A soldier who fires on a target must be able to reason “why” afterward. Similarly, a commander who authorizes a strike must be able to justify that decision to superiors, at times to lawyers, and possibly to the public. If an algorithm makes these decisions, how is the reasoning understood when it is not understood by the engineers who built it? Judging from how military technology has advanced, this is not hypothetical. It is the situation many militaries already face as artificial intelligence (AI) takes on a growing role in identifying threats, and even recommending or engaging targets. The usual conversation about military AI focuses on speed, power, and who can compute faster or strike first. But a quieter, more important question emerges alongside it. Which systems can justify their decisions when lives, laws, and legitimacy are on the line? Quantum AI, an unlikely and still unproven contender, is being explored as a possible answer. 

What Quantum AI Actually Is 

Quantum computing provides a fundamentally different approach to processing information than classical computer methods. Rather than relying solely on classical computational methods, quantum computers exploit quantum mechanical phenomena such as superposition, entanglement, and interference to solve certain classes of problems more efficiently than conventional computers. Where Artificial intelligence is the set of processes that let computers recognize patterns and make predictions with limited human guidance. Quantum AI combines the two, using quantum computers to conduct calculations while classical AI systems manage the rest of the process. 

Militaries are interested in this combination for several reasons, including faster logistics planning and better analysis of satellite imagery. Much of the focus on quantum AI has been on speed, optimization, and solving problems that challenge classical computers. But researchers are increasingly focused on a different possibility, one that has nothing to do with how fast a system can think and everything to do with how it decides and whether one can trust its decisions. 

The Problem With Black Boxes 

Most modern AI systems, particularly the neural network models that power image recognition and predictive analysis, function as what experts call a black box. The system takes in information and produces an answer, but its internal reasoning is buried in millions of numerical values that even its designers cannot fully interpret. For everyday uses like recommending a movie or predicting traffic, this opacity is harmless. In a military context, it is not. If an AI system flags an object in satellite imagery as a probable weapon launcher or recommends that a target meets the legal criteria for engagement, someone must eventually explain the decision reasoning. This is because militaries operate under rules of engagement and international humanitarian law, both of which require distinguishing combatants from civilians and justifying the use of force. If an investigation follows a strike, whether from a military tribunal, a human rights body, or a domestic court, “the algorithm decided” may not be an acceptable answer. Accountability requires a trail of reasoning and legal justification that a human being can follow and defend. 

This is not a distant, theoretical scenario. Militaries around the world are already integrating AI into surveillance, target prioritization, and threat classification systems. As these tools take on more responsibility, the gap between what they decide and what humans can explain grows wider. That gap creates legal exposure, operational risk, and serious human accountability problems for any military that wants to claim its use of force is lawful and proportionate. 

Why Quantum AI Might Offer a Way Out 

This is where quantum AI enters the conversation, not for its speed, but potentially to provide insight into AI decision making. Some researchers argue that certain quantum AI models, particularly a type known as gate-based models, organize information in ways that more closely mirror the actual structure of the problem being solved. Rather than compressing logic into an impenetrable web of numerical weights, these models preserve the structure that allows one to trace back to a specific input or condition that led to the result. In theory, this would allow investigators to follow a clearer path from data to decision, something today’s AI engines cannot offer. 

If this promise holds up, it will matter. A military that can show step-by-step why a system chose a target is in a far stronger position to defend that decision legally and ethically. It also strengthens public trust, both domestically and internationally, at a time when the use of autonomous and AI assisted weapons is under growing scrutiny from human rights organizations and international bodies. In this framing, the race for military AI dominance is not only about who can build the fastest or most powerful system. It becomes a race to build systems that are defensible. These systems must withstand the scrutiny of a courtroom, a parliamentary inquiry, or an international tribunal. 

A Promising Idea, Not a Proven One 

It would be a mistake to overstate that this capability is currently accessible. The idea that quantum AI offers built-in decision recovery is still unproven, not an established capability. Techniques used to explain classical AI decisions, tools such as LIME and SHAP, are only beginning to be adapted for quantum models. Early results are encouraging in narrow research settings, but no military or independent certification body has yet accepted quantum-generated decision recovery as sufficient evidence in a legal or operational context. The honest way to describe this field today is as a promising hypothesis worth serious investment, not a solved problem ready for deployment. Overselling it risks the same trap that has plagued classical military AI, where systems are fielded faster than the frameworks needed to hold them accountable. 

Conclusions 

The common denominator in military technology has been about speed. It is about who can evaluate fastest, be more decisive, and often strike first. Computers systems help drive these and AI plays a key role. Quantum AI’s most valuable military application may ultimately have little to do with either. If it can genuinely offer clearer, more transparent reasoning behind life-and-death decisions, it would address one of the most serious gaps in how militaries currently use it. This deserves considerable research attention and scrutiny in equal measures.  

The technology that ultimately proves most valuable on future battlefields may not be the one that thinks the fastest. It may be the one that can provide an answer when someone finally asks why.  

Maheen Butt is a Lahore-based researcher and strategic communications professional conducting research primarily on foreign affairs. She is a Mphil graduate of International Relations from Kinnaird College for Women, and her work focuses on global affairs, emerging technologies mainly on increasing use of AI in military affairs, and defense studies. The Author’s opinions are their own.

Explainability, Not Speed, Will Define the Next Military AI Race was originally published on Global Security Review.

