AI and defense manufacturing: what’s at stake between the US and China
Artificial intelligence is rapidly changing the conversation around defense manufacturing in the United States. What used to be mostly a debate about cost and efficiency has now become a direct national security issue, especially when you factor in the growing dependence on the China-linked supply chain.
On one side, the American arms industry has spent decades getting used to outsourcing production, chasing the lowest price and spreading suppliers across the globe. On the other, China has spent that same period building an aggressive industrial expansion strategy, using subsidies, regulatory advantages and cheap labor to gain ground in critical sectors such as metal casting, electronic components and strategic materials.
The result of this game is becoming clearer now that AI systems are being deployed to run a detailed x-ray on the origin of parts, raw materials and companies involved in producing the weapons, ammunition and military equipment used by the US. And what these tools are revealing is not pretty: a much deeper dependence than most people imagined on inputs, suppliers and logistics routes that directly or indirectly run through China.
AI exposing hidden risks in the military supply chain
According to risk analysis executives, advanced platforms can already accurately map where each critical component is produced, who owns those companies, which countries supply the raw materials and how everything connects until it ends up in a tank, missile, drone or military communication system. That is where artificial intelligence proves its value.
Instead of looking only at the direct supplier, AI digs several layers deeper into the chain and uncovers relationships that, in practice, stayed hidden. A chip that appears to be purchased from a European company, for instance, may depend on an Asian factory that, in turn, buys silicon from suppliers with strong ties to China. Doing this type of tracing manually would be virtually impossible. With machine learning algorithms and access to public and private databases, monitoring becomes continuous and far more complete.
This deep analysis has been showing that China-related vulnerabilities are spread across multiple layers of strategic weapons systems. It is not just the final product that raises concern, but the entire network of companies, carriers, refineries and processors involved up to the point where equipment reaches the battlefield. In scenarios of geopolitical tension, any point in that network can be hit by sanctions, blockades, delays or even manipulation, with a direct impact on the ability of the US to keep its armed forces fully operational.
Another key contribution of AI is uncovering risk patterns that are not obvious at first glance: supplier concentration in a single region, shipping routes that pass through unstable areas, excessive dependence on a specific metal alloy or electronic component produced in just a few places worldwide. With that visibility, it becomes much easier to prioritize where to act first to reduce exposure.
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China, economic warfare and the hollowing out of US manufacturing
In this context, risk specialists openly talk about what they call economic warfare. Their assessment is that China has spent years targeting what they describe as the thick middle of manufacturing: sectors that are neither ultra-simple products nor exclusive cutting-edge technologies, but everything that sustains the defense industrial base, such as iron foundries, magnesium foundries and forgings.
Two decades ago, the United States had more than 360 manufacturers operating in these defense-related areas. Today, that number has reportedly fallen to fewer than 120. This drop was not just the natural result of market forces: practices such as dumping, state subsidies and other aggressive tactics helped shift production capacity out of the country. At the same time, many US companies chose to outsource stages of production in order to compete on price, without seriously weighing the long-term consequences for national security.
The practical effect is that a significant portion of the infrastructure that produces parts for weapons, ammunition and military vehicles has been steadily eroded. It is not that the US has completely lost its ability to manufacture, but that its room for maneuver has become much tighter. In a prolonged conflict or under broad sanctions, quickly reactivating or expanding this domestic industrial base would be a massive challenge.
Autonomy, robotics and AI as a way to reindustrialize
Despite the tense diagnosis, executives in the sector argue that there is a way out. And it runs directly through heavy automation, autonomous workflows, advanced robotics and intensive use of artificial intelligence throughout the production chain. The logic is straightforward: if American industry cannot compete purely on labor costs, it needs to compete on efficiency, precision and automated scale.
In practice, that means redesigning defense factories to be far more digital, with sensors across the entire line, collaborative robots, computer vision for quality inspection and direct integration with demand planning systems. The same AI that today maps supply chain risks can be used to optimize internal production flows, reduce waste, schedule preventive machine maintenance and automatically adjust assembly lines to new part models.
