As the world gears up for the 2026 Nuclear Non-Proliferation Treaty (NPT) Review Conference, a new and multifaceted factor is complicating the global strategic calculus: Artificial Intelligence (AI). The “nuclear-AI nexus” has evolved from a niche technical interest to a prominent feature in global security discussions, with implications for every aspect of the NPT’s three pillars: non-proliferation, disarmament, and peaceful uses of nuclear energy. However, as experts recently cautioned at the “Atoms for Algorithms” webinar, we need to cut through the speculative “AI hype” to ensure this technology remains a means for peace, not an avenue for unintentional escalation.

To regulate the nuclear-AI connection, we first need to understand the technology. As a United Nations Institute for Disarmament Research researcher, Dr. Yasmina Fina suggests, AI is not a monolithic entity, but a “construct” and a “system of systems,” made up of code, software, data, hardware, and sensors. It is a system used to fulfill certain functions, not a threat capable of usurping human decision-making. The risk is the “speed and scale” of AI, which can have myriad implications for performance and strategy. Moreover, Fina warns that comparing nuclear governance to AI governance is unhelpful because the technologies are not the same; nuclear materials are limited and tangible, whereas AI is ubiquitous and digital.

In the context of non-proliferation, AI is touted as a game-changing verification tool. The International Atomic Energy Agency (IAEA) could potentially use “AI agents,” semi-autonomous machines capable of processing large data streams and satellite images to verify the accuracy of declarations by states at a pace humans cannot match. However, Dr. Ian Stewart, Executive Director of the CNS Washington, states that AI will not help states develop nuclear weapons they could not otherwise build, for two physical reasons: AI cannot “magic up” fissile material, and there is no evidence that large language models can transfer the “tacit knowledge” necessary for weaponization.

When it comes to AI and nuclear weapons, political concerns are high. States have been reluctant to allow the IAEA to use open-source data or “black box” algorithms. Should an AI detect an event, the absence of “explainability” or how the machine arrived at its decision could lead to a crisis of political legitimacy for the safeguards system.

The most fraught part of the nexus is disarmament. We are now seeing a “race to adopt” AI in military strategies due to the perceived speed advantage it offers. AI can speed up threat identification and data integration, potentially freeing up more time for decision-making (or, on the other hand, reducing decision-making cycles to the point that humans are simply rubber-stamping decisions).

Aliche Sultini, senior research lead at the Rhode Island School of Design, explains that AI systems create new levels of uncertainty. If a state cannot grasp how an adversary’s AI operates in its decision-making, it might fall into worst-case scenarios, reinforcing alert postures that prevent disarmament. To support disarmament, AI must be used to enhance technical verification and confidence, not to shorten the path to war. Possibly the most disruptive aspect of this interaction is the NPT’s third pillar: peaceful nuclear energy applications. According to Mr. Shota Kamishima of the IAEA, an “affinity” is emerging between nuclear power and AI. We are now moving into a world where energy-hungry AI data centers need the clean, scalable, and reliable power offered by nuclear power, and where nuclear generation and maintenance are improved through AI.

This alliance is especially important for the rollout of Small Modular Reactors (SMRs), for which AI-optimized construction schedules and supply chains are critical. By enhancing predictability and avoiding cost overruns, a major issue for nuclear construction, AI could make nuclear projects more “bankable” and thus more attractive for the global shift towards clean energy. Despite technological progress, the experts agree: human responsibility is essential. Whether it is a safeguards inspector at the International Atomic Energy Agency (IAEA) or a human commander in a nuclear-armed nation, humans are the “last line of defence”.

“Black box” systems are incompatible with a strong safety culture. Governance policies must ensure that AI is implemented with transparency, traceability, and “explainability”. We must also be alert to the potential for AI to be employed by “agents” to monitor sites, which could result in disinformation and the distortion of threat perception through “anomaly detections.” As the 2026 Review Conference draws near, policymakers’ mission should be to “denoise.” Nuclear policy decisions must not be based on science fiction or fear of competition. Rather, we should prioritize “lower stakes” opportunities where AI can help us now, such as employing AI agents to navigate the overwhelming output of the NPT process — making it searchable and highlighting inconsistencies in delegation positions.

The relationship between nuclear and AI is not a bug to be fixed with more software, but a circumstance to be managed by the international community. By prioritizing evidence-based policy and law, human-in-the-loop systems, and the common ground of the peaceful “Atoms for Algorithms” alliance, we can ensure that the digital revolution supports, rather than undermines, the global nuclear order. In the end, the fate of the NPT will not be determined by algorithms, but by human intelligence.

Muhammad Shahzad Akram is a Research Officer at the Centre for International Strategic Studies, AJK. He holds an MPhil in International Relations from Quaid-i-Azam University, Islamabad. He is an alumnus of the Near East South Asia (NESA) Centre for Strategic Studies, National Defence University (NDU), and Washington, DC. His expertise includes cyber warfare and strategy, arms control, and disarmament. Views expressed in this article are the author’s own. 

Navigating the AI and Nuclear Nexus was originally published on Global Security Review.

In his speech before the United Nations General Assembly on 8 December 1953, President Dwight Eisenhower proposed – in paraphrased terms- that the atom bomb be given to those who can “strip its military casing and adapt it to the arts of peace.” Commonly referred to as the ‘Atoms for Peace’ speech, Eisenhower’s words launched an International Atomic Energy Agency and a generation of research into nuclear energy. Since the Cold War’s end, America’s relationship with nuclear power has attracted less attention, but the artificial intelligence (AI) revolution is forcing the United States to take a “new look” at its power grid.