China’s expanding force of dual-capable missiles is creating a growing source of ambiguity in U.S.-China deterrence. The People’s Liberation Army Rocket Force (PLARF) operates conventional and nuclear missile forces, including systems capable of supporting either mission. Beijing continues to declare a no-first-use policy, and there is no straightforward evidence that Chinese leaders have deliberately lowered the threshold for nuclear employment. The more consequential concern is operational. During a crisis, U.S. forces may track a Chinese missile unit without knowing whether it is supporting a conventional or nuclear mission. A conventional strike against such a system could therefore be interpreted in Beijing as an attempt to degrade China’s nuclear deterrent.

Nuclear-Conventional Ambiguity in the PLARF

China’s stated nuclear posture remains comparatively restrained. Beijing describes its nuclear force as defensive and intended for retaliation and Fiona Cunningham and M. Taylor Fravel find that Chinese strategists have viewed nuclear escalation as difficult to control once nuclear weapons are employed. Dual-capable systems therefore should not be treated as evidence that China intends earlier nuclear use. They do, however, complicate an adversary’s ability to distinguish conventional and nuclear operations.

The DF-26 provides the clearest example. The road-mobile intermediate-range ballistic missile can threaten Guam and conduct conventional land-attack, anti-ship, and nuclear missions. The U.S. Department of Defense assesses that the DF-26 was designed to allow rapid changes between conventional and nuclear warheads. Identifying a launcher, therefore, does not necessarily reveal its assigned mission. James Acton describes this as pre-launch ambiguity. An opponent may know the missile launch system while remaining uncertain whether it is configured for conventional or nuclear use.

China’s command arrangements reduce some risk but do not eliminate this ambiguity. A 2024 China Aerospace Studies Institute assessment finds that nuclear launch authority remains centralized under the Central Military Commission, while conventional PLARF forces can operate through joint campaign command structures. David Logan likewise argues that Chinese nuclear and conventional forces are less entangled than some assessments suggest, although risks remain around dual-capable systems. Organizational separation may reduce unauthorized-use risk, but it does not allow U.S. decision-makers to identify a dispersed unit’s mission with confidence.

Pathways to Inadvertent Escalation

The greatest escalation risk arises when U.S. conventional operations threaten assets that China associates with the survivability of its nuclear forces. In a

Taiwan conflict, U.S. forces could have strong incentives to strike PLARF launchers, sensors, communications systems, or command nodes supporting conventional missile attacks. Caitlin Talmadge has shown that such operations could also affect systems relevant to China’s ability to retaliate with nuclear weapons. Beijing could therefore struggle to determine whether U.S. attacks were limited conventional operations or the opening phase of a broader counterforce campaign.

China might respond by dispersing nuclear units, increasing readiness, or altering command-and-control procedures to preserve its retaliatory capability. Although Beijing could view those steps as defensive, U.S. officials might interpret the same activity as preparation for nuclear employment. Acton’s research on escalation through entanglement shows how attacks on systems supporting both nuclear and conventional missions can produce this kind of misread warning. Actions taken to preserve deterrence on one side can therefore appear threatening to the other.

The literature cautions against treating this pathway as inevitable. Wu Riqiang concludes that the overall probability of inadvertent U.S.-China nuclear escalation remains extremely low, citing the likely survivability of much of China’s nuclear force and strong controls over nuclear use. Logan similarly finds less entanglement than some earlier studies implied. These findings weaken claims that conventional conflict would naturally progress toward nuclear use, but they do not remove the narrower concern that dual-capable forces can make wartime actions harder to interpret.

The scale of that problem may grow as China expands its missile forces. The 2026 Nuclear Notebook estimates approximately 300 DF-26 launchers across eight brigades, while noting that not all are assigned nuclear missions. Henrik Staalhane Hiim, M. Taylor Fravel, and Magnus Langset Troan describe an “entangled security dilemma” in which measures to improve security taken by either China or the U.S. can increase the other side’s concern about nuclear-force survivability. Ambiguity can therefore shape broader perceptions of intent during a crisis.

Implications for Strategic Stability

U.S. planning should treat nuclear-conventional ambiguity as both a targeting and crisis-management problem. Before striking a PLARF launcher, sensor, communications system, or command node, planners should assess whether the target may also support nuclear operations and whether its destruction could be interpreted as part of a disarming campaign. This does not require excluding dual-use targets from conventional plans, but it does require weighing military value against escalation risk.

Risk reduction also requires mechanisms that can clarify intent during a crisis. Missile notifications, protected communication channels, and clearer procedures for signaling changes in nuclear readiness could reduce uncertainty without revealing sensitive operational details. China’s advance notification before its September 2024 Pacific ICBM test demonstrates that limited transparency around strategic missile activity is possible. U.S. and allied exercises should also include ambiguous PLARF movements and attacks on dual-use systems so that decision-makers confront these risks before an actual crisis.

China’s dual-capable missiles do not demonstrate that Beijing has abandoned no first use or deliberately lowered its nuclear threshold. The more important concern is that this threshold may become harder for an adversary to identify during conventional conflict. If U.S. operations threaten assets associated with China’s nuclear deterrent, defensive measures taken by either side could be interpreted as preparation for escalation. Managing that uncertainty will become increasingly important to strategic stability in the Indo-Pacific.

Peyton Mayer is a doctoral student in Business Administration at Edgewood College whose research spans finance, Chinese military strategy, and international security. He is a U.S. Army veteran with six years of military intelligence experience and a professional background in trade compliance and export control policy. His published scholarship examines PLA doctrine and Indo-Pacific security, with broader interests in economic statecraft, emerging technologies, and strategic competition. The views expressed in this article are the author’s own.

China’s Dual-Capable Missiles and Inadvertent Nuclear Escalation was originally published on Global Security Review.