilities.
The agency emphasizes the use of digital twins, surrogate modeling, explainable AI workflows, and multimodal data integration to streamline processes and improve system reliability. By applying AI, the DOE seeks to reduce iteration cycles in design, licensing, production, and operation, with a target of at least double the schedule acceleration for nuclear power development and more than 50% reduction in operational costs.
In addressing environmental liabilities, the DOE plans to utilize multimodal AI models trained on extensive cleanup data to expedite the treatment and remediation of legacy sites, potentially unlocking contaminated areas for energy infrastructure reuse. The digitization of over eight decades of legacy nuclear test records is also in the works, enhancing modeling and safety validation efforts.
Beyond nuclear energy, the Genesis Mission extends into grid infrastructure, aiming to address challenges in transmission planning, interconnection processing, and data center integration. As the demand for electricity surges due to data centers and electrification, the DOE aims to reduce planning and operational uncertainties through AI-driven analytics and simulation tools. The goal is to achieve “20-100x faster decision-making” and improve electricity cost and reliability by at least 10%.
The initiative also seeks to enhance the United States’ leadership in data center development, viewing it as crucial for winning the AI race while ensuring secure and reliable energy supply. Various AI tools will be employed to de-risk advanced data center technologies and optimize their integration into the grid. Additionally, the DOE plans to develop AI capabilities to predict water availability, tackling challenges across the hydrologic cycle that influence energy production.
Looking ahead, the Genesis Mission aims to accelerate the delivery of fusion energy, enhance subsurface energy resource recovery, and secure the supply of critical minerals. By integrating multiple data sources into AI-driven models, the DOE seeks to improve efficiency and reduce costs in unconventional resource extraction.
The overarching ambition of the Genesis Mission is to redefine the scientific and engineering landscape across energy and security systems. By building reasoning engines and integrated modeling platforms, the DOE is positioning itself to support substantial advancements in technology and infrastructure, ultimately aiming for a more resilient and efficient energy future.
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