The United States and China are investing in military systems that can coordinate groups of air, maritime and ground drones, and Taiwan contingencies are a major part of the public discussion. That makes an arms race a credible risk—not a proven outcome. Public exercises and procurement ambitions show progress, but they do not establish mature autonomous combat swarms or which country is ahead.
What does the US-China drone-swarm competition involve?
A drone swarm is not simply a large number of uncrewed vehicles. The military concept depends on coordinating them toward a shared task, sometimes across different domains. The relevant capabilities include communications, navigation when GPS is unavailable or disrupted, autonomy, command and control, endurance, payload and the ability to operate at scale.
“AI-enabled” does not necessarily mean that each drone independently chooses and attacks targets. In the exercises described publicly, people supervised operations or initiated tactics, and the level of autonomy varied. The word “swarm” covers a range of systems and degrees of coordination, not one standard design.
There are signs of investment, but they must be read in context. The Associated Press reported that a Georgetown study published in 2023 found more than one third of the known US and Chinese military-service contracts it examined over an eight-month period in 2020 concerned intelligent uncrewed systems. That is a finding about known contracts in a specific period—not the share of all defense spending or a current spending estimate.
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Who is ahead in military drone swarms?
Public evidence does not establish a clear US or Chinese lead. In its April 12, 2024 reporting, the Associated Press said both countries keep important advances secret and that it was unclear which had an edge. It quoted Skydio CEO Adam Bry characterizing Chinese hardware as stronger and US software as stronger; CNAS analyst Paul Scharre assessed the rivals as roughly at parity. These are different expert judgments, not a verified, comprehensive comparison.
A meaningful comparison would need to cover more than drone numbers. It would include manufacturing capacity, software and autonomy, operation under communications or GPS disruption, range and endurance, payload, affordability, human supervision, and counter-drone defenses. Public reporting does not provide a comparable account of all those factors, nor a comprehensive count of operational autonomous swarms in either country.
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What have exercises and procurement signals actually shown?
The evidence ranges from requests for future capabilities to supervised demonstrations. Those categories should not be treated as proof that a system is already deployed and ready for combat.
| Evidence type | What is publicly reported | What it does—and does not—show |
|---|---|---|
| Procurement ambition | The Associated Press reported Pentagon solicitation specifications for small unmanned maritime “interceptors”: hundreds of miles of transit through contested waters, group operation without GPS, a 1,000-pound payload, attacks on hostile craft traveling at 40 mph, and autonomous adaptation to evasive targets. | These are reported requirements, not evidence that a fielded system meets them. |
| Exercise demonstration | In a 2021 exercise described by AP, one operator supervised more than 100 air and land drones. AP also reported that DARPA’s OFFensive Swarm-Enabled Tactics (OFFSET) work choreographed up to 133 ground and air vehicles at a time for programmed, semi-autonomous reconnaissance and simulated enemy kills. | These were supervised exercises, and the kills were simulated; they do not establish autonomous combat performance. |
| Separate exercise anecdote | AP reported Oregon State professor Julie Adams’s account of a commander handling 45 drones for 2.5 hours after 20 minutes of training. Adams described the approach as “supervisory interaction,” in which a human could stop a command or tactic while a drone acted on its own after a course of action began. | This illustrates one human-supervision arrangement in an exercise, not a universal control model or proof of combat readiness. |
| Forecast | A US Department of Defense research volume published in 2024 forecast that autonomous drone swarms would emerge as a major military capability before 2035. | This is a forecast, not a confirmed schedule or evidence of current fielding. |
Why is Taiwan central to the discussion?
Taiwan is a prominent planning scenario because geography shapes how drones might be used and supplied. A June 2024 Center for a New American Security (CNAS) summary of its tabletop exercise and historical case studies said geography disadvantages the United States: Chinese forces would need to cross 110 miles to reach Taiwan, while US systems would need greater range and endurance and would typically cost more. The report also noted China’s ability to operate from hardened mainland bases.
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That is the report’s scenario analysis, not a prediction that conflict will occur. CNAS recommended that the United States and Taiwan develop varied drone fleets, including longer-range, lower-cost “good enough” systems, autonomous kamikaze drones intended to disrupt naval operations, and robust counter-drone capabilities. These are recommendations for planning, not evidence that the proposed fleets are already available or would determine the outcome of a conflict.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How could militaries defend against large drone attacks?
Defending against many drones is a layered problem: no single interceptor, sensor or electronic-warfare tool can reliably address every type of threat. In its September 2025 report, Countering the Swarm: Protecting the Joint Force in the Drone Age, CNAS argued that cheap drones have widened access to mass precision fires and that future conflict will make drones an unavoidable threat to US forces. It assessed that US counter-drone efforts have lacked sufficient scale and urgency, and framed a Taiwan conflict as potentially involving large, varied salvos and autonomous swarms.
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CNAS recommends combining active defenses—which attempt to defeat drones—with passive measures that reduce damage and help forces keep operating. Its proposals include:
- Integrating different sensors and effectors rather than relying on one defense.
- Using passive resilience, including dispersion, concealment and hardening, so forces can absorb attacks and continue their missions.
- Expanding counter-drone training and testing prototypes under more realistic conditions.
- Developing mobile defenses and stockpiling lower-cost interceptors to address the capacity and cost challenges of mass attacks.
- Investing in AI-enabled sensor processing and command and control, passive sensors, and emerging options such as high-power microwave systems.
CNAS identifies high-power microwaves as particularly promising against swarms; that is the report authors’ assessment, not proof that the technology is a universally effective solution. The US Department of Defense announced a strategy for countering unmanned systems on December 2, 2024, describing unmanned aerial systems as a significant and evolving threat. The announcement establishes the strategy’s existence and broad purpose, not the details of classified capabilities.
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It could encourage faster investment and help spread swarm-related know-how, but the available evidence does not establish a completed, uncontrolled global arms race. The Associated Press reported concerns that software-enabled swarm technology could spread beyond the two major competitors to other states or militant groups. Margarita Konaev, an analyst at Georgetown University’s Center for Security and Emerging Technology, warned in the AP report that unchecked spread “could lead to more instability and conflict around the world.” That is a risk assessment, not a measured outcome.
The AP report also quoted Henry Kissinger and Harvard academic Graham Allison urging restraint before AI becomes embedded in national security systems: “Restraints for AI need to occur before AI is built into the security structure of each society.” The warning captures the timing challenge: rules or limits may be harder to establish after governments have incorporated these capabilities into military planning.
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