AI–Nuclear interface: A new frontier of existential risk

The world is entering an era where the pinnacle of human innovation could be the instrument of its own extinction. As Artificial Intelligence (AI) promises to revolutionize everyday life, its growing integration into nuclear decision-making systems is igniting a race that is as lethal as it is unpredictable. Today, a critical question has emerged: should the decision to deploy weapons capable of annihilating civilization ever be shaped, even indirectly, by algorithms?

Driven by concerns over strategic parity with Russia and China, the United States has renewed its focus on modernizing its nuclear posture. Similar trajectories are increasingly visible across other nuclear-armed states, particularly in decision-support, surveillance, and early-warning systems. This momentum has effectively revived a nuclear arms race, but with a dangerous digital dimension layered onto existing strategic rivalries. Existing arsenals are already sufficient to cause civilizational collapse. Introducing AI into early-warning, targeting, and response systems does not enhance stability.

Instead, it compresses decision-making time, amplifies uncertainty, and increases the probability that miscalculation becomes irreversible.

A major source of global concern is Russia’s claimed development of the “Burevestnik”, a nuclear-powered cruise missile reportedly capable of travelling up to 15,000 kilometers. Beyond its range, the more troubling aspect is the possibility of AI-assisted navigation and targeting. If such systems evade detection for extended periods, adversaries are forced into worst-case assumptions. This dynamic accelerates crisis instability, where the fear of being too late outweighs the discipline of being correct.

The danger lies in the difference between human judgment and algorithmic processing. Even in the direst circumstances, human leaders retain the capacity to pause, verify information, and weigh long-term consequences. An AI system by contrast, operates strictly within the boundaries of its programming, even when the real world is ambiguous.

Nuclear crises are rarely shaped by clarity; they unfold amid incomplete data, technical anomalies, political pressure, and misinterpreted signals. In such conditions, an algorithm may misclassify a radar glitch, a satellite error, or cyber interference as a genuine attack.

History offers sobering lessons. In 1983, Soviet officer Stanislav Petrov questioned a false alarm generated by early-warning systems rather than immediately report an incoming missile strike. His decision prevented a potential nuclear catastrophe. In an AI-mediated command environment, that margin for human discretion may narrow. The “killing chain”—detection, assessment, and response—could operate at a pace that renders meaningful human intervention increasingly procedural rather than decisive.

The broader geopolitical landscape is already shifting. Alongside Burevestnik, Russia has developed the “Poseidon” nuclear-powered underwater drone. The United States and China, meanwhile, are investing heavily in AI-driven maritime surveillance, anomaly detection, and autonomous undersea systems. Even when states claim that AI is used primarily for simulations or non-operational testing, rivals have limited incentive to trust such assurances. In strategic environments defined by low trust and limited transparency, opacity itself becomes destabilizing.

Algorithmic bias further compounds the danger. AI systems are trained on data and assumptions shaped by institutional culture and strategic doctrine. If those assumptions emphasize threat anticipation or rapid escalation, algorithmic outputs may reinforce those tendencies. Over time, reliance on such systems risks eroding norms of restraint that have historically played a role in preventing nuclear conflict.

According to the SIPRI Yearbook 2025, Russia currently possesses an estimated 5,459 nuclear warheads, while the United States maintains approximately 5,177. China’s arsenal is assessed at around 600 warheads. These figures may already be outdated. Any classified developments involving artificial intelligence in nuclear systems—whether in warhead management, delivery platforms, or command-and-control integration—remain outside public accounting. The resulting lack of transparency complicates efforts to assess real capabilities and risks.

What must be done is neither mysterious nor optional. Nuclear command-and-control structures must preserve meaningful human judgment rather than ceremonial oversight. Clear boundaries are essential to ensure that no autonomous or semi-autonomous pathway shortens the distance between a warning signal and a launch decision. Transparency measures, crisis communication mechanisms, and confidence-building frameworks must evolve to address risks specific to AI-enabled systems.

The time to regulate the AI–nuclear interface is not after the first machine-accelerated crisis spirals out of control. It is now, while diplomacy still has space to function and while human judgment remains the final authority.