Professor Lefteri H Tsoukalas of Purdue University studies AI as a catalyst and key enabler for the nuclear energy transition.
The emerging AI-energy nexus represents a critical juncture in the history of technology, requiring a fundamental and physically grounded policy framework. To address the unprecedented and rapidly growing energy demands created by artificial intelligence (AI), we argue that the world must commit to an immediate and planned transition to a nuclear paradigm. This is a monumental transition that AI itself is uniquely positioned to drive and enable.
Energy imbalance caused by AI
The nexus between AI and energy is defined by the rapid increase in energy consumption of AI infrastructure that will overwhelm the world’s power grids. This massive expansion is being fueled by data centers (AI server farms and supercomputer networks), which are rapidly becoming the largest component of future commercial energy consumption.
This demand is quantifiable and urgent. Thousands of new data center projects are expected to break ground in the United States in 2025, and the sector’s total energy consumption is expected to triple by 2028. This energy deficit will require an annual output equivalent to approximately 77 new 1000 MWe reactors by 2028. This demand is so huge that it is now a ‘keep pace challenge’ for continued technological growth, including transport electrification and industrial reshoring.
Promethean limits and the need for energy density
The history of human energy hinges on two great revolutions: Promethean and nuclear power. The Age of Prometheus, based on the mastery of fire and the chemical energy of molecular bonds (fossil fuels, and now most renewable energy using natural gas), is now reaching its physical limits. Policies promote a “green energy transition” to renewable energy, but this framework is fundamentally constrained by low energy density, intermittency, and high entropy production.
Meeting the world’s energy needs entirely with existing renewable energy and storage would require land use, resource extraction, and trillions of dollars of grid infrastructure that are not functionally viable. The scale just doesn’t match your needs.
Against this background, the only viable energy sources are those that can be co-located depending on demand. This is the role of the first generation of nuclear innovation: small modular reactors (SMRs) and microreactors (MRs). These advanced nuclear fission reactors can be installed directly next to data centers or heavy industrial facilities, providing both electrical power and low-temperature process heat from their thermal output. This full-stack option enables decarbonization of hard-to-abate industrial sectors without prohibitively expensive process redesign.
Nuclear imperatives: innovation, scale and fuel production
Nuclear energy transfer harnesses the vast energy of atomic nuclei, releasing approximately 200 MeV with each fission event. This is millions of times more energy per unit mass than coal. Importantly, unlike the Prometheus transition, nuclear power systems (both fission and fusion) can be designed to produce new fuel as they generate electricity.
The urgent need for nuclear innovation
The main barriers to nuclear power are economics and policy, not physics. The industry has historically been defined by costly, bespoke, multi-gigawatt projects, resulting in high levels of cost of electricity (LCOE) and overnight construction cost estimates (OCCE). The path to affordability depends entirely on intentional innovation, a concerted effort to move nuclear construction from one-off mega-projects to factory-based, mass-produced products.
This innovation is manifested in the modular, small-scale design of SMR and MR, allowing you to:
Factory production: Achieve economies of quantity and significantly reduce capital costs. Enhanced safety: Utilizes passive safety systems that rely on natural laws rather than active mechanical components. Regulatory streamlining: Necessary policies must be driven towards technology-inclusive licensing to accelerate adoption and reduce regulatory delays.
Breakthroughs in fuel breeding and fusion
The atomic paradigm is essentially self-sustaining through fuel multiplication. This process converts globally abundant fertile materials (such as uranium and thorium) into superior fissile fuels such as Pu-239. This important ability not only generates new fuel along with energy production, but perhaps more importantly, converts spent fuel (or “nuclear waste”) into an energy resource that can power humanity for thousands of years.
Additionally, recent advances, such as the achievement of net energy gains by the National Ignition Facility (NIF) and the rapid development of high-temperature REBCO magnets by private ventures, are making fusion commercially viable. These scientific milestones demonstrate that nuclear fusion, once a distant dream, could become a commercially viable energy option by the mid-21st century, further strengthening the mission of nuclear power.
AI as a catalyst and enabler
AI itself is the engine that will accelerate the atomic transition. It provides advanced capabilities needed not only for grid optimization and reactor control, but also for managing global nuclear safety.
Energy ecosystem optimization: AI provides advanced capabilities needed for grid stability, enabling real-time control and dynamic partitioning into self-healing energy ecosystems to coordinate the operation of numerous distributed energy sources, including micro-reactors. Non-proliferation and safety: AI enables “cradle-to-grave” monitoring of nuclear materials and processes. This unprecedented oversight will strengthen nonproliferation objectives and help prevent nuclear chaos. In this sense, AI could be an essential technology enabling the widespread use of nuclear power, just as radar technology enabled the reliable development of global civil aviation.
The marriage of nuclear energy transition (driven by high energy density and innovation) and AI-enabled optimization is the only physically and economically viable path to sustaining human technological progress and meeting the extraordinary demands of AI and energy collaboration.
References
Tsoukalas, LH, Energy Transitions: The AI-Energy Nexus, World Scientific, Singapore, 2026.
This article will also be published in the quarterly magazine issue 24.
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