This shift also makes it more feasible to bring back to the US production stages that were moved overseas over the last 20 years. With automation, the unit cost of many parts drops even while paying higher wages. And once you factor in the risk of depending on suppliers under the influence of foreign governments, that residual extra cost starts to look more like a strategic insurance premium.
Impact of geopolitical instability and critical routes like the Strait of Hormuz
The risks identified by AI do not stay on paper. They become even more serious when overlaid with the current geopolitical landscape. Conflicts and rising tensions in regions such as the Middle East and disputes involving Iran are putting the spotlight on strategic routes like the Strait of Hormuz, which carries a significant share of global maritime traffic, including energy and sensitive cargo.
US officials have repeatedly stressed that the United States intends to keep the free flow of traffic in that region, precisely because any blockade or attack there could affect not only oil prices but also logistics chains tied to defense and industry. When AI models incorporate this kind of instability into their simulations, the alert level spikes: suddenly, it is not just who supplies the goods that matters, but also which routes cargo travels before reaching its destination.
This combination of industrial risks and geopolitical tensions has been accelerating plans to diversify routes, strengthen strategic stockpiles and even shift production of certain inputs to locations less exposed to external shocks. Once again, AI comes in as a tool to test scenarios, assess the impact of temporary blockades and simulate alternative transport and supply options.
Reducing dependence on materials controlled by other countries
Behind these discussions, there is a broader movement within government and industry: reducing dependence on materials and components controlled by foreign countries in everything related to defense systems. This ranges from advanced metal alloys and ammunition components to chips, sensors, communication modules and embedded software.
The strategy rests on three main pillars:
- Deep mapping of the supply chain, using AI to identify every touchpoint with companies directly or indirectly controlled by foreign governments;
- Selective reindustrialization, reshoring critical stages back to US soil that cannot be left in the hands of potential strategic adversaries;
- Allied partnerships, reallocating part of production and sourcing to trusted countries in a distributed way, reducing concentration in any single region.
Across all these fronts, AI solutions help bring clarity: they simulate the costs of switching suppliers, identify logistics bottlenecks, calculate transition timelines and highlight where action is most urgent. The goal is not to cut off every single economic relationship with China overnight, but to reduce exposure in sensitive areas so that the defense system is not vulnerable to sudden shocks.
AI, transparency and the challenge of human oversight
Despite all the potential, using AI at scale inside the defense supply chain raises other important debates. One of them is how to make sure these systems do not create a false sense of security. If the underlying data is wrong or incomplete, the model may underestimate China-related risks precisely where vulnerabilities are highest.
That is why concern is growing around algorithm auditing and independent validation of AI-driven analyses. Instead of handing decisions completely over to automated systems, the trend is to keep human experts in the loop reviewing recommendations, especially when they involve drastic changes to suppliers, contracts or logistics routes.
Another issue is the clash between the secrecy culture of the defense industry and the data appetite AI has to work well. The more detailed the system’s information on suppliers, contracts, volumes and routes, the better the analysis. But opening up that data, even inside controlled environments, demands strict governance, access control and constant cybersecurity monitoring.
The future of defense manufacturing with AI at the center
The trajectory that is starting to take shape is one of a much more connected, automated and intelligent American defense manufacturing ecosystem, with AI operating across multiple layers at once. It helps to:
- track the origin of components and expose hidden China-related dependencies;
- simulate crisis scenarios, logistics blockades and economic sanctions;
- optimize production lines and cut internal costs to make reshoring factories to the US viable;
- prioritize investments in new industrial sites, strategic stockpiles and alternative routes.
As these systems mature, decisions move beyond spreadsheets focused purely on short-term cost and start to factor in the full risk cost, including potential long-term disruptions, regional crises and economic disputes between major powers. In this landscape, the ability to use artificial intelligence strategically becomes a competitive advantage in its own right on the global stage.
Ultimately, the debate over AI, manufacturing and defense is not just about technology. It pulls together geopolitics, economics, infrastructure and high-stakes policy decisions. What is really on the line is whether the United States can rebuild a resilient defense industrial base, less dependent on chains controlled by strategic rivals and better aligned with the demands of a world where algorithms, data and automation are part of the battlefield itself.