Throughout 2025, senators, think tanks, and federal commissions likened the pursuit of better AI to the Manhattan Project that built the bomb. The vast sums of energy required to fuel such a task, however, may need its own project. Although President Donald Trump issued an executive order to reinvigorate the nuclear industrial base last May, these energy demands have been overshadowed by mounting fascination with the need to win a technology race with China. Considering U.S. public opinion toward atomic energy reached a near record high last year, there is no better time to expand the atom’s role in support of a coherent AI strategy.

The Dawn of a Nuclear Renaissance

During the early Cold War, nuclear technology drove a revolution in energy generation, powering everything from American cities to aircraft carriers. The skyrocketing number of AI data facilities in the United States, on the other hand, represents a potential crisis in energy consumption. When asked if the country can support the growing demands of its data centers, former President of Energy at Microsoft Brian Janous responded: “No. Utilities have not experienced a period of load growth in almost two decades and are not prepared for—or even capable of matching—the speed at which AI technology is developing.” The White House is exploring nuclear options to meet this challenge, yet its AI strategy released last July only mentions nuclear power briefly on page sixteen. This point deserves more attention.

America’s 94 reactors currently supply twenty percent of its energy with 97 gigawatts (GW), and the largest of them—located in Georgia—has a generating capacity of 4.5 GW. A recent Goldman Sachs report projected that the United States needs 47 GW of additional energy to power its AI centers through 2030—the equivalent of half the country’s nuclear capacity. Meta CEO Mark Zuckerberg has taken notice. In January, he secured a series of nuclear energy deals to power his 6.6 GW AI compound under development in Ohio. Companies that did not exist twenty years ago, such as Meta and OpenAI, could soon demand more than ten percent of the nation’s power grid, and the needs are only increasing.

Professor Joohyun Moon of Dankook University suggested recently that small modular reactors (SMRs)—automobile-sized nuclear batteries—could offer energy solutions for national security purposes in forward areas, such as the Indo-Pacific. Although the United States approved its first SMR design in 2022, it will not be operational until 2029, and only three SMRs are currently active in Japan, China, and Russia. Some studies cast doubt on the affordability of SMRs and question whether they would increase the risk of proliferation given the enriched uranium they need to operate. Moreover, these reactors only generate up to 300 megawatts, so while they could be useful in certain military contingencies, their output pales in comparison to the forecasted energy demands of AI.

Microsoft alone plans to build at least six data centers in Texas, each of which might consume enough energy to power more than 100,000 homes. Once Meta completes its Ohio facilities, it will have at its disposal energy reserves capable of powering roughly five million homes. Data centers in the United States could therefore devour nearly one quarter of the energy used by all American households before 2030. Without tighter integration between a national AI strategy and America’s nuclear sector, these numbers appear unsustainable.

Reversing the Ship

Going all in on nuclear energy also requires sustainable solutions to disposing of spent nuclear fuel and investing in high-capacity pressurized water reactors, but such solutions have not been forthcoming. President Barack Obama’s administration slashed funding for Nevada’s Yucca Mountain disposal facility in 2009 and suspended development of a nuclear waste repository there. Despite the first Trump administration’s requests to fund the disposal program between 2018 and 2020, Congress has yet to approve a plan. Any rapid increase in nuclear energy must be accompanied by a commensurate spike in disposal capacity.

In addition to these concerns, the United States closed thirteen reactors between 2013 and 2022, which has encouraged the current administration to reverse course. Last year, the Department of Energy pledged to quadruple America’s nuclear output from 100 GW to 400 GW by 2050. President Trump also issued an executive order to unburden AI companies of federal regulations and requested that they shoulder the burden of energy costs. The next step is to fuse these developments with a theory of success that explains what “winning” the AI race looks like and then align that vision with the energy requirements needed to support it—much of which will be nuclear.

The Long Shadow of 1945

In her historical account of U.S. citizenship during the early atomic age, Sarah Robey explains how “American culture has never truly partitioned the difference between ‘atoms for peace’ and ‘atoms for war.’” Over the last eighty years, these blurred lines generated both hyperbolic and apathetic responses to the nation’s relationship with nuclear power. The atom became equal parts provider and destroyer, but these conversations disappeared once public fears of a Cold War going hot subsided. With American optimism toward nuclear energy now sitting at 61 percent, there is no better time to reignite the discussion about the atom’s role in American society.

Despite the Trump administrations’ efforts to break ground on new nuclear plants over the last ten years, AI theory has outpaced the long-term realities of AI application, especially regarding the energy equation. Advancing AI research will force western societies to embrace the atom for the purpose of sustaining life rather than destroying it much as Eisenhower theorized in 1953. Accepting this reality by establishing deeper connections between energy generation and AI strategy is the first step toward finding sustainable solutions to AI’s role in war and peace.

MAJ Michael P. Ferguson, U.S. Army, is an instructor in the Department of History and War Studies at the United States Military Academy and a Ph.D. student at the University of North Carolina at Chapel Hill. Specializing in early Cold War history and nuclear strategy, he has published several dozen articles and columns on a wide range of topics. His latest research appeared in the International Journal of Military History and Historiography and Texas National Security Review. The views expressed here are those of the author and do not reflect the policies or position of the U.S. Army, the U.S. Department of War, or the U.S. Government.

Learning to Love the Atom Again: Why the Future of Artificial Intelligence is Nuclear was originally published on Global Security Review.