Kevin McCauley
©2026 Kevin McCauley
CLSC Quick Takes offer expert analysis of select sources and provide timely insight in a succinct format rather than as formally cited academic products.
Discovery
In a PLA Daily article on March 17, 2026, the authors propose large-scale drone swarm operations potentially providing victory through quantity. They refer to Lanchester’s Square Law where a force’s combat capability is calculated by the square of its number of units. Drone swarms relying on interconnected, intelligent systems can unleash their numerical advantage to achieve victory through large-scale employment. In the past, the pursuit of system peak performance drove up weapons research, development, production, and maintenance costs. Small, low-cost, mass-produced uncrewed systems can supplant that pattern and achieve victory. The authors note the ability to win with quantity is reliant on cost control and mass production of drones as well as logistics to maintain the flow of systems to units.
The authors state that combat effectiveness is based not only on quantity, but also on hard-to-quantify human qualities such as morale, command, and training. The employment of large quantities of drones can mitigate some of the soft factors as they do not suffer physiological fatigue or mental stress over long periods of combat. Still, this article (as do many PLA articles dealing with intelligent warfare) stresses that the human factor remains critical for strategic judgment, planning objectives, and responding to sudden developments.
Analysis
The authors argue employment of large numbers of drone swarms can—to a degree—supplant the qualitative pattern of development and production of high-cost precision weapons systems with a quantitative model to achieve victory with low-cost, mass-produced intelligent uncrewed systems employed in swarms. The authors do not reference the Russia-Ukraine War or Iran’s response to US and Israeli operations; however, it would appear they influenced the authors’ thesis.
While uncrewed systems provide advantages, the authors note that the human factor remains critical for command, planning, and responding to emergencies. The importance of humans in determining victory is echoed by other PLA writers on intelligent warfare who raise questions about the amount of autonomy the PLA will allow for intelligent systems. This reliance on human control could lessen the impact of intelligent, autonomous systems.
Implications
The authors’ advocation of the advantages of quantity could alter the PLA’s modernization plans and priorities. The PLA could place a lower priority on higher cost air, naval, and fire-support weapons systems and increase emphasis on large-scale production and employment of low-cost air, maritime, and ground uncrewed systems employed in swarms—translating quantity into victory.
Strategic Message
PLA theorists are analyzing future trends in warfare, particularly intelligent warfare. These theorists could impact PLA modernization and how it fights in the future. A change in emphasis from high-cost peak performance systems to low-cost, mass-produced systems could influence how adversaries equip and defend in response to changes in PLA war-fighting and modernization priorities. Adversaries would need to expend greater resources on the development and production of low-cost counters to large-scale employment of drone swarms.
Analysis Source: “谈谈‘集群作战’的‘以量取胜’ ” [On “Winning by Quantity” in “Swarm Operations”], PLA Daily, March 17, 2026, http://www.81.cn/szb_223187/szbxq/index.html?paperName=jfjb&paperDate=2026-03-17&paperNumber=07&articleid=974689.
Keywords: PLA modernization, autonomous systems, intelligent warfare, drone swarms, large-scale employment
Kevin McCauley
Kevin McCauley served as senior intelligence officer for the Soviet Union, Russia, the People’s Republic of China (PRC), and Taiwan during 31 years of service in the federal government. He formerly worked as an adjunct at the RAND Corporation and with the US Army Transformation and Training Command (T2COM) G-2 (intelligence) as a China subject matter expert.
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